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I'm done paying $500 a month for anti-detect browsers after finding this. It's called CloakBrowser. A stealth Chromium that scores 0.9 on reCAPTCHA v3 (same as a real human) and passes 14 out of 14 bot detection tests. - Auto-resolves Cloudflare Turnstile - Beats FingerprintJS and BrowserScan - TLS...

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Hasan Toor

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237,684 Aufrufe • vor 3 Monaten •via X (Twitter)

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Stop paying $20–50/month for your AI agent to browse the web. i built the free version no API keys, no config, no rate limits😳 it's called Hound. An MCP server that does fetch, search, crawl, and screenshot — all keyless and now it ships a native Pi extension, so you get all 6 tools as first-class Pi tools, not through a generic MCP adapter what you get: → web_fetch — anti-bot fetch → clean markdown. PDFs get section maps + auto-OCR. Dead pages auto-recover from the Internet archive (honestly marked, never pretending it's live) → web_search — 10 keyless backends in parallel (DuckDuckGo, Brave, Mojeek, Yandex, Google…) + a local neural reranker → web_crawl — best-first same-domain walk. sitemap mode maps a whole site in one fetch → web_screenshot — anti-bot shots for multimodal models → cache_clear + hound_version what it replaces: -tavily — free tier -firecrawl — $16–50/mo -searXNG + browser + extractor glue — fragile -hound — $0, keyless, forever why it matters: >agent research needs web access, but everyone gates it behind a key or a limit >hound is honest about errors — a 404 says "Page doesn't exist" instead of dumping an error page as if it were content >archive recovery tags source= so the agent knows the content is historical, not live 2-minute setup: -pip install hound-mcp[all] -pi install npm: @houndmcp/hound-mcp-pi -/reload → tools are live. That's it Caveats (read): dataDome, Akamai, Cloudflare Turnstile — no free tool bypasses these hound tries the stealthy browser, then tells you to switch sources the [all] extra is ~100MB (onnxruntime + OCR). Works without it, but full install is recommended not a scraping-at-scale tool. Crawl caps at 100 pages by default — built for agent research Give your agent the web for free
1:12

Stop paying $20–50/month for your AI agent to browse the web. i built the free version no API keys, no config, no rate limits😳 it's called Hound. An MCP server that does fetch, search, crawl, and screenshot — all keyless and now it ships a native Pi extension, so you get all 6 tools as first-class Pi tools, not through a generic MCP adapter what you get: → web_fetch — anti-bot fetch → clean markdown. PDFs get section maps + auto-OCR. Dead pages auto-recover from the Internet archive (honestly marked, never pretending it's live) → web_search — 10 keyless backends in parallel (DuckDuckGo, Brave, Mojeek, Yandex, Google…) + a local neural reranker → web_crawl — best-first same-domain walk. sitemap mode maps a whole site in one fetch → web_screenshot — anti-bot shots for multimodal models → cache_clear + hound_version what it replaces: -tavily — free tier -firecrawl — $16–50/mo -searXNG + browser + extractor glue — fragile -hound — $0, keyless, forever why it matters: >agent research needs web access, but everyone gates it behind a key or a limit >hound is honest about errors — a 404 says "Page doesn't exist" instead of dumping an error page as if it were content >archive recovery tags source= so the agent knows the content is historical, not live 2-minute setup: -pip install hound-mcp[all] -pi install npm: @houndmcp/hound-mcp-pi -/reload → tools are live. That's it Caveats (read): dataDome, Akamai, Cloudflare Turnstile — no free tool bypasses these hound tries the stealthy browser, then tells you to switch sources the [all] extra is ~100MB (onnxruntime + OCR). Works without it, but full install is recommended not a scraping-at-scale tool. Crawl caps at 100 pages by default — built for agent research Give your agent the web for free

Nahid

44,094 Aufrufe • vor 27 Tagen

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch
27:27

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch

GREG ISENBERG

135,017 Aufrufe • vor 4 Monaten

One guy keeps a farm of Mac minis on his desk and says each $600 box brings him $2,000 a month while he sleeps. AND THE HARDWARE ACTUALLY WORKS. But the number is not even the interesting part. The broken part is HOW: his AI no longer sits in a chat window. It sees the screen, moves the mouse itself, types and clicks the interface like a human at a computer. That is it. While most people still run AI in a chat and ask it for text, he sat Claude down right at the computer and put it to work with its hands. He automated not a single task but the workplace itself. How it actually works: on every Mac mini Claude runs with computer use turned on and the official Claude API docs spell it out: screenshot capture, mouse control, keyboard input, desktop automation. The agent opens the browser and the apps itself and runs the boring routine on a schedule: pulls leads, fills the CRM, checks orders, runs QA on the site. One box, one quiet worker that does not sleep and does not ask for a salary. His math is simple: a Mac mini is $600 once, Claude Max is $200 a month, and a live white-collar worker on the same routine costs a business $4,000 and up. So he rents out each node to a client as an AI worker for about $2,000 and 6 Mac minis come out to around $12,000 a month with costs a bit over $1,000 on subscriptions. But the $12,000 is his projection not a revenue dashboard: the video has no client, no task log, no working automation at all. The real asset here is not the stack of hardware but the one repeatable process the agent actually closes. Because a Mac mini on its own earns nothing. The money shows up exactly where the boring browser routine used to be done by hand for a salary and now you can hand it to an agent for the price of a subscription. Computer use is still in beta, almost nobody builds a service on it and the demand for cheap GUI routine is huge. The window is open for literally the next few months. Most people will watch this, laugh at the "$600 AI worker" and close it. And the ones who actually put an agent on one boring task and grind it into a repeat will ride this wave while it is still empty. Would you sit an AI right at your own computer on the boring routine or are you still clicking through it by hand?
1:05

One guy keeps a farm of Mac minis on his desk and says each $600 box brings him $2,000 a month while he sleeps. AND THE HARDWARE ACTUALLY WORKS. But the number is not even the interesting part. The broken part is HOW: his AI no longer sits in a chat window. It sees the screen, moves the mouse itself, types and clicks the interface like a human at a computer. That is it. While most people still run AI in a chat and ask it for text, he sat Claude down right at the computer and put it to work with its hands. He automated not a single task but the workplace itself. How it actually works: on every Mac mini Claude runs with computer use turned on and the official Claude API docs spell it out: screenshot capture, mouse control, keyboard input, desktop automation. The agent opens the browser and the apps itself and runs the boring routine on a schedule: pulls leads, fills the CRM, checks orders, runs QA on the site. One box, one quiet worker that does not sleep and does not ask for a salary. His math is simple: a Mac mini is $600 once, Claude Max is $200 a month, and a live white-collar worker on the same routine costs a business $4,000 and up. So he rents out each node to a client as an AI worker for about $2,000 and 6 Mac minis come out to around $12,000 a month with costs a bit over $1,000 on subscriptions. But the $12,000 is his projection not a revenue dashboard: the video has no client, no task log, no working automation at all. The real asset here is not the stack of hardware but the one repeatable process the agent actually closes. Because a Mac mini on its own earns nothing. The money shows up exactly where the boring browser routine used to be done by hand for a salary and now you can hand it to an agent for the price of a subscription. Computer use is still in beta, almost nobody builds a service on it and the demand for cheap GUI routine is huge. The window is open for literally the next few months. Most people will watch this, laugh at the "$600 AI worker" and close it. And the ones who actually put an agent on one boring task and grind it into a repeat will ride this wave while it is still empty. Would you sit an AI right at your own computer on the boring routine or are you still clicking through it by hand?

Sorven

11,948 Aufrufe • vor 1 Monat

Matthew Gallagher Built a $401M Company in Year One with 2 People. And the tool behind it? Claude Code. This year he's on track for $1.8B. Sam Altman predicted this. It's happening now. The problem? It costs money. API credits stack up. Monthly bills keep growing. Every prompt eats your budget. Every project drains your wallet faster. Until now. Two methods. 99% cheaper. One is completely free. Forever. $0. Not a trial. This video breaks down both step by step. ↓ Let me put this in perspective. $100-$500. That's monthly. That's what you spend. That's $6,000/year on API credits. Just to use a tool you haven't shipped anything with. The $401M guy? Spending $0. Same capability. Shipping weekly. Different cost structure. Different results. Different life. I'm about to hand you his cost structure for free. ↓ Open source vs closed source. Pay attention. Closed source: Claude. GPT-4. Pay per token. Meter always running. Open source: Qwen. Llama. Mistral. Free to download. Free to run. Free forever. No meter. No tokens. No bill. Here's what nobody tells you: 80% of coding tasks? Open source handles them. More than handles them. Writes clean code. Debugs errors. Generates boilerplate. Handles routine work perfectly. You're paying premium prices for tasks that don't need premium intelligence. That's hiring a brain surgeon to put on a bandaid. Smart play: Free models for the 80%. Paid credits for the 20%. That's what the $401M guy does. That's what this video teaches you. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 1: Ollama. Local. Free. Forever. Download it. Pull a model. Point Claude Code at it. Done. No internet needed. No API keys required. No monthly subscription. No token counting ever. No bill. Today. Tomorrow. Ever. Your data never leaves your computer. Complete privacy. Complete freedom. Claude Code thinks it's talking to the cloud. It's talking to your laptop. For $0. The video walks through every step: Every config file. Every variable. Every command. Every click. If you can follow a recipe, you can do this. People who set this up 3 months ago? Saved $300-$1,500 since then. Workflow didn't change one bit. ↓ Hardware you need: 16GB RAM: 7B models run smooth. 32GB RAM: 32B models run comfortable. 64GB + GPU: biggest models available. No GPU? Still works. Just slower. Few extra seconds. That's it. Your $1,500 laptop is sitting there running Chrome and Spotify. Put it to work saving you $200/month instead. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 2: Open Router. Free Cloud. No Hardware. Weak machine? Don't want local setup? This method is for you. Free AI models in the cloud. No download. No hardware. Configure Claude Code to route through Open Router. The config: Base URL: Open Router API. API key: free Open Router key. Default Sonnet: free. Default Opus: free. Default Haiku: free. Small fast model: free. Subagent model: free. Free. Free. Free. Free. Free across the board. Same interface. Same commands. Same workflow. Zero cost. Copy the config from the video. Paste it. Save $200/month. Starting today. Right now. ↓ When to use which: Ollama (local): Best for privacy. Best for offline work. Best for unlimited usage. Best if you have decent hardware. Open Router (cloud): Best for weak machines. Best for instant setup. Best for trying different models. Best if you don't want to manage anything. Both methods: Best for 80% of your daily work. Still use paid Claude for: Complex architecture. Multi-file refactoring. Deep reasoning tasks. The 20% that actually needs it. $20/month instead of $200/month. Same output. 90% less cost. ↓ The math that should make you angry. You (current): $200-$500/month. $2,400-$6,000/year. $7,200-$18,000 over 3 years. You (after this video): $20-$50/month. $240-$600/year. $720-$1,800 over 3 years. Savings over 3 years: $6,480-$16,200. That's a used car. That's seed money. That's 6 months of rent. All from one 25-minute video. All from 15 minutes of configuration. Highest ROI 25 minutes you'll spend this year. ↓ The limitations. I won't lie to you. Open source is not Opus. Not as smart on complex reasoning. Not as good at long-context tasks. Makes more mistakes on nuanced problems. But they are: Free. Capable. Getting better monthly. Good enough for 80% of daily work. Smart cost management isn't being cheap. It's being strategic. Expensive tool when it matters. Free tool when it doesn't. ↓ The one-person billion-dollar company is coming. $401M in year one proved it's possible. The building blocks: AI that codes: Claude Code. Way to run it free: this video. Distribution: the internet. Customers: everyone. Only missing ingredient? Someone who builds. Not reads about building. Not saves posts about building. Not bookmarks videos about building. Builds. Tools are free. Knowledge is free. Opportunity is screaming. You're still "thinking about it." ↓ Your action plan: Tonight: Watch the video. Tomorrow morning: Set up Ollama or Open Router. Tomorrow afternoon: Build something. Anything. This week: Build a second thing. Faster. This month: Charge someone for it. One video. One setup. One weekend. $0 cost. Unlimited potential. Or keep paying $200/month for something you could get free. Keep consuming instead of building. Keep planning instead of shipping. Matthew Gallagher didn't plan a $401M company. He built it. Full video attached. Every method. Every config. Every tradeoff. 25 minutes. Your move. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses.
25:22

Matthew Gallagher Built a $401M Company in Year One with 2 People. And the tool behind it? Claude Code. This year he's on track for $1.8B. Sam Altman predicted this. It's happening now. The problem? It costs money. API credits stack up. Monthly bills keep growing. Every prompt eats your budget. Every project drains your wallet faster. Until now. Two methods. 99% cheaper. One is completely free. Forever. $0. Not a trial. This video breaks down both step by step. ↓ Let me put this in perspective. $100-$500. That's monthly. That's what you spend. That's $6,000/year on API credits. Just to use a tool you haven't shipped anything with. The $401M guy? Spending $0. Same capability. Shipping weekly. Different cost structure. Different results. Different life. I'm about to hand you his cost structure for free. ↓ Open source vs closed source. Pay attention. Closed source: Claude. GPT-4. Pay per token. Meter always running. Open source: Qwen. Llama. Mistral. Free to download. Free to run. Free forever. No meter. No tokens. No bill. Here's what nobody tells you: 80% of coding tasks? Open source handles them. More than handles them. Writes clean code. Debugs errors. Generates boilerplate. Handles routine work perfectly. You're paying premium prices for tasks that don't need premium intelligence. That's hiring a brain surgeon to put on a bandaid. Smart play: Free models for the 80%. Paid credits for the 20%. That's what the $401M guy does. That's what this video teaches you. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 1: Ollama. Local. Free. Forever. Download it. Pull a model. Point Claude Code at it. Done. No internet needed. No API keys required. No monthly subscription. No token counting ever. No bill. Today. Tomorrow. Ever. Your data never leaves your computer. Complete privacy. Complete freedom. Claude Code thinks it's talking to the cloud. It's talking to your laptop. For $0. The video walks through every step: Every config file. Every variable. Every command. Every click. If you can follow a recipe, you can do this. People who set this up 3 months ago? Saved $300-$1,500 since then. Workflow didn't change one bit. ↓ Hardware you need: 16GB RAM: 7B models run smooth. 32GB RAM: 32B models run comfortable. 64GB + GPU: biggest models available. No GPU? Still works. Just slower. Few extra seconds. That's it. Your $1,500 laptop is sitting there running Chrome and Spotify. Put it to work saving you $200/month instead. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses. ↓ Method 2: Open Router. Free Cloud. No Hardware. Weak machine? Don't want local setup? This method is for you. Free AI models in the cloud. No download. No hardware. Configure Claude Code to route through Open Router. The config: Base URL: Open Router API. API key: free Open Router key. Default Sonnet: free. Default Opus: free. Default Haiku: free. Small fast model: free. Subagent model: free. Free. Free. Free. Free. Free across the board. Same interface. Same commands. Same workflow. Zero cost. Copy the config from the video. Paste it. Save $200/month. Starting today. Right now. ↓ When to use which: Ollama (local): Best for privacy. Best for offline work. Best for unlimited usage. Best if you have decent hardware. Open Router (cloud): Best for weak machines. Best for instant setup. Best for trying different models. Best if you don't want to manage anything. Both methods: Best for 80% of your daily work. Still use paid Claude for: Complex architecture. Multi-file refactoring. Deep reasoning tasks. The 20% that actually needs it. $20/month instead of $200/month. Same output. 90% less cost. ↓ The math that should make you angry. You (current): $200-$500/month. $2,400-$6,000/year. $7,200-$18,000 over 3 years. You (after this video): $20-$50/month. $240-$600/year. $720-$1,800 over 3 years. Savings over 3 years: $6,480-$16,200. That's a used car. That's seed money. That's 6 months of rent. All from one 25-minute video. All from 15 minutes of configuration. Highest ROI 25 minutes you'll spend this year. ↓ The limitations. I won't lie to you. Open source is not Opus. Not as smart on complex reasoning. Not as good at long-context tasks. Makes more mistakes on nuanced problems. But they are: Free. Capable. Getting better monthly. Good enough for 80% of daily work. Smart cost management isn't being cheap. It's being strategic. Expensive tool when it matters. Free tool when it doesn't. ↓ The one-person billion-dollar company is coming. $401M in year one proved it's possible. The building blocks: AI that codes: Claude Code. Way to run it free: this video. Distribution: the internet. Customers: everyone. Only missing ingredient? Someone who builds. Not reads about building. Not saves posts about building. Not bookmarks videos about building. Builds. Tools are free. Knowledge is free. Opportunity is screaming. You're still "thinking about it." ↓ Your action plan: Tonight: Watch the video. Tomorrow morning: Set up Ollama or Open Router. Tomorrow afternoon: Build something. Anything. This week: Build a second thing. Faster. This month: Charge someone for it. One video. One setup. One weekend. $0 cost. Unlimited potential. Or keep paying $200/month for something you could get free. Keep consuming instead of building. Keep planning instead of shipping. Matthew Gallagher didn't plan a $401M company. He built it. Full video attached. Every method. Every config. Every tradeoff. 25 minutes. Your move. Follow Himanshu Kumar for more breakdowns that turn free tools into real businesses.

Himanshu Kumar

13,599 Aufrufe • vor 4 Monaten

CANCEL Your Weekend Plans, and Learn Claude Code Today. $5,000/month. $10,000/month. $20,000/month. People are building entire apps and charging clients thousands using Claude Code. You're still Googling 'how to center a div.' While you're binge-watching a show you won't remember next week, a 19 year old with zero coding experience just built a $5,000 SaaS product in one afternoon using the tool I'm about to break down. Same laptop. Same internet. Same 24 hours. He has Claude Code. You have Netflix. That's the only difference. This YouTube video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Save this post. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. ↓ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. ↓ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. ↓ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. ↓ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. ↓ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. ↓ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. ↓ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. ↓ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. ↓ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. ↓ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. ↓ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. ↓ 12. Set Up Claude.MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. ↓ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. ↓ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. ↓ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. ↓ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. ↓ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. ↓ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. ↓ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumar for daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.
35:48

CANCEL Your Weekend Plans, and Learn Claude Code Today. $5,000/month. $10,000/month. $20,000/month. People are building entire apps and charging clients thousands using Claude Code. You're still Googling 'how to center a div.' While you're binge-watching a show you won't remember next week, a 19 year old with zero coding experience just built a $5,000 SaaS product in one afternoon using the tool I'm about to break down. Same laptop. Same internet. Same 24 hours. He has Claude Code. You have Netflix. That's the only difference. This YouTube video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Save this post. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. ↓ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. ↓ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. ↓ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. ↓ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. ↓ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. ↓ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. ↓ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. ↓ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. ↓ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. ↓ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. ↓ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. ↓ 12. Set Up Claude.MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. ↓ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. ↓ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. ↓ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. ↓ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. ↓ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. ↓ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. ↓ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumar for daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

101,793 Aufrufe • vor 4 Monaten

I pay Claude $20 a month. Most $TAO holders do too. There is a stack you can build in 15 minutes that fixes that completely. It runs on Bittensor. It costs $10. You do not write a single line of code. Here is how every AI chat product actually works under the hood. Three layers. Always three. The model. The brain. GPT, Claude, DeepSeek, Kimi, GLM. The inference layer. The GPU that runs the model when you hit send. The interface. The chat box you actually look at. ChatGPT and Claude bundle all three and hand you the result. You cannot change the model. You cannot change the inference. The interface is non-negotiable. Every prompt you type goes to a server run by a private company whose terms of service can quietly change next month. The anti-ChatGPT move is to pick each layer yourself. This is where $TAO comes in. Chutes is Subnet 64 on Bittensor. It is the inference layer. Open source models like DeepSeek, Kimi, GLM, and Llama get served by a global network of miner-operated GPUs. Validators score the output quality. The best inference wins the emissions. You hit send. A miner somewhere runs your prompt. You get the answer back. The TAO you hold is in part paying for the GPU you just used. The basic stack is one URL. chutes. ai/chat No account. No API key. No setup. Switch models mid-conversation. Web search built in. Image generation. File uploads. Free. The advanced stack is Chutes plus TypingMind. One-time license. No recurring fee. Plugins, agents, custom personas, a prompt library you build over months. Full model switching between Chutes, OpenAI, and Anthropic from the same window. Total cost: $10 a month to Chutes for inference. That $10 buys you $50 in actual usage. But here is the signal most people missed inside this story. Chutes ran a free tier until February. Then they killed it. Then they raised the minimum to $10 in May. Most people saw that as bad news. It is the opposite. Free things on the internet do not last. Real products do. Chutes is becoming a real product. A subnet that generates actual revenue from actual users paying actual money for actual AI inference. That is what $43 million in Q1 network revenue looks like at the individual subnet level. And there is one more thing ChatGPT and Claude cannot offer that Chutes already has. Trusted Execution Environments. Your prompt gets encrypted on your device, shipped to a confidential compute GPU, and the lock only breaks inside the chip. The miner running the model physically cannot read your prompt. ChatGPT cannot promise that. Claude cannot promise that. Bittensor already built it. You are holding a network where the subnets are generating real revenue, shipping real privacy infrastructure, and replacing $20 a month centralised subscriptions with $10 a month decentralised inference. The people who use the product always understand the investment better than the people who only watch the price.
8:27

I pay Claude $20 a month. Most $TAO holders do too. There is a stack you can build in 15 minutes that fixes that completely. It runs on Bittensor. It costs $10. You do not write a single line of code. Here is how every AI chat product actually works under the hood. Three layers. Always three. The model. The brain. GPT, Claude, DeepSeek, Kimi, GLM. The inference layer. The GPU that runs the model when you hit send. The interface. The chat box you actually look at. ChatGPT and Claude bundle all three and hand you the result. You cannot change the model. You cannot change the inference. The interface is non-negotiable. Every prompt you type goes to a server run by a private company whose terms of service can quietly change next month. The anti-ChatGPT move is to pick each layer yourself. This is where $TAO comes in. Chutes is Subnet 64 on Bittensor. It is the inference layer. Open source models like DeepSeek, Kimi, GLM, and Llama get served by a global network of miner-operated GPUs. Validators score the output quality. The best inference wins the emissions. You hit send. A miner somewhere runs your prompt. You get the answer back. The TAO you hold is in part paying for the GPU you just used. The basic stack is one URL. chutes. ai/chat No account. No API key. No setup. Switch models mid-conversation. Web search built in. Image generation. File uploads. Free. The advanced stack is Chutes plus TypingMind. One-time license. No recurring fee. Plugins, agents, custom personas, a prompt library you build over months. Full model switching between Chutes, OpenAI, and Anthropic from the same window. Total cost: $10 a month to Chutes for inference. That $10 buys you $50 in actual usage. But here is the signal most people missed inside this story. Chutes ran a free tier until February. Then they killed it. Then they raised the minimum to $10 in May. Most people saw that as bad news. It is the opposite. Free things on the internet do not last. Real products do. Chutes is becoming a real product. A subnet that generates actual revenue from actual users paying actual money for actual AI inference. That is what $43 million in Q1 network revenue looks like at the individual subnet level. And there is one more thing ChatGPT and Claude cannot offer that Chutes already has. Trusted Execution Environments. Your prompt gets encrypted on your device, shipped to a confidential compute GPU, and the lock only breaks inside the chip. The miner running the model physically cannot read your prompt. ChatGPT cannot promise that. Claude cannot promise that. Bittensor already built it. You are holding a network where the subnets are generating real revenue, shipping real privacy infrastructure, and replacing $20 a month centralised subscriptions with $10 a month decentralised inference. The people who use the product always understand the investment better than the people who only watch the price.

2xnmore

27,088 Aufrufe • vor 2 Monaten

CANCEL Your Weekend Plans, & Learn Claude Code Today. This Claude Code teaches more about vibe-coding in 30 mins than most tutorials do in hours. Save this, it'll change how you build forever People are building entire apps and charging clients $5,000 to $20,000 using Claude Code. This Claude Code video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. ↓ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. ↓ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. ↓ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. ↓ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. ↓ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. ↓ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. ↓ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. ↓ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. ↓ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. ↓ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. ↓ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. ↓ 12. Set Up Claude MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. ↓ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. ↓ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. ↓ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. ↓ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. ↓ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. ↓ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. ↓ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumarfor daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.
35:48

CANCEL Your Weekend Plans, & Learn Claude Code Today. This Claude Code teaches more about vibe-coding in 30 mins than most tutorials do in hours. Save this, it'll change how you build forever People are building entire apps and charging clients $5,000 to $20,000 using Claude Code. This Claude Code video is a goldmine. Full Claude Code tutorial. Beginner to pro. Every feature. Every setup step. Every best practice. Zero prior knowledge needed. Save it. Watch it tonight. Not tomorrow. Tonight. Follow Himanshu Kumar so you don't miss the breakdowns for each feature. This is your complete Claude Code roadmap. Lose it and you lose the next 12 months of income. ↓ 1. Understand What Claude Code Actually Is. You think Claude Code is just another chatbot. It's not. And that misunderstanding is why you're broke. ChatGPT gives you text. Claude Code gives you software. It runs in your terminal. It reads your entire codebase. It writes files directly to your project. It runs commands on your machine. It debugs errors autonomously. It builds features end to end. You're not chatting. You're deploying a developer. One that works 24/7. Never asks for a raise. Never calls in sick. Never pushes broken code at 5 PM on a Friday. People are charging clients $5,000-$10,000 for apps they built with Claude Code in 3 hours. And you didn't even know this tool existed because you're still asking ChatGPT to write you a to-do list. The gap between you and people making money with AI isn't intelligence. It's awareness. Now you're aware. Save this post. Follow Himanshu Kumar for the complete breakdown of every Claude Code feature. ↓ 2. Set Up Claude Code Properly. Most people quit here. "It's too complicated." "I don't know terminal." "I'll set it up later." Later never comes. And "complicated" means "I watched for 30 seconds and gave up." The setup takes 10 minutes. Install Node.js. Install Claude Code via npm. Authenticate your account. Open your terminal. Done. 10 minutes. You spent longer this morning deciding what to have for breakfast. The video walks through every single click. Every command. Every screen. Assuming you know absolutely nothing. If you can download an app on your phone, you can set up Claude Code. It's the same level of difficulty. But you'll still tell yourself it's "too technical" because that excuse is more comfortable than admitting you're just scared to try something new. This is the setup that everything else builds on. Skip it and nothing works. ↓ 3. Use the Desktop App. You don't even need to live in the terminal if you don't want to. Claude Code has a desktop app. Clean interface. Visual feedback. Everything you need without touching command line. But here's the thing most people don't know: The desktop app isn't just a pretty wrapper. It lets you manage projects visually. See file changes in real time. Switch between projects instantly. The people making money with Claude Code use the desktop app for client projects because it's faster to manage multiple builds simultaneously. You're still opening 14 browser tabs to organize one project. They open one app and everything's there. Efficiency isn't a personality trait. It's a tool choice. Save this post. Follow Himanshu Kumar for the desktop app workflow that handles 5 client projects at once. ↓ 4. Install the Right Dependencies. This is where beginners silently fail and blame the tool. Claude Code needs certain dependencies installed to work properly. Miss one and everything breaks. Then you go on Twitter and say "Claude Code doesn't work." It works fine. You just didn't read the setup guide. The video covers every dependency you need. What to install. How to install it. How to verify it's working. No guessing. No Stack Overflow rabbit holes at midnight. No "why isn't this working" for 3 hours. Watch the dependency section once. Follow every step. Never deal with setup issues again. You spent more time last week troubleshooting a printer than this takes. ↓ 5. Work Inside Your Code Editor. Claude Code integrates directly with your code editor. VS Code. Cursor. Whatever you use. It's not a separate window you alt-tab between. It's right there. In your workflow. You type a request. Claude writes the code. The code appears in your editor. You review it. Accept it. Done. No copy pasting between windows. No reformatting code that got mangled in transit. No "which version was the right one." It's like pair programming with someone who never gets distracted, never argues about naming conventions, and actually writes code that works on the first try. Your current coding process is: Google the problem, read 5 answers on Stack Overflow, copy the wrong one, debug for an hour, find the right one, paste it in, break something else, repeat. Claude Code's process is: describe what you want, get working code, move on with your life. Same hour. One method produces working software. The other produces frustration and a browser history full of Stack Overflow tabs. Stop coding the hard way. Save this post. Follow Himanshu Kumar for code editor setup guides and integration tips. ↓ 6. Master Basic Usage. Most people learn 5% of a tool and say they "know" it. You "know" Photoshop because you can crop an image. You "know" Excel because you can sum a column. You "know" Claude Code because you asked it one question. Basic usage means: How to give Claude Code context about your project. How to ask for changes to existing code. How to generate new files and features. How to review what Claude produces. How to iterate when the output isn't perfect. These basics are the foundation of everything. Skip them and every advanced feature feels confusing. Master them and every advanced feature feels obvious. The video breaks down each one with real examples. Not theory. Actual usage on actual projects. You've been using AI tools at 5% capacity and wondering why your results are 5% of what others get. Save this post. Follow Himanshu Kumar for daily Claude Code usage tips. ↓ 7. Learn Every Command. Claude Code has commands that most users never discover. Because most users type one message and expect magic. That's not how professionals use it. Professionals use specific commands that tell Claude Code exactly what to do, how to do it, and what constraints to follow. The difference between a beginner and someone making $10K/month with Claude Code is knowing which command to use and when. The video walks through every single one. Not just what they do. But when to use each one. And why one command is better than another for specific situations. You've been using Claude Code like a hammer. These commands turn it into a full toolbox. Stop treating a power tool like a blunt instrument. Save this post. Follow Himanshu Kumar for the command cheat sheet I use daily. ↓ 8. Understand Modes and Shortcuts. Speed matters. The person who builds an app in 2 hours charges $5,000. The person who builds the same app in 2 days charges $2,000. Same app. Same quality. Different speed. Different income. Claude Code has modes that change how it operates. And shortcuts that cut your workflow time in half. Most people don't know either exists. They use Claude Code in default mode for everything. Like driving a car in first gear on the highway. Technically it works. But everyone is passing you. The video shows you every mode. Every shortcut. Every time-saving trick that separates the people charging $2,000 per project from the people charging $10,000. Speed is money. Literally. Save this post. Follow Himanshu Kumar for the shortcuts that cut my build time by 60%. ↓ 9. Write a Proper Planning Prompt. This is the section that separates amateurs from professionals. And it's the section most people skip. A planning prompt tells Claude Code what you're building before you start building it. Architecture. File structure. Technologies. Features. Constraints. Edge cases. Without a planning prompt, Claude Code guesses. And guessing produces garbage. With a planning prompt, Claude Code executes a clear plan. And clear plans produce working software. The video shows you exactly how to write a planning prompt that makes Claude Code produce professional-grade output on the first try. "But I just want to start coding." That's why your code breaks every time. That's why you restart projects 4 times. That's why nothing you build ever gets finished. Because you refuse to plan. A 5-minute planning prompt saves you 5 hours of debugging. But you'd rather skip the 5 minutes and suffer through the 5 hours because patience isn't your thing. And that's exactly why you're not making money. Planning is the most underpaid skill in coding. And the most overpaid when you master it. Save this post. Follow Himanshu Kumar for the planning prompt templates I use for every client project. ↓ 10. Choose the Right Model. Claude Code lets you select different AI models. Not all models are the same. Not all tasks need the same model. Using the most powerful model for a simple task wastes credits. Using a basic model for a complex task wastes time. The video explains: Which model to use for quick fixes. Which model to use for complex architecture. Which model to use for debugging. Which model to use for code generation. Most people pick one model and use it for everything. That's like using a sledgehammer to hang a picture frame. Model selection is strategy. And strategy is money. The people making $10K/month with Claude Code are strategic about every credit they spend. You're burning through credits because you use the most expensive model to write a hello world. ↓ 11. Use Git and Version Control. If you're not using version control, you're one mistake away from losing everything. Claude Code integrates with Git. Every change tracked. Every version saved. Every mistake reversible. Without Git: Claude makes a change. It breaks something. You can't undo it. You start over. 3 hours wasted. With Git: Claude makes a change. It breaks something. You roll back in 5 seconds. Keep working. Version control isn't optional. It's insurance. And the people not using it are the same people who say "I lost my entire project" like it's something that just happens. It doesn't just happen. It happens because you didn't set up Git. The video walks through the entire Git integration. Save this post. Follow Himanshu Kumar for the Git workflow that's saved every project I've ever built. ↓ 12. Set Up Claude MD and Memory. This is the feature that makes Claude Code feel like a real team member instead of a stranger you explain everything to every time. ClaudeMD is a memory file. You tell Claude Code about your project once. It remembers forever. Coding style preferences. Project architecture decisions. Technology stack. File naming conventions. Business logic rules. Without ClaudeMD: Every new conversation starts from zero. You explain the same things repeatedly. Output is inconsistent. With ClaudeMD: Claude knows your project. Claude follows your rules. Claude produces consistent, professional code. The difference between a sloppy freelancer and a reliable agency is consistency. Claude. MD gives you consistency without the agency overhead. Most people don't set this up and wonder why Claude Code gives different answers every time. ↓ 13. Automate with Tasks. This is where Claude Code stops being a tool and starts being an employee. Tasks let you define repeating workflows. "Every time I push code, run tests." "Every time I create a new file, add boilerplate." "Every time I start a session, check for errors." Automated. Hands-free. Consistent. You're doing these things manually every single day. The same checks. The same steps. The same routine. Tasks do them automatically. So you can focus on the work that actually makes money. Every manual task you automate is time you get back. And time is the only thing you can never make more of. Save this post. Follow Himanshu Kumar for the task automation templates that run my entire workflow. ↓ 14. Explore Features Most People Never Touch. The video covers features that 95% of Claude Code users don't know exist. Because they watched a 3-minute TikTok about Claude Code and think they're experts now. They're not. They're using 5% of a tool that can do everything. The full tutorial goes deep into features that most tutorials skip because they're "too advanced." They're not too advanced. They're too valuable for lazy creators to bother explaining. This video explains all of them. Clearly. For beginners. The 5% of features you don't know about are the 5% that make people rich. ↓ Let's zoom out. I just broke down 14 sections of Claude Code. Setup and installation. Desktop app. Dependencies. Code editor integration. Basic usage. Commands. Modes and shortcuts. Planning prompts. Model selection. Git and version control. Memory and Claude. MD. Tasks and automation. Advanced features. All in one video. All free. All beginner friendly. The person who masters even half of these in the next 2 weeks will be in the top 1% of Claude Code users. The top 1% of Claude Code users are the ones charging $5,000-$10,000 per project and building them in a single afternoon. Everyone else is asking ChatGPT to fix their resume. Same tools. Same access. Completely different outcomes. Because one person treats AI like a toy. And the other treats it like a business. ↓ Here's the hard truth nobody wants to hear. You don't have a talent problem. You don't have an intelligence problem. You don't have a resources problem. You have an action problem. Everything I just listed has a free tutorial right here in the attached video. 33 minutes. That's it. 33 minutes to learn the tool that people are using to build $5,000-$20,000/month businesses. You spent more time today scrolling Twitter than it takes to watch this video. You spent more time this week watching Netflix than it takes to master Claude Code basics. You spent more time this month doing nothing than it would take to completely change your income. The information is free. The tool is accessible. The opportunity is here. The only thing missing is you caring enough to start. ↓ CANCEL your plans this week. This isn't optional anymore. The people learning Claude Code right now will be building apps for the people who didn't learn it. That's not a prediction. That's already happening. Companies are replacing $150/hour developers with one person and Claude Code. If you code: learn Claude Code or become half as valuable by next year. If you don't code: learn Claude Code or miss the biggest opportunity to start earning from tech without a CS degree. There's no path forward that doesn't include AI coding tools. None. You have one window. Right now. This week. ↓ Here's your action plan for the next 7 days: Day 1: Watch the full video. Install Claude Code. Set up dependencies. Day 2: Learn basic usage. Try 5 different commands. Day 3: Write your first planning prompt. Build a small project. Day 4: Set up Claude. MD. Configure your memory file. Day 5: Master modes and shortcuts. Build a second project faster. Day 6: Set up Git integration. Automate with tasks. Day 7: Build something real. A tool, an app, a website. Ship it. 7 days. One tool. One completely different skill set. One completely different income potential. Or 7 more days of scrolling Twitter watching other people build things while you "plan to start." Your call. ↓ This is the most important video you'll watch this year. 33 minutes. Complete Claude Code mastery. From zero to building real projects. Save this post. Come back to it every single day this week. Check off each section as you complete it. Follow Himanshu Kumarfor daily Claude Code breakdowns, advanced tutorials, and the exact workflows that are turning beginners into $10K/month builders. The only thing between you and $10K/month with Claude Code is this video and 7 days. Don't waste them. You Must Follow me Himanshu Kumar, so i can send you DM.

Himanshu Kumar

85,668 Aufrufe • vor 3 Monaten

i ran 1,000 agents across the last month of the internet looking for one thing: people who are already paying real money to do a job by hand 24 days later that list has paid me $104,513. the agents cost $4,100. the workers ran on Claude Sonnet 5, which had been out for two days when i started. the verifier ran on Fable 5, back online the day before that. cheap model doing the reading, expensive model doing the judging. none of that is the interesting part. the interesting part has a name, and it is called Graph Engineering: independent work runs side by side instead of in a queue, dependent work keeps its order, and nothing is allowed to grade its own homework. one agent asking one question at a time would still be reading today. wired as a graph, the same models did this: → 1,000 workers, 16 live at once, each handed its own slice: one forum, one thread, one review section. no worker ever saw another's work → every worker hunted one phrase shape: a person admitting what they already pay. "i pay someone to do this every morning." "we keep a guy just for this task." → a separate Fable 5 verifier picked up every hit on fresh context and killed anything without a name and a number attached → all of it collected into one file 1,940,000 discussions read. 41,812 hits. 3,147 survived the verifier. that verifier killed 92% of what the workers brought back, and that number is the entire business. people complain for free. the ones naming who they pay and how much are buyers. 14 hours from launch to one finished file. one agent doing the same work end to end needs 224 hours straight and forgets the beginning by the middle. 3,147 buyers collapsed into 63 repeating jobs. the most profitable one was so boring i almost deleted it on the first pass. 412 people paying a human $740 a month to do the same dull thing by hand. nobody had built for it because nobody wants to build it. i emailed all 412 before writing a line of code. 96 replied. 34 prepaid a year at $1,400. $47,600 in the bank before the product existed. i cost six times less than the person they were already paying, and that closed every call. built it in 11 days, for people who had already written me their own spec. then the remaining 3,147 got the email: 26 more prepaid a year, 97 signed monthly at $129, and four paid $2,000 each to have it fitted to their process. $47,600 + $36,400 + $12,513 + $8,000 = $104,513 take the Graph Engineering out and there is no story. one agent runs out of memory before it finishes 1.9m discussions. a searcher grading its own findings hands you 41,812 pieces of garbage. a thousand workers sharing one context overwrite each other by hour two. fan out where the work is independent. verify on fresh context. isolate every worker. three moves, 24 days, and a month of the internet becomes one file you can sell from. i wrote the whole method down: what a node is, how to spot the dependencies that were never real, and six graphs you can run this week. free ↓ bookmark this
0:48

i ran 1,000 agents across the last month of the internet looking for one thing: people who are already paying real money to do a job by hand 24 days later that list has paid me $104,513. the agents cost $4,100. the workers ran on Claude Sonnet 5, which had been out for two days when i started. the verifier ran on Fable 5, back online the day before that. cheap model doing the reading, expensive model doing the judging. none of that is the interesting part. the interesting part has a name, and it is called Graph Engineering: independent work runs side by side instead of in a queue, dependent work keeps its order, and nothing is allowed to grade its own homework. one agent asking one question at a time would still be reading today. wired as a graph, the same models did this: → 1,000 workers, 16 live at once, each handed its own slice: one forum, one thread, one review section. no worker ever saw another's work → every worker hunted one phrase shape: a person admitting what they already pay. "i pay someone to do this every morning." "we keep a guy just for this task." → a separate Fable 5 verifier picked up every hit on fresh context and killed anything without a name and a number attached → all of it collected into one file 1,940,000 discussions read. 41,812 hits. 3,147 survived the verifier. that verifier killed 92% of what the workers brought back, and that number is the entire business. people complain for free. the ones naming who they pay and how much are buyers. 14 hours from launch to one finished file. one agent doing the same work end to end needs 224 hours straight and forgets the beginning by the middle. 3,147 buyers collapsed into 63 repeating jobs. the most profitable one was so boring i almost deleted it on the first pass. 412 people paying a human $740 a month to do the same dull thing by hand. nobody had built for it because nobody wants to build it. i emailed all 412 before writing a line of code. 96 replied. 34 prepaid a year at $1,400. $47,600 in the bank before the product existed. i cost six times less than the person they were already paying, and that closed every call. built it in 11 days, for people who had already written me their own spec. then the remaining 3,147 got the email: 26 more prepaid a year, 97 signed monthly at $129, and four paid $2,000 each to have it fitted to their process. $47,600 + $36,400 + $12,513 + $8,000 = $104,513 take the Graph Engineering out and there is no story. one agent runs out of memory before it finishes 1.9m discussions. a searcher grading its own findings hands you 41,812 pieces of garbage. a thousand workers sharing one context overwrite each other by hour two. fan out where the work is independent. verify on fresh context. isolate every worker. three moves, 24 days, and a month of the internet becomes one file you can sell from. i wrote the whole method down: what a node is, how to spot the dependencies that were never real, and six graphs you can run this week. free ↓ bookmark this

Argona

19,695 Aufrufe • vor 21 Tagen

Made $530,000 with Ai Bot that started with $313. Didn't know how to code. Now this bots run 24/7 printing money while sleeping. I've made the exact step-by-step guide to build this Claude Code Polymarket trading bot. Prompts. Code. Risk settings. Paper trading checklist. Everything from zero to running bot. It's free. For 24 hours. After that I'm charging $499 for it. To grab it right now: 1. Comment "Claude Bot" 2. Like and Retweet this post 3. Follow me Himanshu Kumar ( I can't send DMs to non-followers ) I'm DMing everyone who Complete the 3 steps. I spent hundreds of thousands hiring developers because he was too scared to learn. Then learned Claude Code. Built algorithmic trading systems. $313 → $530,000. You have the same tools available right now. And you're using them to ask ChatGPT for Instagram captions. This attached video is a goldmine. Full live walkthrough. Claude Code building actual Polymarket trading bots. From zero. Every line of code. Every decision explained. Now let me break down why everything you're doing in trading is wrong and exactly how to fix it. Save this post. You'll hate yourself if you lose it. ↓ Let's start with why you keep losing money. You already know the answer. You just won't admit it. You overtrade. Every. Single. Day. You see a candle move. You feel something. You enter. No plan. No edge. No reason. Just feelings. Then it goes against you. You feel something else. Panic. Anger. Denial. You move your stop loss. Or you didn't set one at all. "It'll come back." It doesn't come back. So you take another trade. A revenge trade. Bigger size this time. Because you need to "make it back." That one fails too. Now you're emotional. Now you're tilted. Now you're using leverage you have no business touching. 40x. 50x. 100x. On a trade you entered because a candle looked "bullish" and some guy on Twitter said "send it." You get liquidated. Close the laptop. Punch something. Tell yourself you'll be "more disciplined" tomorrow. Tomorrow comes. Same cycle. Same result. Same liquidation. You've been doing this for months. Maybe years. And you still think the problem is your strategy. The problem isn't your strategy. The problem is you. Save this post right now. What I'm about to show you is the only way to remove yourself from the equation. Follow Himanshu Kumar so you don't miss any of this. ↓ Here's what's actually killing your account. It's not the market. The market doesn't care about you. It's not your indicators. RSI works fine. MACD works fine. They all "work." It's not your timeframe. It's not your broker. It's not the "manipulation." It's four things: 1. Emotions. You hold losers because hope feels better than loss. You cut winners because fear feels stronger than greed. You size up when angry. You skip trades when scared. Your emotional state determines your position size. That's insane. And you know it's insane. But you keep doing it. 2. Overtrading. You take 15 trades a day. Maybe 5 of them had actual setups. The other 10 were boredom. Boredom trades are the most expensive hobby in human history. 3. Leverage. You use 20x-50x on trades where you're not even sure about the direction. That's not trading. That's a casino with a nicer interface. 4. Fees. You're smashing market orders. Paying spread. Paying commission. On 15 trades a day. Your broker makes more money from your account than you do. Think about that. Your broker is profitable on your account. You're not. You're the product. Not the trader. These four things are why 90% of traders lose. Not bad luck. Not the market. You. Save this post and follow Himanshu Kumar because the solution is coming next. ↓ The solution is painfully obvious. Remove yourself from the equation. Not partially. Not "I'll be more disciplined." Not "I'll journal my trades." Not "I'll meditate before trading." Completely remove yourself. Build a bot. Let the bot trade. You go live your life. The bot doesn't feel emotions. The bot doesn't overtrade. The bot doesn't use reckless leverage. The bot doesn't smash market orders and bleed fees. The bot follows the rules. Every single time. Without exception. Without "just this once." Without "I have a feeling about this one." Rules in. Execution out. No human in the middle to mess everything up. That's algorithmic trading. And before your ego jumps in with "but I'm different, I have discipline" — No you don't. Your account balance proves you don't. If you had discipline, your account would be green. It's not. So you don't. Accept it. Automate it. Move on. This is the hardest truth in trading. Your discipline will always fail. A bot's won't. Save this post. Follow Himanshu Kumar for the exact bot setup that removes your emotions permanently. ↓ "But I don't know how to code." Neither did he. The guy in this video didn't know how to code for most of his life. Got held back in 7th grade. People counted him out early. Spent years building apps and SaaS businesses without writing a single line of code. Hired developers on Upwork instead. Spent hundreds of thousands of dollars paying other people to build what he could have built himself. Because he was scared to learn. That fear cost him years. And hundreds of thousands of dollars. Sound familiar? You're doing the same thing right now. Not with developers. But with your time. You're spending thousands of hours trading manually because you're scared to learn the thing that would make trading automatic. The fear of learning to code is costing you more than any bad trade ever did. Because every month you trade manually is a month of emotional decisions, overleveraged entries, and unnecessary losses that a bot would never make. And here's the thing that should really frustrate you: AI does the hard parts now. You don't need a computer science degree. You don't need to work at a hedge fund. You don't need to be "good at math." Claude Code writes the code for you. You just need to think clearly about trading ideas. That's it. If you can describe a strategy in English, Claude can build it in Python. "I don't know how to code" stopped being a valid excuse in 2024. It's 2026. You're 2 years late on that excuse. Find a new one. Or stop making excuses entirely. Save this post. Follow Himanshu Kumar because I'm showing you how people with zero coding experience are building profitable bots. ↓ The process that actually makes money. Three letters. R. B. I. Research. Backtest. Implement. That's it. That's the entire process. Every single day. Research: Find an idea. A pattern. A market inefficiency. Don't trade it yet. Don't even think about trading it yet. Just research it. Backtest: Test the idea against historical data. Does it work? Not "does it look good on one chart." Does it work across thousands of trades? Across different market conditions? Across in-sample AND out-of-sample data? If no, kill it. Find another idea. If yes, move to step 3. Implement: Build the bot. Deploy it. Paper trade first. Then live with small size. Scale only on evidence. Research. Backtest. Implement. Every day. No exceptions. You know what your current process is? Feel. Enter. Pray. F. E. P. Feel bullish. Enter a trade. Pray it works. That's not a process. That's gambling with a TradingView subscription. RBI is the only process that works. Save this post. Tattoo it on your forearm. Follow Himanshu Kumar for daily RBI breakdowns. ↓ What Claude Code actually does that your manual process can't. You can maybe test 3-5 strategy ideas per week. Manually adjusting parameters. Manually checking results. Manually writing code (badly). Claude Code tests 50-100 ideas per week. With parallel agents running simultaneously. Multiple strategies being built, tested, and validated at the same time. While you sleep. The guy in this video spends 4-8 hours a day building systems with Claude Code. Not trading. Building. Research. Backtest. Implement. Then iterate. Improve. Optimize. Every day the systems get better. Every day the edge compounds. Every day the bots get smarter. While you? You spend 4-8 hours a day staring at charts making the same mistakes you made last month. Same indicators. Same patterns. Same entries. Same losses. He's iterating forward. You're running in circles. Same 8 hours per day. Completely different outcomes. Because he's building systems. And you're feeding a casino. Stop feeding the casino. Start building the machine. Save this post and follow Himanshu Kumar for the Claude Code workflow that iterates strategies while you sleep. ↓ Jim Simons. That's the benchmark. You probably don't know who Jim Simons is. And that tells me everything about how seriously you take trading. Jim Simons. Mathematician. Founded Renaissance Technologies. Built a net worth of $31 billion. 100% from algorithmic trading. Not one single manual trade. Not one "gut feeling" entry. Not one RSI divergence. Not one "smart money concept." Algorithms. Bots. Systems. Data. $31 billion. His fund averaged 66% annual returns for over 30 years. While you're excited about making $200 on a trade that you'll give back tomorrow. The best trader in human history never placed a manual trade in his life. And you think your edge is staring at a 5-minute chart with bloodshot eyes at 2 AM? Your edge is building the system. Not being inside it. Jim Simons is the benchmark. Everything else is noise. Save this post. Follow Himanshu Kumar because I'm building toward the same goal and showing every step publicly. ↓ What you need to understand about patience. This is not get-rich-overnight. The guy in this video says it directly: "This channel is not for people looking to get rich overnight. It's not plug and play. There are no shortcuts. If you're impatient, this probably isn't for you." And that's exactly why most people will fail at this. Because you want results now. Today. This trade. You don't want to spend a week building a bot. You don't want to paper trade for 2 weeks. You don't want to test 50 ideas to find 1 that works. You want to copy someone's bot, run it live with your rent money, and be rich by Friday. That's why you'll be broke by Friday. The guy making $2.3M spent months iterating. Testing. Failing. Rebuilding. Testing again. He was patient when you would have quit. He was calm when you would have panicked. He was consistent when you would have given up. Patience isn't just a virtue in trading. It's the only virtue. Without it, everything else fails. Impatience is the most expensive personality trait in trading. Save this post. Follow Himanshu Kumar and learn to build systems with the patience that actually pays. ↓ The live streams where the real learning happens. The YouTube video is the trailer. The live streams are the movie. Real-time bot building. Real-time questions answered. Real code shown. Real mistakes made and fixed. Not polished highlight reels where everything works perfectly. Actual development. Where things break. Where strategies fail. Where code doesn't compile. Where the fix takes 2 hours. Because that's what real development looks like. And seeing the messy parts is more valuable than any polished tutorial. Because when your bot breaks at 3 AM, you need to know how to fix it. Not just how to celebrate when it works. The streams mix beginner and advanced. Start with how to automate trading. How to use AI for code generation. Then dive into the daily work. Claude Code. Parallel agents. Constant iteration. Live debugging. 4-8 hours of real algorithmic trading development. Live. Uncut. No filter. Most "trading education" shows you the wins. This shows you the work. Save this post. Follow Himanshu Kumar for the stream schedules and breakdowns. ↓ The belief that changes everything. Code is the greatest equalizer. Not money. Not connections. Not a degree. Not where you grew up. Not what school you went to. Code. Once you can build systems, you can build anything. For the rest of your life. A trading bot today. A SaaS product tomorrow. An automation business next month. A completely different life next year. The skill isn't "algorithmic trading." The skill is building systems. And that skill transfers to everything. The guy who can build a trading bot can also build a lead gen tool. Can also build a content pipeline. Can also build a SaaS product. Can also build literally anything that runs on logic and code. One skill. Infinite applications. And AI makes learning it 100x easier than it was 5 years ago. You don't need to be smart. You don't need talent. You need Claude Code and the willingness to sit down and build something instead of consuming content about building something. Building is the skill. Everything else is entertainment disguised as education. Save this post. Follow Himanshu Kumar because I'm showing you how to build, not just how to watch. ↓ If any of this applies to you, pay attention. If you've lost money from overtrading. If you've been liquidated. If you know trading is the vehicle but manual execution keeps crashing you. If you've tried "being more disciplined" and it never lasted more than a week. If you keep saying "next month I'll start automating." If you've spent more money on courses than you've made from trading. There is a better way. It's not a magic indicator. It's not a signal group. It's not a $997 mentorship from a guy who makes money teaching, not trading. It's building your own system. A system that trades without emotion. A system that follows rules without exception. A system that runs while you sleep. A system that compounds while you live your life. That's the answer. It's always been the answer. You've just been too scared to accept that the solution requires building something instead of buying something. ↓ What the next 30 days look like if you actually commit. Week 1: Watch the video. Learn Claude Code basics. Build your first simple strategy. Run your first backtest. Week 2: Iterate. Let Claude improve the strategy. Run Monte Carlo validation. Paper trade. Week 3: Go live with $50-100. Tiny positions. Watch every trade. Compare to paper results. Week 4: Scale based on evidence. Not based on excitement. Not based on one good day. Based on data. 30 days from now you either have a running bot that trades without your emotions destroying every position. Or you're exactly where you are right now. Reading another post. Making another promise. Breaking it by Tuesday. Same 30 days either way. Different actions. Different results. Different life. ↓ Full video tutorial attached. Live bot building with Claude Code. From zero to running Polymarket trading bot. Every line of code. Every decision explained. The video is free. Claude Code is available now. The market is open 24/7. The only thing standing between you and a profitable trading bot is the same thing that's been standing there for months. You. Get out of your own way. Follow Himanshu Kumar for daily AI trading bot breakdowns, live build sessions, and the full RBI process. Save this post. Watch the video. Build the bot. Or keep trading manually and keep losing. The choice has never been easier. And you've never been more stubborn about making the wrong one.
18:53

Made $530,000 with Ai Bot that started with $313. Didn't know how to code. Now this bots run 24/7 printing money while sleeping. I've made the exact step-by-step guide to build this Claude Code Polymarket trading bot. Prompts. Code. Risk settings. Paper trading checklist. Everything from zero to running bot. It's free. For 24 hours. After that I'm charging $499 for it. To grab it right now: 1. Comment "Claude Bot" 2. Like and Retweet this post 3. Follow me Himanshu Kumar ( I can't send DMs to non-followers ) I'm DMing everyone who Complete the 3 steps. I spent hundreds of thousands hiring developers because he was too scared to learn. Then learned Claude Code. Built algorithmic trading systems. $313 → $530,000. You have the same tools available right now. And you're using them to ask ChatGPT for Instagram captions. This attached video is a goldmine. Full live walkthrough. Claude Code building actual Polymarket trading bots. From zero. Every line of code. Every decision explained. Now let me break down why everything you're doing in trading is wrong and exactly how to fix it. Save this post. You'll hate yourself if you lose it. ↓ Let's start with why you keep losing money. You already know the answer. You just won't admit it. You overtrade. Every. Single. Day. You see a candle move. You feel something. You enter. No plan. No edge. No reason. Just feelings. Then it goes against you. You feel something else. Panic. Anger. Denial. You move your stop loss. Or you didn't set one at all. "It'll come back." It doesn't come back. So you take another trade. A revenge trade. Bigger size this time. Because you need to "make it back." That one fails too. Now you're emotional. Now you're tilted. Now you're using leverage you have no business touching. 40x. 50x. 100x. On a trade you entered because a candle looked "bullish" and some guy on Twitter said "send it." You get liquidated. Close the laptop. Punch something. Tell yourself you'll be "more disciplined" tomorrow. Tomorrow comes. Same cycle. Same result. Same liquidation. You've been doing this for months. Maybe years. And you still think the problem is your strategy. The problem isn't your strategy. The problem is you. Save this post right now. What I'm about to show you is the only way to remove yourself from the equation. Follow Himanshu Kumar so you don't miss any of this. ↓ Here's what's actually killing your account. It's not the market. The market doesn't care about you. It's not your indicators. RSI works fine. MACD works fine. They all "work." It's not your timeframe. It's not your broker. It's not the "manipulation." It's four things: 1. Emotions. You hold losers because hope feels better than loss. You cut winners because fear feels stronger than greed. You size up when angry. You skip trades when scared. Your emotional state determines your position size. That's insane. And you know it's insane. But you keep doing it. 2. Overtrading. You take 15 trades a day. Maybe 5 of them had actual setups. The other 10 were boredom. Boredom trades are the most expensive hobby in human history. 3. Leverage. You use 20x-50x on trades where you're not even sure about the direction. That's not trading. That's a casino with a nicer interface. 4. Fees. You're smashing market orders. Paying spread. Paying commission. On 15 trades a day. Your broker makes more money from your account than you do. Think about that. Your broker is profitable on your account. You're not. You're the product. Not the trader. These four things are why 90% of traders lose. Not bad luck. Not the market. You. Save this post and follow Himanshu Kumar because the solution is coming next. ↓ The solution is painfully obvious. Remove yourself from the equation. Not partially. Not "I'll be more disciplined." Not "I'll journal my trades." Not "I'll meditate before trading." Completely remove yourself. Build a bot. Let the bot trade. You go live your life. The bot doesn't feel emotions. The bot doesn't overtrade. The bot doesn't use reckless leverage. The bot doesn't smash market orders and bleed fees. The bot follows the rules. Every single time. Without exception. Without "just this once." Without "I have a feeling about this one." Rules in. Execution out. No human in the middle to mess everything up. That's algorithmic trading. And before your ego jumps in with "but I'm different, I have discipline" — No you don't. Your account balance proves you don't. If you had discipline, your account would be green. It's not. So you don't. Accept it. Automate it. Move on. This is the hardest truth in trading. Your discipline will always fail. A bot's won't. Save this post. Follow Himanshu Kumar for the exact bot setup that removes your emotions permanently. ↓ "But I don't know how to code." Neither did he. The guy in this video didn't know how to code for most of his life. Got held back in 7th grade. People counted him out early. Spent years building apps and SaaS businesses without writing a single line of code. Hired developers on Upwork instead. Spent hundreds of thousands of dollars paying other people to build what he could have built himself. Because he was scared to learn. That fear cost him years. And hundreds of thousands of dollars. Sound familiar? You're doing the same thing right now. Not with developers. But with your time. You're spending thousands of hours trading manually because you're scared to learn the thing that would make trading automatic. The fear of learning to code is costing you more than any bad trade ever did. Because every month you trade manually is a month of emotional decisions, overleveraged entries, and unnecessary losses that a bot would never make. And here's the thing that should really frustrate you: AI does the hard parts now. You don't need a computer science degree. You don't need to work at a hedge fund. You don't need to be "good at math." Claude Code writes the code for you. You just need to think clearly about trading ideas. That's it. If you can describe a strategy in English, Claude can build it in Python. "I don't know how to code" stopped being a valid excuse in 2024. It's 2026. You're 2 years late on that excuse. Find a new one. Or stop making excuses entirely. Save this post. Follow Himanshu Kumar because I'm showing you how people with zero coding experience are building profitable bots. ↓ The process that actually makes money. Three letters. R. B. I. Research. Backtest. Implement. That's it. That's the entire process. Every single day. Research: Find an idea. A pattern. A market inefficiency. Don't trade it yet. Don't even think about trading it yet. Just research it. Backtest: Test the idea against historical data. Does it work? Not "does it look good on one chart." Does it work across thousands of trades? Across different market conditions? Across in-sample AND out-of-sample data? If no, kill it. Find another idea. If yes, move to step 3. Implement: Build the bot. Deploy it. Paper trade first. Then live with small size. Scale only on evidence. Research. Backtest. Implement. Every day. No exceptions. You know what your current process is? Feel. Enter. Pray. F. E. P. Feel bullish. Enter a trade. Pray it works. That's not a process. That's gambling with a TradingView subscription. RBI is the only process that works. Save this post. Tattoo it on your forearm. Follow Himanshu Kumar for daily RBI breakdowns. ↓ What Claude Code actually does that your manual process can't. You can maybe test 3-5 strategy ideas per week. Manually adjusting parameters. Manually checking results. Manually writing code (badly). Claude Code tests 50-100 ideas per week. With parallel agents running simultaneously. Multiple strategies being built, tested, and validated at the same time. While you sleep. The guy in this video spends 4-8 hours a day building systems with Claude Code. Not trading. Building. Research. Backtest. Implement. Then iterate. Improve. Optimize. Every day the systems get better. Every day the edge compounds. Every day the bots get smarter. While you? You spend 4-8 hours a day staring at charts making the same mistakes you made last month. Same indicators. Same patterns. Same entries. Same losses. He's iterating forward. You're running in circles. Same 8 hours per day. Completely different outcomes. Because he's building systems. And you're feeding a casino. Stop feeding the casino. Start building the machine. Save this post and follow Himanshu Kumar for the Claude Code workflow that iterates strategies while you sleep. ↓ Jim Simons. That's the benchmark. You probably don't know who Jim Simons is. And that tells me everything about how seriously you take trading. Jim Simons. Mathematician. Founded Renaissance Technologies. Built a net worth of $31 billion. 100% from algorithmic trading. Not one single manual trade. Not one "gut feeling" entry. Not one RSI divergence. Not one "smart money concept." Algorithms. Bots. Systems. Data. $31 billion. His fund averaged 66% annual returns for over 30 years. While you're excited about making $200 on a trade that you'll give back tomorrow. The best trader in human history never placed a manual trade in his life. And you think your edge is staring at a 5-minute chart with bloodshot eyes at 2 AM? Your edge is building the system. Not being inside it. Jim Simons is the benchmark. Everything else is noise. Save this post. Follow Himanshu Kumar because I'm building toward the same goal and showing every step publicly. ↓ What you need to understand about patience. This is not get-rich-overnight. The guy in this video says it directly: "This channel is not for people looking to get rich overnight. It's not plug and play. There are no shortcuts. If you're impatient, this probably isn't for you." And that's exactly why most people will fail at this. Because you want results now. Today. This trade. You don't want to spend a week building a bot. You don't want to paper trade for 2 weeks. You don't want to test 50 ideas to find 1 that works. You want to copy someone's bot, run it live with your rent money, and be rich by Friday. That's why you'll be broke by Friday. The guy making $2.3M spent months iterating. Testing. Failing. Rebuilding. Testing again. He was patient when you would have quit. He was calm when you would have panicked. He was consistent when you would have given up. Patience isn't just a virtue in trading. It's the only virtue. Without it, everything else fails. Impatience is the most expensive personality trait in trading. Save this post. Follow Himanshu Kumar and learn to build systems with the patience that actually pays. ↓ The live streams where the real learning happens. The YouTube video is the trailer. The live streams are the movie. Real-time bot building. Real-time questions answered. Real code shown. Real mistakes made and fixed. Not polished highlight reels where everything works perfectly. Actual development. Where things break. Where strategies fail. Where code doesn't compile. Where the fix takes 2 hours. Because that's what real development looks like. And seeing the messy parts is more valuable than any polished tutorial. Because when your bot breaks at 3 AM, you need to know how to fix it. Not just how to celebrate when it works. The streams mix beginner and advanced. Start with how to automate trading. How to use AI for code generation. Then dive into the daily work. Claude Code. Parallel agents. Constant iteration. Live debugging. 4-8 hours of real algorithmic trading development. Live. Uncut. No filter. Most "trading education" shows you the wins. This shows you the work. Save this post. Follow Himanshu Kumar for the stream schedules and breakdowns. ↓ The belief that changes everything. Code is the greatest equalizer. Not money. Not connections. Not a degree. Not where you grew up. Not what school you went to. Code. Once you can build systems, you can build anything. For the rest of your life. A trading bot today. A SaaS product tomorrow. An automation business next month. A completely different life next year. The skill isn't "algorithmic trading." The skill is building systems. And that skill transfers to everything. The guy who can build a trading bot can also build a lead gen tool. Can also build a content pipeline. Can also build a SaaS product. Can also build literally anything that runs on logic and code. One skill. Infinite applications. And AI makes learning it 100x easier than it was 5 years ago. You don't need to be smart. You don't need talent. You need Claude Code and the willingness to sit down and build something instead of consuming content about building something. Building is the skill. Everything else is entertainment disguised as education. Save this post. Follow Himanshu Kumar because I'm showing you how to build, not just how to watch. ↓ If any of this applies to you, pay attention. If you've lost money from overtrading. If you've been liquidated. If you know trading is the vehicle but manual execution keeps crashing you. If you've tried "being more disciplined" and it never lasted more than a week. If you keep saying "next month I'll start automating." If you've spent more money on courses than you've made from trading. There is a better way. It's not a magic indicator. It's not a signal group. It's not a $997 mentorship from a guy who makes money teaching, not trading. It's building your own system. A system that trades without emotion. A system that follows rules without exception. A system that runs while you sleep. A system that compounds while you live your life. That's the answer. It's always been the answer. You've just been too scared to accept that the solution requires building something instead of buying something. ↓ What the next 30 days look like if you actually commit. Week 1: Watch the video. Learn Claude Code basics. Build your first simple strategy. Run your first backtest. Week 2: Iterate. Let Claude improve the strategy. Run Monte Carlo validation. Paper trade. Week 3: Go live with $50-100. Tiny positions. Watch every trade. Compare to paper results. Week 4: Scale based on evidence. Not based on excitement. Not based on one good day. Based on data. 30 days from now you either have a running bot that trades without your emotions destroying every position. Or you're exactly where you are right now. Reading another post. Making another promise. Breaking it by Tuesday. Same 30 days either way. Different actions. Different results. Different life. ↓ Full video tutorial attached. Live bot building with Claude Code. From zero to running Polymarket trading bot. Every line of code. Every decision explained. The video is free. Claude Code is available now. The market is open 24/7. The only thing standing between you and a profitable trading bot is the same thing that's been standing there for months. You. Get out of your own way. Follow Himanshu Kumar for daily AI trading bot breakdowns, live build sessions, and the full RBI process. Save this post. Watch the video. Build the bot. Or keep trading manually and keep losing. The choice has never been easier. And you've never been more stubborn about making the wrong one.

Himanshu Kumar

37,638 Aufrufe • vor 4 Monaten

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen
49:49

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen

Moon Dev

26,010 Aufrufe • vor 5 Monaten

I’ve been using GPT-5.6 Sol internally for the past two months, I've spent probably 25+ billion tokens. Here’s my review and comparison to Fable 5: > Let's start with the analogy because everyone seems to be giving theirs - GPT-5.6 is likely the last version of the GPT-5 training run series. It's kind of like an athlete at their peak. Through years of experience in the game, they've become the most reliable player and has the highest game IQ. But, there's no more room to grow. Fable on the other hand, being essentially the first version of a new training run, is the first round draft pick rookie. Raw talent mixed with the energy only a young person would have results in some incredible plays we didn't think possible, but also mistakes due to lack of experience. But that rookie will only improve and likely will be better than the veteran ever was because it's a new game and a new era. > GPT-5.6 is genuinely better at long, sustained work. With /goal, I've had it running complex projects for days with almost no intervention. It built a Minecraft-style game, kept adding features and mobs after the core game worked, and only stopped because I stopped the run. I never felt as though I had to jump in and guide it back to the right path. > It keeps finding useful work when you give it a concrete finish line. I had it recreate Excel with a loop. It inspected the real desktop excel app with Computer Use, comparing that against its own build, and closing the gaps. I stopped it after six days after it had built an incredible amount of functionality. > It's faster than other models in two different ways. The raw generation speed is higher, something OpenAI has been putting effort into. But it also takes a shorter path to solutions. It wanders less, changes less code, and generally knows how to get things done directly. In daily use, it feels about 2-3x times faster than Fable. That's my impression, not a controlled benchmark. The difference is large enough that I notice it constantly. > It works well across a wide range of tasks. I use it for one-line edits, quick questions, browser chores, and multi-day builds without changing my prompting style. Speaking of browser control, its the best ever I've used. To the point where I actually use it often. If a task lives on a website, GPT-5.6 usually opens the browser and does it there instead of asking for an API key or forcing everything through the terminal. When I switched back to GPT-5.5, it went straight to the command line even when the browser was clearly the better tool. > And it can handle real browser work, not just toy demos. During a data import, I had it monitor Supabase and resize instances as the load changed. It stayed on the dashboard, adjusted capacity, and checked the result without an API or a custom script. > I also gave it a full Google Workspace migration. It moved Forward Future from to preserved the old aliases, and configured MX, SPF, and DKIM. Before a consequential save, it stopped, explained exactly what would change, and waited for confirmation. > The reasoning setting matters a lot. Light is good for questions and small edits. High and Extra High are the sweet spots for serious work. Ultra usually takes longer than the extra thinking is worth and burns tokens. > I love that 5.6 is split into 3 sizes. Not only can you control speed and cost that way, but you still also have the thinking effort setting for each of them. Very precise controls. I just wish Codex automatically routed my prompts for me. > Its personality is blunt and a little bland. Claude feels warmer and more natural to talk to. GPT-5.6 is more clinical, but I like that for work. It gives me enough explanation and rarely pads the answer. I usually have to ask Fable to explain things more simply and/or more concise. > Its front-end taste has improved, but the default is predictable. Left alone, it turns websites into PowerPoint decks with huge statements and hard section breaks. The good news is that it takes design direction well and can revise without destroying the parts that already work. > It still makes confident mistakes. I asked it to rebuild parts of a system, and it told me the job was finished. Later, I found out it wasn't. Bits of its internal process also leak into the answer occasionally. > Claude Fable is more naturally autonomous on large, open-ended projects. GPT-5.6 is easier to reach for. I don't need to invent a huge project to justify using it. It works just as well for a small edit or browser chore. > GPT-5.6 is also cheaper. Sol costs $5 per million input tokens and $30 per million output tokens. Fable costs $10 and $50. Cached input is cheaper too. Still, cost per finished task matters more than cost per token. > GPT-5.6 isn't the best at everything, and it still needs supervision. But it generates faster, wanders less, works at almost any scale, and wastes less of my time. It's the model I have the most confidence in to get the job done right the first time. I put together a full breakdown with all the tests, prompts, and examples on a site. You can read it here:
7:46

I’ve been using GPT-5.6 Sol internally for the past two months, I've spent probably 25+ billion tokens. Here’s my review and comparison to Fable 5: > Let's start with the analogy because everyone seems to be giving theirs - GPT-5.6 is likely the last version of the GPT-5 training run series. It's kind of like an athlete at their peak. Through years of experience in the game, they've become the most reliable player and has the highest game IQ. But, there's no more room to grow. Fable on the other hand, being essentially the first version of a new training run, is the first round draft pick rookie. Raw talent mixed with the energy only a young person would have results in some incredible plays we didn't think possible, but also mistakes due to lack of experience. But that rookie will only improve and likely will be better than the veteran ever was because it's a new game and a new era. > GPT-5.6 is genuinely better at long, sustained work. With /goal, I've had it running complex projects for days with almost no intervention. It built a Minecraft-style game, kept adding features and mobs after the core game worked, and only stopped because I stopped the run. I never felt as though I had to jump in and guide it back to the right path. > It keeps finding useful work when you give it a concrete finish line. I had it recreate Excel with a loop. It inspected the real desktop excel app with Computer Use, comparing that against its own build, and closing the gaps. I stopped it after six days after it had built an incredible amount of functionality. > It's faster than other models in two different ways. The raw generation speed is higher, something OpenAI has been putting effort into. But it also takes a shorter path to solutions. It wanders less, changes less code, and generally knows how to get things done directly. In daily use, it feels about 2-3x times faster than Fable. That's my impression, not a controlled benchmark. The difference is large enough that I notice it constantly. > It works well across a wide range of tasks. I use it for one-line edits, quick questions, browser chores, and multi-day builds without changing my prompting style. Speaking of browser control, its the best ever I've used. To the point where I actually use it often. If a task lives on a website, GPT-5.6 usually opens the browser and does it there instead of asking for an API key or forcing everything through the terminal. When I switched back to GPT-5.5, it went straight to the command line even when the browser was clearly the better tool. > And it can handle real browser work, not just toy demos. During a data import, I had it monitor Supabase and resize instances as the load changed. It stayed on the dashboard, adjusted capacity, and checked the result without an API or a custom script. > I also gave it a full Google Workspace migration. It moved Forward Future from to preserved the old aliases, and configured MX, SPF, and DKIM. Before a consequential save, it stopped, explained exactly what would change, and waited for confirmation. > The reasoning setting matters a lot. Light is good for questions and small edits. High and Extra High are the sweet spots for serious work. Ultra usually takes longer than the extra thinking is worth and burns tokens. > I love that 5.6 is split into 3 sizes. Not only can you control speed and cost that way, but you still also have the thinking effort setting for each of them. Very precise controls. I just wish Codex automatically routed my prompts for me. > Its personality is blunt and a little bland. Claude feels warmer and more natural to talk to. GPT-5.6 is more clinical, but I like that for work. It gives me enough explanation and rarely pads the answer. I usually have to ask Fable to explain things more simply and/or more concise. > Its front-end taste has improved, but the default is predictable. Left alone, it turns websites into PowerPoint decks with huge statements and hard section breaks. The good news is that it takes design direction well and can revise without destroying the parts that already work. > It still makes confident mistakes. I asked it to rebuild parts of a system, and it told me the job was finished. Later, I found out it wasn't. Bits of its internal process also leak into the answer occasionally. > Claude Fable is more naturally autonomous on large, open-ended projects. GPT-5.6 is easier to reach for. I don't need to invent a huge project to justify using it. It works just as well for a small edit or browser chore. > GPT-5.6 is also cheaper. Sol costs $5 per million input tokens and $30 per million output tokens. Fable costs $10 and $50. Cached input is cheaper too. Still, cost per finished task matters more than cost per token. > GPT-5.6 isn't the best at everything, and it still needs supervision. But it generates faster, wanders less, works at almost any scale, and wastes less of my time. It's the model I have the most confidence in to get the job done right the first time. I put together a full breakdown with all the tests, prompts, and examples on a site. You can read it here:

Matthew Berman

187,086 Aufrufe • vor 1 Monat

Don't Buy a Mac Mini for Clawdbot: The Secret $10,000 Architecture That Costs You Nothing clawdbot might be the reason you feel like you need a ten thousand dollar computer right now but i am about to show you why that fomo is going to leave you broke. if you have been watching everyone rush out to buy mac minis and mac studios just to run open claw or some local models you are witnessing a massive transfer of wealth from your pocket to apple for no reason. there is a specific setup i use that costs almost nothing and keeps my main machine safe from whatever these autonomous agents are doing. if you stick with me i will walk you through the exact architecture of a professional trading system that handles the heavy lifting without you needing to drop a single rack on hardware most people are scared of running these bots on their main computer because they don't want an agent messing with their personal files or browser sessions. instead of buying a second mac mini for six hundred dollars you can just go to the top left of your screen and create a brand new user profile. this acts like a completely isolated sandbox where you can install all your trading tools and agents without them ever seeing your main data. it is essentially like getting a free computer for the price of five minutes of clicking around your settings but what if you aren't on a mac or you need to access your system while you are traveling without carrying three laptops in your backpack. this is where the first loop of professional automation starts to close because i use something called chrome remote desktop to bridge the gap. this allows me to leave a dedicated machine running in a safe place while i access the full desktop environment from a tablet or a cheap laptop anywhere in the world. it solves the mobility issue but it still doesn't solve the problem of those massive ten thousand dollar price tags for high end mac pros if you are a pc user or just someone who doesn't want to own physical hardware yet you should look into a windows vps through a provider like contabo. most developers will tell you to use a linux terminal but if you aren't a coder yet you need a visual interface you can actually see. getting a windows server allows you to log in and see a desktop just like your home computer for about fifteen dollars a month. i usually recommend at least twelve gigabytes of ram to keep things from getting janky when you are running multiple browser windows and agents at once now you might be thinking that the whole point of the big hardware was to run local models like kimi or glm to save on api costs. i spent years thinking i had to own the machines myself and i even spent hundreds of thousands on developers before i realized i could just do this myself. the secret to running those massive open source models without the ten thousand dollar investment is renting gpu power by the hour. sites like lambda labs let you spin up a monster machine that can run any model in existence for just a couple dollars an hour this is the ultimate pivot because it allows you to test if your strategy actually prints money before you commit to the hardware. you can turn the server on when you are iterating and turn it off the second you are done which keeps your overhead near zero. if you haven't proven that your bot can pay for itself yet then buying a mac studio is just an expensive hobby rather than a business move. there is a much bigger loophole involving the anthropic subscriptions that most people are completely overlooking right now right now i am using a specific plan with claude code that costs about two hundred dollars a month but it lets me run open claw all day without hitting api limits. if i were paying for those same tokens through the standard api i would probably be spending hundreds of dollars every single day. it is a massive cost savings that allows you to iterate and fail until you find a winning strategy without draining your bank account. even if they eventually close this loophole or snitch on the usage patterns it serves as the perfect training ground for a data dog the goal is to find a system that works with a smaller or cheaper model like haiku before you ever try to scale up to the heavy weights. if you can make a strategy profitable using a less intelligent and cheaper model then you know you have found real alpha. once you have that foundation you can decide if it finally makes sense to build your own custom pc rig which will always be half the price of an apple machine. i am an apple guy so i usually pay the tax anyway but i only do it once the system is already generating enough to cover the cost ten times over i believe that code is the great equalizer because it took me from losing money and getting liquidated to having fully automated systems doing the work for me. i had to learn to live with the iterations and the failures on youtube to get to this point of clarity. the universe tends to get out of your way once you make a non negotiable contract with yourself to see the process through to the end. you don't need the flashy hardware or the most expensive setup to start winning in this game stay focused on the logic and the data rather than the hype and the fomo that everyone else is falling for. if you can master the bridge between renting power and owning your logic you will be ahead of ninety nine percent of the people in this space. the path to a fully automated life isn't paved with expensive gadgets but with the discipline to iterate until the system finally prints
16:04

Don't Buy a Mac Mini for Clawdbot: The Secret $10,000 Architecture That Costs You Nothing clawdbot might be the reason you feel like you need a ten thousand dollar computer right now but i am about to show you why that fomo is going to leave you broke. if you have been watching everyone rush out to buy mac minis and mac studios just to run open claw or some local models you are witnessing a massive transfer of wealth from your pocket to apple for no reason. there is a specific setup i use that costs almost nothing and keeps my main machine safe from whatever these autonomous agents are doing. if you stick with me i will walk you through the exact architecture of a professional trading system that handles the heavy lifting without you needing to drop a single rack on hardware most people are scared of running these bots on their main computer because they don't want an agent messing with their personal files or browser sessions. instead of buying a second mac mini for six hundred dollars you can just go to the top left of your screen and create a brand new user profile. this acts like a completely isolated sandbox where you can install all your trading tools and agents without them ever seeing your main data. it is essentially like getting a free computer for the price of five minutes of clicking around your settings but what if you aren't on a mac or you need to access your system while you are traveling without carrying three laptops in your backpack. this is where the first loop of professional automation starts to close because i use something called chrome remote desktop to bridge the gap. this allows me to leave a dedicated machine running in a safe place while i access the full desktop environment from a tablet or a cheap laptop anywhere in the world. it solves the mobility issue but it still doesn't solve the problem of those massive ten thousand dollar price tags for high end mac pros if you are a pc user or just someone who doesn't want to own physical hardware yet you should look into a windows vps through a provider like contabo. most developers will tell you to use a linux terminal but if you aren't a coder yet you need a visual interface you can actually see. getting a windows server allows you to log in and see a desktop just like your home computer for about fifteen dollars a month. i usually recommend at least twelve gigabytes of ram to keep things from getting janky when you are running multiple browser windows and agents at once now you might be thinking that the whole point of the big hardware was to run local models like kimi or glm to save on api costs. i spent years thinking i had to own the machines myself and i even spent hundreds of thousands on developers before i realized i could just do this myself. the secret to running those massive open source models without the ten thousand dollar investment is renting gpu power by the hour. sites like lambda labs let you spin up a monster machine that can run any model in existence for just a couple dollars an hour this is the ultimate pivot because it allows you to test if your strategy actually prints money before you commit to the hardware. you can turn the server on when you are iterating and turn it off the second you are done which keeps your overhead near zero. if you haven't proven that your bot can pay for itself yet then buying a mac studio is just an expensive hobby rather than a business move. there is a much bigger loophole involving the anthropic subscriptions that most people are completely overlooking right now right now i am using a specific plan with claude code that costs about two hundred dollars a month but it lets me run open claw all day without hitting api limits. if i were paying for those same tokens through the standard api i would probably be spending hundreds of dollars every single day. it is a massive cost savings that allows you to iterate and fail until you find a winning strategy without draining your bank account. even if they eventually close this loophole or snitch on the usage patterns it serves as the perfect training ground for a data dog the goal is to find a system that works with a smaller or cheaper model like haiku before you ever try to scale up to the heavy weights. if you can make a strategy profitable using a less intelligent and cheaper model then you know you have found real alpha. once you have that foundation you can decide if it finally makes sense to build your own custom pc rig which will always be half the price of an apple machine. i am an apple guy so i usually pay the tax anyway but i only do it once the system is already generating enough to cover the cost ten times over i believe that code is the great equalizer because it took me from losing money and getting liquidated to having fully automated systems doing the work for me. i had to learn to live with the iterations and the failures on youtube to get to this point of clarity. the universe tends to get out of your way once you make a non negotiable contract with yourself to see the process through to the end. you don't need the flashy hardware or the most expensive setup to start winning in this game stay focused on the logic and the data rather than the hype and the fomo that everyone else is falling for. if you can master the bridge between renting power and owning your logic you will be ahead of ninety nine percent of the people in this space. the path to a fully automated life isn't paved with expensive gadgets but with the discipline to iterate until the system finally prints

Moon Dev

17,382 Aufrufe • vor 6 Monaten

The 118,000% Alpha: Building a High-Frequency AI Trading Floor with Claude Code if you think claude code is just for writing simple scripts then you are already losing to the bots that are hunting your liquidity right now. most traders are still clicking buttons while i have an ai employee running backtests on twenty eight different data sources simultaneously. i am going to show you how a strategy that returned over four hundred thousand percent was built in minutes using a secret sub agent workflow most people treat ai like a chatbot but i treat it like a quant architect that builds systems better than the devs i used to pay hundreds of thousands of dollars. there is one specific indicator combo that actually survived a stress test across tesla and bitcoin at the same time and i will reveal that logic further down. we have to talk about why your current backtests are probably lying to you before we get into the code my name is moon dev and i truly believe that code is the great equalizer in this world. for years i was the guy getting liquidated and overtrading because i was letting my emotions drive the wheel. i spent an insane amount of money hiring developers to build apps for me because i thought i was not smart enough to code myself. through that pain i realized that if i wanted to win i had to automate everything and learn to do it live on youtube for the world to see the secret to trading with claude code is not asking it for a strategy but using it to build a backtest architect. this sub agent acts as a consistent employee that understands how to test against massive datasets without getting tired. it allows me to iterate through hundreds of ideas in the time it used to take me to write one single line of python. this is how i found the strategy that hit a one hundred and eighteen thousand percent return on a single run there is a massive trap that almost every beginner falls into when they start using ai for trading. they find a strategy that looks amazing on one chart and they think they found the holy grail of wealth. that is usually just a lucky fluke or a curve fit mess that will blow up your account next week. the real secret to staying alive is the multi data testing system that claude built for me today we test every single idea against bitcoin and ethereum and solana but we also throw in apple and tesla and nvidia. if a strategy only works on crypto it is probably just riding a trend that is already over. i want to find the logic that is robust enough to handle the volatility of a meme coin and the steady grind of a blue chip stock. this is the only way to prove that the code actually has an edge in the market before we dive into the kalman filter logic i have to tell you about the dca bot i have running on solana right now. it is called housecoin and the thesis behind it is either going to make me a genius or leave me with nothing. it is buying every time we are under the five minute sma and i have been checking the transactions live. i will explain the risk management behind this "all or nothing" play shortly but first we need to look at the winners the winner of today was the acceleration bands combined with a kalman filter. the kalman filter is incredible because it helps remove the noise and lag that you get with standard moving averages. most indicators repaint which means they change their past values to look better after the price has already moved. the way i have implemented this filter prevents that trap so the results you see in the backtest are actually tradable when we ran the acceleration bands across the hourly nvidia chart it returned over two hundred percent while the underlying asset was down forty percent. that is a massive alpha gap that most people will never see because they are stuck using standard rsi settings. i have found that adding a volatility breakout with atr to this setup helps catch the moves that the banks are trying to hide. the math behind the atr breakout is what kept me from getting chopped up in the sideway ranges you might be wondering why i am giving all this code away for free on github instead of keeping it in a vault. it is because i remember what it felt like to be on the other side of the trade losing money every single day. i want to build a community of quads that are all researching and backtesting together. the goal is to chase the legacy of jim simons who proved that math and code are the only things that matter in the long run the rbi system is the framework that i follow every single day without exception. it stands for research and backtest and implement. most traders skip the middle step because they are too impatient to see the results. they hear a rumor on twitter and they buy the top only to get liquidated when the whales decide to take profits. if you do not backtest your ideas then you are just gambling with your life savings i am spending around forty to one hundred dollars a day on claude opus tokens because it is a drop in the bucket compared to what a developer would charge. this ai does not need a lunch break and it does not get bored when i ask it to create sixty different variations of a strategy. we just created five different parabolic sar versions today and found that the long only setup was the only one worth keeping. it returned sixteen thousand percent on the soul data set because it stayed out of the short side traps shorting crypto is extremely dangerous and usually not worth the stress for most people. i have found that focusing on long only strategies with a tight trail stop is the most consistent way to grow an account. the sub agent architect allowed me to verify this across twenty five data sources in less than ten minutes. this speed of iteration is the only way to stay ahead of the curve in an industry that changes every few seconds the dca bot i mentioned earlier is still grinding away and buying the dips as we speak. i have built it to be a long term play where i am slowly accumulating a position in housecoin based on smas. if the price stays under the moving average the bot keeps buying and if it goes above then it sits on its hands. it is a simple logic but it removes the human desire to "buy the moon" when the price is already overextended i found that the camarilla pivot indicator was mostly trash today when we ran the numbers. even though it looks fancy on a chart the backtest showed negative expectancy across almost every asset we tried. this is why backtesting is so important because it kills the "indicator porn" that influencers use to sell you courses. i would much rather know that a strategy is a loser now than find out after i put real money on the line the true secret to using claude code is to treat it like a partner and not just a tool. i ask it to find anomalies and then i ask it to prove me wrong by testing it against the worst market conditions in history. if a strategy can survive the 2022 crypto crash and the 2020 stock market dip then i might consider it for a live run. we are stepping on the gas every single day because there are always new anomalies popping up if you are fast enough to find them i have uploaded over twenty five new backtests to the github today for everyone to use. code is the equalizer because it does not care about your background or how much money you started with. if you can write the logic and prove the edge then the market has to pay you. i am going to keep building in public and showing the wins and the losses because that is the only way to stay real in this space the final piece of the puzzle is the mindset of iteration over perfection. i would rather run a hundred messy backtests today than spend a month trying to write one perfect script. the ai allows me to fail fast so that i can find the winners that actually move the needle. my housecoin dca bot is a testament to that philosophy of just building and letting the systems do the heavy lifting for me if you are still trading by hand you are playing a game that is rigged against you by the biggest firms in the world. they have the best servers and the best data and the best phds but they do not have your specific creativity. when you combine your ideas with the power of claude code you are creating a custom weapon that they have never seen before. i will see you in the code and we will keep chasing the goat until we find that ultimate edge
1:55:47

The 118,000% Alpha: Building a High-Frequency AI Trading Floor with Claude Code if you think claude code is just for writing simple scripts then you are already losing to the bots that are hunting your liquidity right now. most traders are still clicking buttons while i have an ai employee running backtests on twenty eight different data sources simultaneously. i am going to show you how a strategy that returned over four hundred thousand percent was built in minutes using a secret sub agent workflow most people treat ai like a chatbot but i treat it like a quant architect that builds systems better than the devs i used to pay hundreds of thousands of dollars. there is one specific indicator combo that actually survived a stress test across tesla and bitcoin at the same time and i will reveal that logic further down. we have to talk about why your current backtests are probably lying to you before we get into the code my name is moon dev and i truly believe that code is the great equalizer in this world. for years i was the guy getting liquidated and overtrading because i was letting my emotions drive the wheel. i spent an insane amount of money hiring developers to build apps for me because i thought i was not smart enough to code myself. through that pain i realized that if i wanted to win i had to automate everything and learn to do it live on youtube for the world to see the secret to trading with claude code is not asking it for a strategy but using it to build a backtest architect. this sub agent acts as a consistent employee that understands how to test against massive datasets without getting tired. it allows me to iterate through hundreds of ideas in the time it used to take me to write one single line of python. this is how i found the strategy that hit a one hundred and eighteen thousand percent return on a single run there is a massive trap that almost every beginner falls into when they start using ai for trading. they find a strategy that looks amazing on one chart and they think they found the holy grail of wealth. that is usually just a lucky fluke or a curve fit mess that will blow up your account next week. the real secret to staying alive is the multi data testing system that claude built for me today we test every single idea against bitcoin and ethereum and solana but we also throw in apple and tesla and nvidia. if a strategy only works on crypto it is probably just riding a trend that is already over. i want to find the logic that is robust enough to handle the volatility of a meme coin and the steady grind of a blue chip stock. this is the only way to prove that the code actually has an edge in the market before we dive into the kalman filter logic i have to tell you about the dca bot i have running on solana right now. it is called housecoin and the thesis behind it is either going to make me a genius or leave me with nothing. it is buying every time we are under the five minute sma and i have been checking the transactions live. i will explain the risk management behind this "all or nothing" play shortly but first we need to look at the winners the winner of today was the acceleration bands combined with a kalman filter. the kalman filter is incredible because it helps remove the noise and lag that you get with standard moving averages. most indicators repaint which means they change their past values to look better after the price has already moved. the way i have implemented this filter prevents that trap so the results you see in the backtest are actually tradable when we ran the acceleration bands across the hourly nvidia chart it returned over two hundred percent while the underlying asset was down forty percent. that is a massive alpha gap that most people will never see because they are stuck using standard rsi settings. i have found that adding a volatility breakout with atr to this setup helps catch the moves that the banks are trying to hide. the math behind the atr breakout is what kept me from getting chopped up in the sideway ranges you might be wondering why i am giving all this code away for free on github instead of keeping it in a vault. it is because i remember what it felt like to be on the other side of the trade losing money every single day. i want to build a community of quads that are all researching and backtesting together. the goal is to chase the legacy of jim simons who proved that math and code are the only things that matter in the long run the rbi system is the framework that i follow every single day without exception. it stands for research and backtest and implement. most traders skip the middle step because they are too impatient to see the results. they hear a rumor on twitter and they buy the top only to get liquidated when the whales decide to take profits. if you do not backtest your ideas then you are just gambling with your life savings i am spending around forty to one hundred dollars a day on claude opus tokens because it is a drop in the bucket compared to what a developer would charge. this ai does not need a lunch break and it does not get bored when i ask it to create sixty different variations of a strategy. we just created five different parabolic sar versions today and found that the long only setup was the only one worth keeping. it returned sixteen thousand percent on the soul data set because it stayed out of the short side traps shorting crypto is extremely dangerous and usually not worth the stress for most people. i have found that focusing on long only strategies with a tight trail stop is the most consistent way to grow an account. the sub agent architect allowed me to verify this across twenty five data sources in less than ten minutes. this speed of iteration is the only way to stay ahead of the curve in an industry that changes every few seconds the dca bot i mentioned earlier is still grinding away and buying the dips as we speak. i have built it to be a long term play where i am slowly accumulating a position in housecoin based on smas. if the price stays under the moving average the bot keeps buying and if it goes above then it sits on its hands. it is a simple logic but it removes the human desire to "buy the moon" when the price is already overextended i found that the camarilla pivot indicator was mostly trash today when we ran the numbers. even though it looks fancy on a chart the backtest showed negative expectancy across almost every asset we tried. this is why backtesting is so important because it kills the "indicator porn" that influencers use to sell you courses. i would much rather know that a strategy is a loser now than find out after i put real money on the line the true secret to using claude code is to treat it like a partner and not just a tool. i ask it to find anomalies and then i ask it to prove me wrong by testing it against the worst market conditions in history. if a strategy can survive the 2022 crypto crash and the 2020 stock market dip then i might consider it for a live run. we are stepping on the gas every single day because there are always new anomalies popping up if you are fast enough to find them i have uploaded over twenty five new backtests to the github today for everyone to use. code is the equalizer because it does not care about your background or how much money you started with. if you can write the logic and prove the edge then the market has to pay you. i am going to keep building in public and showing the wins and the losses because that is the only way to stay real in this space the final piece of the puzzle is the mindset of iteration over perfection. i would rather run a hundred messy backtests today than spend a month trying to write one perfect script. the ai allows me to fail fast so that i can find the winners that actually move the needle. my housecoin dca bot is a testament to that philosophy of just building and letting the systems do the heavy lifting for me if you are still trading by hand you are playing a game that is rigged against you by the biggest firms in the world. they have the best servers and the best data and the best phds but they do not have your specific creativity. when you combine your ideas with the power of claude code you are creating a custom weapon that they have never seen before. i will see you in the code and we will keep chasing the goat until we find that ultimate edge

Moon Dev

18,650 Aufrufe • vor 6 Monaten

🚨 DOT-COM 2.0 IS ALREADY HERE A $2 trillion AI economy built on the same dollars being passed in a circle I'm not being dramatic. The accounting trick is right there in the filings The scariest part? It's all 100% legal Here's how it works: A tech giant gives an AI startup billions in "investment." The contract forces that startup to spend the exact same money renting servers from… the tech giant. The tech giant then books that server usage as brand new "cloud revenue." Translation: they're paying themselves with their own money and calling it a sale. Look at Microsoft and OpenAI. Microsoft "invested" $13 billion in OpenAI. Most of it never left Microsoft - it was cloud credits that could only be spent on Microsoft servers. OpenAI used those credits to train its models. Microsoft turned around and recorded that exact spend as new cloud revenue That's why OpenAI's annual cloud bill is now $60 BILLION For a company doing only $25 BILLION in actual revenue It's not a customer. It's a recycled funding loop Anthropic runs the exact same script: $2.66 billion paid to AWS in 9 months - basically 100% of everything Anthropic earned. And it gets worse Every time these AI startups raise at a higher valuation, the tech giants mark up their equity and book the paper gain as PROFIT. Q1 2026: ➮ Alphabet reported $62.6B in profit. $28.7B of it (nearly half) was just a paper markup on Anthropic. ➮ Amazon reported $30.3B in profit. $16.8B of it was the same Anthropic paper gain. While Amazon was reporting record profits, its actual free cash flow collapsed 95% to just $1.2 billion Because they had to spend $44.2 BILLION in REAL money building data centers Real cash going out. Paper "profits" coming in Now here's where it gets dangerous: ➮ Microsoft has 49% of its $627 billion future backlog tied to OpenAI alone ➮ Oracle has 54% of its $553 billion pipeline depending on OpenAI alone Trillions of dollars of "demand" resting on one or two unprofitable startups If this all sounds familiar, it should This is 2001 all over again Back then, Global Crossing and Qwest swapped identical fiber-optic capacity with each other just to book fake sales Qwest had to erase $1.4 billion in fake income Global Crossing went bankrupt The only difference between then and now? The dot-com swaps were illegal Today's AI loop is fully legal under current accounting rules That's not a comfort. That's a warning Legal doesn't mean safe. It just means nobody can stop it before it blows up And here's the part most people don't realize: Every 401k, every index fund, every retirement account in America is being forced to buy more of these tech stocks every month. The loop inflates the stock prices The funds chase the prices The chase inflates them further Until the day the music stops and there's no real cash underneath. Don't worry though - my system flags the exact moment the market shifts from caution to DANGER. You'll be warned before it hits, like always. All you need to NOT miss my next call is to keep NOTIFS ON
0:59

🚨 DOT-COM 2.0 IS ALREADY HERE A $2 trillion AI economy built on the same dollars being passed in a circle I'm not being dramatic. The accounting trick is right there in the filings The scariest part? It's all 100% legal Here's how it works: A tech giant gives an AI startup billions in "investment." The contract forces that startup to spend the exact same money renting servers from… the tech giant. The tech giant then books that server usage as brand new "cloud revenue." Translation: they're paying themselves with their own money and calling it a sale. Look at Microsoft and OpenAI. Microsoft "invested" $13 billion in OpenAI. Most of it never left Microsoft - it was cloud credits that could only be spent on Microsoft servers. OpenAI used those credits to train its models. Microsoft turned around and recorded that exact spend as new cloud revenue That's why OpenAI's annual cloud bill is now $60 BILLION For a company doing only $25 BILLION in actual revenue It's not a customer. It's a recycled funding loop Anthropic runs the exact same script: $2.66 billion paid to AWS in 9 months - basically 100% of everything Anthropic earned. And it gets worse Every time these AI startups raise at a higher valuation, the tech giants mark up their equity and book the paper gain as PROFIT. Q1 2026: ➮ Alphabet reported $62.6B in profit. $28.7B of it (nearly half) was just a paper markup on Anthropic. ➮ Amazon reported $30.3B in profit. $16.8B of it was the same Anthropic paper gain. While Amazon was reporting record profits, its actual free cash flow collapsed 95% to just $1.2 billion Because they had to spend $44.2 BILLION in REAL money building data centers Real cash going out. Paper "profits" coming in Now here's where it gets dangerous: ➮ Microsoft has 49% of its $627 billion future backlog tied to OpenAI alone ➮ Oracle has 54% of its $553 billion pipeline depending on OpenAI alone Trillions of dollars of "demand" resting on one or two unprofitable startups If this all sounds familiar, it should This is 2001 all over again Back then, Global Crossing and Qwest swapped identical fiber-optic capacity with each other just to book fake sales Qwest had to erase $1.4 billion in fake income Global Crossing went bankrupt The only difference between then and now? The dot-com swaps were illegal Today's AI loop is fully legal under current accounting rules That's not a comfort. That's a warning Legal doesn't mean safe. It just means nobody can stop it before it blows up And here's the part most people don't realize: Every 401k, every index fund, every retirement account in America is being forced to buy more of these tech stocks every month. The loop inflates the stock prices The funds chase the prices The chase inflates them further Until the day the music stops and there's no real cash underneath. Don't worry though - my system flags the exact moment the market shifts from caution to DANGER. You'll be warned before it hits, like always. All you need to NOT miss my next call is to keep NOTIFS ON

Reflection🪩

3,868,930 Aufrufe • vor 2 Monaten

Here's a devlog made by an anonymous Chinese fan replicating the surprisingly brand new technique that I developed for detecting asteroids which wound up being so powerful that it can easily track Stealth Fighters from over 100km away even when it’s only using three $30 webcams as sensors meaning it easily outperforms all modern stealth tracking techniques in precision, range and cost. And while this demo is using optical light, this same technique which I call pixel motion to voxel projection, can be used interchangeably with thermal infrared cameras to work at night and also majorly boosts the effectiveness of radar allowing you to track fighters much more effectively through clouds and over the horizon. This technique will also always eventually give the exact location of the target even if the image is blurry as those blurs will always average out from the different perspectives into revealing the precise location of the target in the voxel grid. There is definitely a Mandela effect with this technique as it feels as though it should already exist, especially because at first as it sounds like it is performing triangulation (which has existed for years and is what we do for mocap and tennis ball tracking). But triangulation is entirely separate to this as triangulations only works if you have already identified where the ball is in a 2D image because you’re able to rely on being able to use at least 2 separate high quality cameras which are much closer to the ball making the ball’s apparent size much much bigger and therefore gives you hundreds of pixels to work with which makes it much easier to use object recognition techniques to recognize where it is in the image aka in 2D and then you’re just using the other cameras view to project out lines which intersect in 3D to find out where the ball is in 3D. The major difference is that pixel motion to voxel projection allows you to find where the object is in 3D without having already found it in 2D which is an unbelievable difference as it allows you to use much lower quality cameras together to accumulate data together into 3D space. If this seem like it doesn’t mean much then what it actually means is that you don’t understand what I’m saying as what I’m saying means a LOT in practical terms as it means you go from having to use an imaging system that has to be able to image the object to the point that it is over a hundred total pixels in surface area to have enough data to recognize it to instead be able to use something that is only images the object to be 1 pixel in surface area and only changes the brightness value by 1 value every now and then. I’d recommend an amazing video by DST studios called “Lowlight cameras can’t defeat stealth” if you want a great video which goes over the difficulty of even using telescopes to recognize stealth fighters and why this is so impressive compared to other techniques and ironically it is what inspired me to realize the asteroid tracker I was working on actually could do this. Which brings me to the point that if this wasn’t a new technique then not only would there be at least one example of an asteroid survey that points distant telescopes at the same place at the same time in order to be able to add the light together to detect asteroids which as I was shocked to learn isn’t a thing despite the fact that it would make detecting asteroids trivial by comparison to modern 2D imaging while also having no impact on the normal scientific operations of those surveys other than small changes to scheduling. But there would also be an example of a drone tracker that uses this instead of using the aforementioned high quality zoomable telescope which has to be able to zoom in close enough to be able to recognize a drone. If you want to tell me that this is something that already exists give me an exact example of a product that uses it, not the general outline of a concept that you think it is, the actual product and then also tell me the asteroid survey that uses distant telescopes that point at the exact same place at the exact same time because I can guarantee that if you google what you think uses this you won’t even find the steps of subtracting the images from each other to get motion and will definitely not get the added step of projecting that motion into a voxel grid (It would blow your mind if you found out how Xbox kinect cameras work.) Also I want to make it clear, I’m not saying you should just use web cams to do this, I’m just using them as an example to show you the power of this in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar. Pretty much all of the problems you could think of for this are incredibly easy to overcome if you apply even a small amount of brainpower into fixing the problem. And yes, this gives you the exact location down to the meter of whatever you are tracking even if the image is blurry as those blurs will always average out to the exact location down to the meter in the voxel grid. Which is what makes this technique so powerful since the cost of adding each camera to The network grows linearly while the rate at which each camera gives more information grows exponentially due to the increasing unlikeliness of all of them having more movement in the same place. And given the size of the cameras it really wouldn’t be that hard to hide and network these cameras together in other countries and on sea buoys to know where planes are everywhere in the world. Which brings me to the point that I personally really don’t care about the military uses of this technology, if all it could do is precisely track stealth fighters then I wouldn’t have cared enough to work on it, I could have used any of the many other life saving techniques as the subject of the video, stealth fighters just sounds the most clickable and the scale of the problem is more intuitive to most people and if I did use any of those as subjects for the demo it would inevitably result in the stealth fighter technique being figured out anyway and all of the other uses are so useful that I don't think anyone would reasonably complain about the upside. The real purpose of this video is that since this is a new technique that hasn’t been used to detect stealth fighters despite the billions we have spent on that, then what else can you apply this to that could go on to improve billions of people’s lives that you or others are working on. For example this also allows you to majorly improve the effectiveness of cryo electron microscopy and CT scanners. This part also is kind of hard to explain as it also sounds like it exists but again, when you look through all of the places where you think it is being used you will find that it wasn’t. What I’m saying here isn’t that this is a Radon transform or gaussian splat or whatever, I’m saying that this is able to get new information that wasn’t being accessed before due to the added information about depth you get from the correlation of movement between each perspective which adds to the information that you already have. This allows you to directly subtract foreground and background objects as well as noise faster than you would be able to before and works better than super resolution for your images since super resolution won’t remove foreground and background objects like this does and instead just scales up target, foreground and background objects indiscriminately. And while with enough data Radon transforms or other scanning techniques would eventually get you a correct answer this will get you there a lot faster since those are mostly averaging techniques which average out noise whereas this gets you the ability to directly subtract noise. I’m not expecting you to think that this would do anything but if you try it for yourself you will find that it does majorly improve your ability to perform 3d scans. Again, cryo EM is a field where you would expect this technique to exist but when you look through all the papers on the topic there is no mention of tilting the grid slightly in order to be able to change your perspective slightly on the order of the feature size (if you tilt the grid then you only need precision on the order of an arc minute to do this) and doing multiple exposures from multiple different known tilts and then using those difference images to correlate depth from motion. In fact, in cryo EM you would normally want to do the opposite of this and have your exposures all taken from the same grid angle and just use the variations in how many of the same proteins are oriented in order to be able to scan them for a 3D model but this will generate you far more data faster. There is so much information that I can’t really explain in text so if you have any questions such as why this hasn’t been made before then they will most likely be answered in the video I originally posted which I have added to the end of the first Devlog for your convenience. And again, pretty much all of the problems with the technique can be fixed with a little bit of brainpower, in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar.
18:48

Here's a devlog made by an anonymous Chinese fan replicating the surprisingly brand new technique that I developed for detecting asteroids which wound up being so powerful that it can easily track Stealth Fighters from over 100km away even when it’s only using three $30 webcams as sensors meaning it easily outperforms all modern stealth tracking techniques in precision, range and cost. And while this demo is using optical light, this same technique which I call pixel motion to voxel projection, can be used interchangeably with thermal infrared cameras to work at night and also majorly boosts the effectiveness of radar allowing you to track fighters much more effectively through clouds and over the horizon. This technique will also always eventually give the exact location of the target even if the image is blurry as those blurs will always average out from the different perspectives into revealing the precise location of the target in the voxel grid. There is definitely a Mandela effect with this technique as it feels as though it should already exist, especially because at first as it sounds like it is performing triangulation (which has existed for years and is what we do for mocap and tennis ball tracking). But triangulation is entirely separate to this as triangulations only works if you have already identified where the ball is in a 2D image because you’re able to rely on being able to use at least 2 separate high quality cameras which are much closer to the ball making the ball’s apparent size much much bigger and therefore gives you hundreds of pixels to work with which makes it much easier to use object recognition techniques to recognize where it is in the image aka in 2D and then you’re just using the other cameras view to project out lines which intersect in 3D to find out where the ball is in 3D. The major difference is that pixel motion to voxel projection allows you to find where the object is in 3D without having already found it in 2D which is an unbelievable difference as it allows you to use much lower quality cameras together to accumulate data together into 3D space. If this seem like it doesn’t mean much then what it actually means is that you don’t understand what I’m saying as what I’m saying means a LOT in practical terms as it means you go from having to use an imaging system that has to be able to image the object to the point that it is over a hundred total pixels in surface area to have enough data to recognize it to instead be able to use something that is only images the object to be 1 pixel in surface area and only changes the brightness value by 1 value every now and then. I’d recommend an amazing video by DST studios called “Lowlight cameras can’t defeat stealth” if you want a great video which goes over the difficulty of even using telescopes to recognize stealth fighters and why this is so impressive compared to other techniques and ironically it is what inspired me to realize the asteroid tracker I was working on actually could do this. Which brings me to the point that if this wasn’t a new technique then not only would there be at least one example of an asteroid survey that points distant telescopes at the same place at the same time in order to be able to add the light together to detect asteroids which as I was shocked to learn isn’t a thing despite the fact that it would make detecting asteroids trivial by comparison to modern 2D imaging while also having no impact on the normal scientific operations of those surveys other than small changes to scheduling. But there would also be an example of a drone tracker that uses this instead of using the aforementioned high quality zoomable telescope which has to be able to zoom in close enough to be able to recognize a drone. If you want to tell me that this is something that already exists give me an exact example of a product that uses it, not the general outline of a concept that you think it is, the actual product and then also tell me the asteroid survey that uses distant telescopes that point at the exact same place at the exact same time because I can guarantee that if you google what you think uses this you won’t even find the steps of subtracting the images from each other to get motion and will definitely not get the added step of projecting that motion into a voxel grid (It would blow your mind if you found out how Xbox kinect cameras work.) Also I want to make it clear, I’m not saying you should just use web cams to do this, I’m just using them as an example to show you the power of this in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar. Pretty much all of the problems you could think of for this are incredibly easy to overcome if you apply even a small amount of brainpower into fixing the problem. And yes, this gives you the exact location down to the meter of whatever you are tracking even if the image is blurry as those blurs will always average out to the exact location down to the meter in the voxel grid. Which is what makes this technique so powerful since the cost of adding each camera to The network grows linearly while the rate at which each camera gives more information grows exponentially due to the increasing unlikeliness of all of them having more movement in the same place. And given the size of the cameras it really wouldn’t be that hard to hide and network these cameras together in other countries and on sea buoys to know where planes are everywhere in the world. Which brings me to the point that I personally really don’t care about the military uses of this technology, if all it could do is precisely track stealth fighters then I wouldn’t have cared enough to work on it, I could have used any of the many other life saving techniques as the subject of the video, stealth fighters just sounds the most clickable and the scale of the problem is more intuitive to most people and if I did use any of those as subjects for the demo it would inevitably result in the stealth fighter technique being figured out anyway and all of the other uses are so useful that I don't think anyone would reasonably complain about the upside. The real purpose of this video is that since this is a new technique that hasn’t been used to detect stealth fighters despite the billions we have spent on that, then what else can you apply this to that could go on to improve billions of people’s lives that you or others are working on. For example this also allows you to majorly improve the effectiveness of cryo electron microscopy and CT scanners. This part also is kind of hard to explain as it also sounds like it exists but again, when you look through all of the places where you think it is being used you will find that it wasn’t. What I’m saying here isn’t that this is a Radon transform or gaussian splat or whatever, I’m saying that this is able to get new information that wasn’t being accessed before due to the added information about depth you get from the correlation of movement between each perspective which adds to the information that you already have. This allows you to directly subtract foreground and background objects as well as noise faster than you would be able to before and works better than super resolution for your images since super resolution won’t remove foreground and background objects like this does and instead just scales up target, foreground and background objects indiscriminately. And while with enough data Radon transforms or other scanning techniques would eventually get you a correct answer this will get you there a lot faster since those are mostly averaging techniques which average out noise whereas this gets you the ability to directly subtract noise. I’m not expecting you to think that this would do anything but if you try it for yourself you will find that it does majorly improve your ability to perform 3d scans. Again, cryo EM is a field where you would expect this technique to exist but when you look through all the papers on the topic there is no mention of tilting the grid slightly in order to be able to change your perspective slightly on the order of the feature size (if you tilt the grid then you only need precision on the order of an arc minute to do this) and doing multiple exposures from multiple different known tilts and then using those difference images to correlate depth from motion. In fact, in cryo EM you would normally want to do the opposite of this and have your exposures all taken from the same grid angle and just use the variations in how many of the same proteins are oriented in order to be able to scan them for a 3D model but this will generate you far more data faster. There is so much information that I can’t really explain in text so if you have any questions such as why this hasn’t been made before then they will most likely be answered in the video I originally posted which I have added to the end of the first Devlog for your convenience. And again, pretty much all of the problems with the technique can be fixed with a little bit of brainpower, in reality you would probably want to use 5 high quality zoomable thermal cameras which pan across the sky in sync with each other which due to using lower frequency are much less prone to the Rayleigh scattering that scatters visible light at 150 or so km away and again, you can also use this to majorly upgrade radar.

ConsistentlyInconsistent

50,687 Aufrufe • vor 11 Monaten

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated
1:23:35

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated

Moon Dev

11,948 Aufrufe • vor 4 Monaten

I built a self-hosted Sentry clone that runs entirely on Cloudflare Workers, and I think it showcases one of the most underrated features in the Cloudflare ecosystem: Service Bindings. Let me explain why this matters. When you have multiple Cloudflare Workers (an API, a webhook handler, a cron job), they all need common things: error tracking, authentication, rate limiting, metrics. The typical solution? External HTTP calls to third-party services. That means: - 50-200ms latency per call - Egress fees - Your data leaving your infrastructure - Another vendor to manage Service bindings let Workers call each other directly inside Cloudflare's network. No HTTP. No internet. Just internal RPC with <5ms latency. With Workers Sentinel, any Worker in my account can just point Sentry-SDK into the Service binding, and have all errors flow into one centralized dashboard, stored in Durable Objects with SQLite. No external calls. No added latency. Service bindings aren't just for error tracking. You can centralize: 🔐 Authentication — One Worker that validates tokens for all your services 📊 Metrics — Centralized collection without external observability costs 🚦 Rate Limiting — Shared counters that actually work across Workers 🚩 Feature Flags — Instant propagation, no deployment needed Think of it as building your own internal microservices mesh, but at the edge, with zero network overhead. Workers Sentinel uses two Durable Objects: - AuthState (singleton) — users, sessions, projects - ProjectState (per-project) — issues, events, stats Events are fingerprinted and grouped intelligently. The dashboard is a Vue.js app served from the same Worker. I could say i built this to learn Durable Objects or that I needed error tracking for side projects, but honestly I just need a way to show my wife why I'm sending $200/month to some guy named Claudio who apparently helps me write code. The whole thing is open source. Deploy it to your Cloudflare account, point your Sentry SDKs at it, and you're done. But more importantly: take a closer look at service bindings. They're the glue that turns a collection of Workers into an actual platform. Most Cloudflare customers I talk to aren't using them, and they're missing out. To the Sentry team: I love your work. Genuinely. Sentry is battle-tested, has incredible features, and is what you should use for anything that matters. This project is a toy. A learning exercise. A weekend hack that got slightly out of hand. Please do not trust your production errors to this dummy clone. If your startup goes down at 3 AM because Workers Sentinel missed an edge case, that's on you. I warned you. Use the real thing. But if you want to learn about Durable Objects, service bindings, and how error tracking works under the hood? Clone away. Your Workers shouldn't be islands. Connect them.
1:53

I built a self-hosted Sentry clone that runs entirely on Cloudflare Workers, and I think it showcases one of the most underrated features in the Cloudflare ecosystem: Service Bindings. Let me explain why this matters. When you have multiple Cloudflare Workers (an API, a webhook handler, a cron job), they all need common things: error tracking, authentication, rate limiting, metrics. The typical solution? External HTTP calls to third-party services. That means: - 50-200ms latency per call - Egress fees - Your data leaving your infrastructure - Another vendor to manage Service bindings let Workers call each other directly inside Cloudflare's network. No HTTP. No internet. Just internal RPC with <5ms latency. With Workers Sentinel, any Worker in my account can just point Sentry-SDK into the Service binding, and have all errors flow into one centralized dashboard, stored in Durable Objects with SQLite. No external calls. No added latency. Service bindings aren't just for error tracking. You can centralize: 🔐 Authentication — One Worker that validates tokens for all your services 📊 Metrics — Centralized collection without external observability costs 🚦 Rate Limiting — Shared counters that actually work across Workers 🚩 Feature Flags — Instant propagation, no deployment needed Think of it as building your own internal microservices mesh, but at the edge, with zero network overhead. Workers Sentinel uses two Durable Objects: - AuthState (singleton) — users, sessions, projects - ProjectState (per-project) — issues, events, stats Events are fingerprinted and grouped intelligently. The dashboard is a Vue.js app served from the same Worker. I could say i built this to learn Durable Objects or that I needed error tracking for side projects, but honestly I just need a way to show my wife why I'm sending $200/month to some guy named Claudio who apparently helps me write code. The whole thing is open source. Deploy it to your Cloudflare account, point your Sentry SDKs at it, and you're done. But more importantly: take a closer look at service bindings. They're the glue that turns a collection of Workers into an actual platform. Most Cloudflare customers I talk to aren't using them, and they're missing out. To the Sentry team: I love your work. Genuinely. Sentry is battle-tested, has incredible features, and is what you should use for anything that matters. This project is a toy. A learning exercise. A weekend hack that got slightly out of hand. Please do not trust your production errors to this dummy clone. If your startup goes down at 3 AM because Workers Sentinel missed an edge case, that's on you. I warned you. Use the real thing. But if you want to learn about Durable Objects, service bindings, and how error tracking works under the hood? Clone away. Your Workers shouldn't be islands. Connect them.

Gabriel Massadas

28,840 Aufrufe • vor 7 Monaten

The 40,000% ROI "Bug": How Claude Code Cracked the TradingView Holy Grail most people think the elite traders at the top of the mountain have some secret indicator or a hidden math formula that gives them a forty thousand percent return. they assume the game is rigged against the small player and that you need a multi million dollar budget just to get a seat at the table. the truth is that the holy grail of trading is actually hidden in plain sight inside a community tab that most people scroll past every single day i spent years losing money to liquidations and over trading because i thought i had to manually predict where the price was going next. i even spent hundreds of thousands of dollars on developers to build apps for me because i was convinced that i would never be able to code the systems myself. it turns out that once you stop trying to be a genius and start using the tools that are already available you can crack the code to unlimited trading strategies the secret is not in a single indicator but in the process of research back test and implement. if you go to the community section of trading view you will find an endless stream of source code for indicators that people have built over decades. most traders just slap these on a chart and hope for the best but if you are a data dog like me you know that a chart is just a pretty picture that lies to you i believe that code is the great equalizer because it allows us to take these public ideas and turn them into fully automated systems that trade for us while we sleep. i decided to learn to code live on youtube to show everyone that you can iterate your way to success without being a math wizard or a stanford graduate. now i have fully automated systems that manage my capital instead of getting liquidated by emotional decisions in the middle of the night the biggest trap in the trading world is something called repainting and it is the reason why so many strategy back tests look like they are printing money when they are actually just a scam. repainting happens when an indicator looks at future data to tell you what happened in the past which makes every buy and sell signal look like a perfect entry at the top and bottom. if you trust a back test on a basic chart without understanding the logic underneath you are just building a house on a foundation of sand this is why i transitioned all of my serious work into python because python does not lie to you. in python you can control the data flow tick by tick and bar by bar to ensure that no future data is leaking into your strategy. i built a back test architect which is a specialized sub agent that knows exactly how to take a simple idea and test it against twenty five different data sources all at once when you run a strategy across btc eth apple google and tesla you start to see the real truth about whether a strategy has an edge or if it was just a lucky fluke on one chart. i saw one strategy this week that showed a one million percent return which sounds like a total lie but the data does not have an ego. even if a number looks insane you have to investigate it and incubate it with tiny size to see if it holds up in the live market you must treat your trading like a business where you are the manager and the code is your team of tireless employees. i have sub agents running for me right now that act as masters of specific tasks like converting pine script into python or optimizing exit logic. if you are not using these specialized ai assistants in your workflow you are essentially trying to build a skyscraper with a hand saw while everyone else is using heavy machinery most people get stuck in the beginner phase because they think they need to write every single line of code from scratch. the reality is that the best developers are just really good at importing the hard work of others and connecting it like lego blocks. i use a library called ccxt that allows my bots to communicate with every major exchange in the world with just a few lines of script which saves me months of development time the reason i show everything live is because the industry is filled with gatekeepers who want to keep the secrets of automation to themselves. they want you to stay as a manual trader who pays high fees and provides liquidity for their algorithms. once you learn to automate you are no longer a victim of the market but a participant in the architecture of the financial system if you are sitting there right now feeling defeated because you just got smoked on a trade or you missed a massive pump you have to realize that those emotions are your greatest enemy. a computer does not feel fomo and it does not get tilted after a loss; it just waits for the next signal that fits the parameters you defined. my mission is to help you get to a place where you can walk away from the screen and let the machines do the heavy lifting learning to code is actually much easier than learning a second language because the syntax is logical and the feedback is immediate. i spent ten years in tech scared to touch a keyboard for anything other than emails because i thought i was not smart enough for engineering. once i realized that code is just logic i was able to build my first profitable bot within a few months and i have never looked back the transition from a manual trader to an algorithmic expert is about building a robust framework for testing your ideas as fast as possible. you want to be able to find an indicator on trading view convert it to python and run it against years of historical data in less than five minutes. if you can do that you have a higher chance of success than ninety nine percent of the people who are just drawing lines on a screen one of the most powerful strategies i found recently combines the squeeze momentum indicator with smart money concepts. when you test these individually they might show a decent return but when you combine them and add a filter like the adx you can find setups that have a massive expectancy. the key is to look for strategies that show positive returns across multiple different asset classes and time frames simultaneously even if a strategy looks like it is printing a forty thousand percent return you must always remain skeptical and look for the catch. i always incubate my new ideas with tiny capital for at least a few weeks to see how they handle real world slippage and fees. a back test is a map of the past but the live market is a wilderness that changes every single day this is why i believe in the rbi method which stands for research back test and implement. you spend your mornings looking for new ideas your afternoons stress testing them with ai and your evenings deploying the winners to the market. it is a systematic approach to wealth that removes the need for luck or guessing what a celebrity is going to tweet next the most successful traders in history like jim simons did not sit around looking at rsi levels on a fifteen minute chart. they built systems that identified mathematical edges and then scaled those systems until they were managing billions of dollars. you do not need thirty one billion dollars to change your life but you do need the discipline to stop trading like a human and start thinking like a system i give away so much for free on youtube because i want to build a community of data dogs who are all chasing the same goal of financial freedom through automation. when we work together and share our findings we can collectively identify edges that nobody else is looking at. the world is moving towards an ai dominated economy and if you are not learning to control the machines you are going to be controlled by them the road to automation is not a straight line and you will run into bugs that make you want to throw your computer out the window. but every time you fix an error and every time you optimize a script you are getting one step closer to a life where you own your time. code really is the great equalizer and it is waiting for you to pick it up and start building your own future if you can fly then run and if you can run then walk but whatever you do you must keep moving forward in this journey. trading can be heartless but the logic of code is always fair and consistent. stop being the liquidity for someone else's bot and start building the walls that will protect your capital forever
2:02:43

The 40,000% ROI "Bug": How Claude Code Cracked the TradingView Holy Grail most people think the elite traders at the top of the mountain have some secret indicator or a hidden math formula that gives them a forty thousand percent return. they assume the game is rigged against the small player and that you need a multi million dollar budget just to get a seat at the table. the truth is that the holy grail of trading is actually hidden in plain sight inside a community tab that most people scroll past every single day i spent years losing money to liquidations and over trading because i thought i had to manually predict where the price was going next. i even spent hundreds of thousands of dollars on developers to build apps for me because i was convinced that i would never be able to code the systems myself. it turns out that once you stop trying to be a genius and start using the tools that are already available you can crack the code to unlimited trading strategies the secret is not in a single indicator but in the process of research back test and implement. if you go to the community section of trading view you will find an endless stream of source code for indicators that people have built over decades. most traders just slap these on a chart and hope for the best but if you are a data dog like me you know that a chart is just a pretty picture that lies to you i believe that code is the great equalizer because it allows us to take these public ideas and turn them into fully automated systems that trade for us while we sleep. i decided to learn to code live on youtube to show everyone that you can iterate your way to success without being a math wizard or a stanford graduate. now i have fully automated systems that manage my capital instead of getting liquidated by emotional decisions in the middle of the night the biggest trap in the trading world is something called repainting and it is the reason why so many strategy back tests look like they are printing money when they are actually just a scam. repainting happens when an indicator looks at future data to tell you what happened in the past which makes every buy and sell signal look like a perfect entry at the top and bottom. if you trust a back test on a basic chart without understanding the logic underneath you are just building a house on a foundation of sand this is why i transitioned all of my serious work into python because python does not lie to you. in python you can control the data flow tick by tick and bar by bar to ensure that no future data is leaking into your strategy. i built a back test architect which is a specialized sub agent that knows exactly how to take a simple idea and test it against twenty five different data sources all at once when you run a strategy across btc eth apple google and tesla you start to see the real truth about whether a strategy has an edge or if it was just a lucky fluke on one chart. i saw one strategy this week that showed a one million percent return which sounds like a total lie but the data does not have an ego. even if a number looks insane you have to investigate it and incubate it with tiny size to see if it holds up in the live market you must treat your trading like a business where you are the manager and the code is your team of tireless employees. i have sub agents running for me right now that act as masters of specific tasks like converting pine script into python or optimizing exit logic. if you are not using these specialized ai assistants in your workflow you are essentially trying to build a skyscraper with a hand saw while everyone else is using heavy machinery most people get stuck in the beginner phase because they think they need to write every single line of code from scratch. the reality is that the best developers are just really good at importing the hard work of others and connecting it like lego blocks. i use a library called ccxt that allows my bots to communicate with every major exchange in the world with just a few lines of script which saves me months of development time the reason i show everything live is because the industry is filled with gatekeepers who want to keep the secrets of automation to themselves. they want you to stay as a manual trader who pays high fees and provides liquidity for their algorithms. once you learn to automate you are no longer a victim of the market but a participant in the architecture of the financial system if you are sitting there right now feeling defeated because you just got smoked on a trade or you missed a massive pump you have to realize that those emotions are your greatest enemy. a computer does not feel fomo and it does not get tilted after a loss; it just waits for the next signal that fits the parameters you defined. my mission is to help you get to a place where you can walk away from the screen and let the machines do the heavy lifting learning to code is actually much easier than learning a second language because the syntax is logical and the feedback is immediate. i spent ten years in tech scared to touch a keyboard for anything other than emails because i thought i was not smart enough for engineering. once i realized that code is just logic i was able to build my first profitable bot within a few months and i have never looked back the transition from a manual trader to an algorithmic expert is about building a robust framework for testing your ideas as fast as possible. you want to be able to find an indicator on trading view convert it to python and run it against years of historical data in less than five minutes. if you can do that you have a higher chance of success than ninety nine percent of the people who are just drawing lines on a screen one of the most powerful strategies i found recently combines the squeeze momentum indicator with smart money concepts. when you test these individually they might show a decent return but when you combine them and add a filter like the adx you can find setups that have a massive expectancy. the key is to look for strategies that show positive returns across multiple different asset classes and time frames simultaneously even if a strategy looks like it is printing a forty thousand percent return you must always remain skeptical and look for the catch. i always incubate my new ideas with tiny capital for at least a few weeks to see how they handle real world slippage and fees. a back test is a map of the past but the live market is a wilderness that changes every single day this is why i believe in the rbi method which stands for research back test and implement. you spend your mornings looking for new ideas your afternoons stress testing them with ai and your evenings deploying the winners to the market. it is a systematic approach to wealth that removes the need for luck or guessing what a celebrity is going to tweet next the most successful traders in history like jim simons did not sit around looking at rsi levels on a fifteen minute chart. they built systems that identified mathematical edges and then scaled those systems until they were managing billions of dollars. you do not need thirty one billion dollars to change your life but you do need the discipline to stop trading like a human and start thinking like a system i give away so much for free on youtube because i want to build a community of data dogs who are all chasing the same goal of financial freedom through automation. when we work together and share our findings we can collectively identify edges that nobody else is looking at. the world is moving towards an ai dominated economy and if you are not learning to control the machines you are going to be controlled by them the road to automation is not a straight line and you will run into bugs that make you want to throw your computer out the window. but every time you fix an error and every time you optimize a script you are getting one step closer to a life where you own your time. code really is the great equalizer and it is waiting for you to pick it up and start building your own future if you can fly then run and if you can run then walk but whatever you do you must keep moving forward in this journey. trading can be heartless but the logic of code is always fair and consistent. stop being the liquidity for someone else's bot and start building the walls that will protect your capital forever

Moon Dev

245,471 Aufrufe • vor 6 Monaten

My last post about starting a stump removal business went viral, and my DMs filled up with the same question: how do I actually get started in this business? This is a great blue collar hedge against AI if you are worried about losing your white collar job in tech or otherwise. I've made $12,000 in the first 3 months and here's everything I have learned in that time: The machine is the big check. Everything else is small. I bought a Bandit SG-40 tracked stump grinder for $33k and financed it at about $1k/month. The catch is the interest, roughly $100/month at a high rate, so I'm just paying it off next month to make the interest go away. I also have a $1M general liability policy that costs about $100 per month. Plus the finance company made me get insurance on the machine for about $100 per month. You need a way to haul it. That's a trailer, not a new truck. I got a Big Tex trailer for $4,000. I already had a 4Runner, so I didn't need a truck to start. I'm buying an F-350 diesel with the 7.3L for $6k, but only because a close friend is selling it to me and that's an insane deal. Do not go buy a $60k truck to start a stump business. Haul it with something cheap if you have to buy a truck just to get things started. Pricing: $5–$8 per inch, and you feel it out. I charge $5 to $8 per diameter inch and I read each job. A stump sitting high off the ground or one they want ground deep costs more. A flush little stump in soft dirt costs less. Measure the diameter, pick your per-inch number based on difficulty. And set a minimum. Mine is $200 for me to even show up. Below that it's not worth the drive and setup. Referrals from tree services are the whole game. Tree companies cut trees down. They usually don't grind the stump. That leftover stump is your job, and they're standing right next to it. Go build relationships with every tree service in your area. When they hand you their stumps, you have a pipeline you didn't have to advertise for. But try every channel, because they all work. I've landed a paying job from every single marketing channel I've tried so far. Not one dud yet: Flyers on community boards Business cards I hand out locally at the cafe and the dog park Posts in the local Facebook groups Nextdoor Yelp Google Business Profile Corrugated cardboard road signs None of it is fancy. It's just showing up where people already look when they've got a stump in the yard. The next one I'm testing: post office mailers. You make a flyer, pick a route, and the post office lets you see the demographics of that route, age, household income, how many people live there. Then it's about 27 cents to mail each one. You aim it at neighborhoods that own homes with yards. I'll report back on how it does. Support local, and local supports you. Use the local businesses. Buy from them, show up, be a regular. They turn around and send business your way. A small town runs on who knows you, and stump removal is a local business. Yes, it's a one-man job. Yesterday I ran two jobs, made $300 and $375. From leaving my house to pulling back in was about 4 hours, and I burned maybe $20 in fuel between my car and the machine. That's a good day when you've got two small ones. Three months in I've made $12,000, averaging about $4k/month. I expect that to climb as more people in the area know my name. The math is simple: low overhead, cash jobs, work that has to be done in the real world. Bonus: this is a business AI can't take from you. I spent 10 years in an office. With everything up in the air around AI and jobs, there's something I like about owning a business where the work physically has to happen. A stump doesn't grind itself. You show up, it's there, you leave, it's gone. And after a decade at a desk, I forgot how good it feels to see exactly what you accomplished at the end of the day. I've shared a vid of a job I did yesterday 👇
0:46

My last post about starting a stump removal business went viral, and my DMs filled up with the same question: how do I actually get started in this business? This is a great blue collar hedge against AI if you are worried about losing your white collar job in tech or otherwise. I've made $12,000 in the first 3 months and here's everything I have learned in that time: The machine is the big check. Everything else is small. I bought a Bandit SG-40 tracked stump grinder for $33k and financed it at about $1k/month. The catch is the interest, roughly $100/month at a high rate, so I'm just paying it off next month to make the interest go away. I also have a $1M general liability policy that costs about $100 per month. Plus the finance company made me get insurance on the machine for about $100 per month. You need a way to haul it. That's a trailer, not a new truck. I got a Big Tex trailer for $4,000. I already had a 4Runner, so I didn't need a truck to start. I'm buying an F-350 diesel with the 7.3L for $6k, but only because a close friend is selling it to me and that's an insane deal. Do not go buy a $60k truck to start a stump business. Haul it with something cheap if you have to buy a truck just to get things started. Pricing: $5–$8 per inch, and you feel it out. I charge $5 to $8 per diameter inch and I read each job. A stump sitting high off the ground or one they want ground deep costs more. A flush little stump in soft dirt costs less. Measure the diameter, pick your per-inch number based on difficulty. And set a minimum. Mine is $200 for me to even show up. Below that it's not worth the drive and setup. Referrals from tree services are the whole game. Tree companies cut trees down. They usually don't grind the stump. That leftover stump is your job, and they're standing right next to it. Go build relationships with every tree service in your area. When they hand you their stumps, you have a pipeline you didn't have to advertise for. But try every channel, because they all work. I've landed a paying job from every single marketing channel I've tried so far. Not one dud yet: Flyers on community boards Business cards I hand out locally at the cafe and the dog park Posts in the local Facebook groups Nextdoor Yelp Google Business Profile Corrugated cardboard road signs None of it is fancy. It's just showing up where people already look when they've got a stump in the yard. The next one I'm testing: post office mailers. You make a flyer, pick a route, and the post office lets you see the demographics of that route, age, household income, how many people live there. Then it's about 27 cents to mail each one. You aim it at neighborhoods that own homes with yards. I'll report back on how it does. Support local, and local supports you. Use the local businesses. Buy from them, show up, be a regular. They turn around and send business your way. A small town runs on who knows you, and stump removal is a local business. Yes, it's a one-man job. Yesterday I ran two jobs, made $300 and $375. From leaving my house to pulling back in was about 4 hours, and I burned maybe $20 in fuel between my car and the machine. That's a good day when you've got two small ones. Three months in I've made $12,000, averaging about $4k/month. I expect that to climb as more people in the area know my name. The math is simple: low overhead, cash jobs, work that has to be done in the real world. Bonus: this is a business AI can't take from you. I spent 10 years in an office. With everything up in the air around AI and jobs, there's something I like about owning a business where the work physically has to happen. A stump doesn't grind itself. You show up, it's there, you leave, it's gone. And after a decade at a desk, I forgot how good it feels to see exactly what you accomplished at the end of the day. I've shared a vid of a job I did yesterday 👇

smokey

34,218 Aufrufe • vor 7 Tagen

I Spent $100k On Developers Before Learning This: Build Your AI Bot Today the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some crazy math background to build these systems but i spent ten years in tech scared to code for that exact reason. i thought it was only for the geniuses and the nerds while i was just a guy who played video games and wanted his time back the reality is that code is the great equalizer because it doesn't care who you are or where you came from. i lost hundreds of thousands of dollars hiring developers who did shoddy work and i lost even more through liquidations and over trading because i was too emotional to follow my own rules. i knew i had to automate everything if i wanted to survive this game so i decided to learn live on youtube and iterate my way to success everyone is looking for the holy grail indicator that prints money while they sleep but they are looking in the wrong place. the real secret isn't a magical line on a chart but a process i call the rbi system which stands for research backtest and implement. most traders fail because they try to build a bot before they even know if their strategy worked in the past which is basically just gambling with extra steps you have to start with deep research into a strategy like supply and demand zones where you buy where the banks buy and sell where they sell. once you have a solid idea you must backtest it against years of data to see if it actually has an edge. if it doesn't work in the past it definitely won't work in the future but if it shows promise then you move to the implementation phase with small size there is a hidden cost to automation that can wipe out your profits before you even place a trade if you aren't careful. i found myself overusing api credits and running up a massive bill just to fetch wallet balances and token lists. if your bot is calling the exchange every five seconds just to see how much money you have you are essentially burning cash for no reason you can use ai tools like cursor to help you write the python code even if you are a total beginner. i still use ai to explain complex functions and identify where my code is being inefficient or chewing through credits. i had to refactor my entire dashboard and timer logic to only check balances every thirty minutes instead of every few seconds to save those precious credits the man who made thirty one billion dollars in the markets had one rule he never broke throughout his entire career. jim simons was the greatest algorithmic trader to ever live and he proved that systems will always beat human intuition over a long enough timeline. his secret wasn't some complex formula that no one else could understand but a commitment to a specific way of thinking simons always said you just have to make your systems better and better because that is what everyone else is trying to do. the game never really ends because the markets are always evolving and your edge will eventually decay if you don't iterate. this is why i build in public and show every step of the process because the iteration is where the actual money is made the reason you get liquidated isn't the market or the whales or some conspiracy against your small account. the real reason is the conversation you have with yourself at two in the morning when you are down on a trade and decide to move your stop loss. humans are built for survival not for trading and our emotions like fomo and fear will always sabotage our results when you automate your trading you are essentially signing a non negotiable contract with yourself that the bot will execute without question. if the plan says to sell fifty percent in an uptrend and ninety five percent in a downtrend the bot does it every single time. it doesn't feel the panic when a red candle drops or the greed when a green one spikes it just follows the code i used to spend all day staring at screens chasing bars up and down thinking that more screen time equaled more profit. i got into trading to get my time back but i ended up becoming a slave to the charts until i finally learned to code. now i have fully automated systems trading for me instead of getting liquidated because i removed the weakest link in the system which was me you don't need to spend ten years learning how to code before you can start building your own trading bots. if you spend three to six months getting the gist of python and using ai to bridge the gap you can start building immediately. start with a simple supply and demand bot that looks for major coin trends and only enters when the odds are heavily in your favor by checking the trend of bitcoin ethereum and solana simultaneously you can ensure you aren't fighting the overall market direction. i look for at least two out of those three to be trending before my bot is even allowed to look for an entry. this simple filter alone can save you from thousands of dollars in paper cuts during choppy sideways markets if you can't fly then run and if you can't run then walk but by all means you must keep moving toward automation. the process of taking an idea out of your brain and putting it into a system is the most secretive and valuable skill in the world. don't follow the pack and try to solve the same problems as everyone else but find your own edge and code it into existence the deal you make with yourself at the start of your journey is what determines if you will actually make it or not. i made a contract with myself to learn live and show everything because i believe that transparency is the only way to truly learn this craft. stick to your plan and iterate every single day because the systems you build today are the equalizers that will change your life tomorrow
50:50

I Spent $100k On Developers Before Learning This: Build Your AI Bot Today the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some crazy math background to build these systems but i spent ten years in tech scared to code for that exact reason. i thought it was only for the geniuses and the nerds while i was just a guy who played video games and wanted his time back the reality is that code is the great equalizer because it doesn't care who you are or where you came from. i lost hundreds of thousands of dollars hiring developers who did shoddy work and i lost even more through liquidations and over trading because i was too emotional to follow my own rules. i knew i had to automate everything if i wanted to survive this game so i decided to learn live on youtube and iterate my way to success everyone is looking for the holy grail indicator that prints money while they sleep but they are looking in the wrong place. the real secret isn't a magical line on a chart but a process i call the rbi system which stands for research backtest and implement. most traders fail because they try to build a bot before they even know if their strategy worked in the past which is basically just gambling with extra steps you have to start with deep research into a strategy like supply and demand zones where you buy where the banks buy and sell where they sell. once you have a solid idea you must backtest it against years of data to see if it actually has an edge. if it doesn't work in the past it definitely won't work in the future but if it shows promise then you move to the implementation phase with small size there is a hidden cost to automation that can wipe out your profits before you even place a trade if you aren't careful. i found myself overusing api credits and running up a massive bill just to fetch wallet balances and token lists. if your bot is calling the exchange every five seconds just to see how much money you have you are essentially burning cash for no reason you can use ai tools like cursor to help you write the python code even if you are a total beginner. i still use ai to explain complex functions and identify where my code is being inefficient or chewing through credits. i had to refactor my entire dashboard and timer logic to only check balances every thirty minutes instead of every few seconds to save those precious credits the man who made thirty one billion dollars in the markets had one rule he never broke throughout his entire career. jim simons was the greatest algorithmic trader to ever live and he proved that systems will always beat human intuition over a long enough timeline. his secret wasn't some complex formula that no one else could understand but a commitment to a specific way of thinking simons always said you just have to make your systems better and better because that is what everyone else is trying to do. the game never really ends because the markets are always evolving and your edge will eventually decay if you don't iterate. this is why i build in public and show every step of the process because the iteration is where the actual money is made the reason you get liquidated isn't the market or the whales or some conspiracy against your small account. the real reason is the conversation you have with yourself at two in the morning when you are down on a trade and decide to move your stop loss. humans are built for survival not for trading and our emotions like fomo and fear will always sabotage our results when you automate your trading you are essentially signing a non negotiable contract with yourself that the bot will execute without question. if the plan says to sell fifty percent in an uptrend and ninety five percent in a downtrend the bot does it every single time. it doesn't feel the panic when a red candle drops or the greed when a green one spikes it just follows the code i used to spend all day staring at screens chasing bars up and down thinking that more screen time equaled more profit. i got into trading to get my time back but i ended up becoming a slave to the charts until i finally learned to code. now i have fully automated systems trading for me instead of getting liquidated because i removed the weakest link in the system which was me you don't need to spend ten years learning how to code before you can start building your own trading bots. if you spend three to six months getting the gist of python and using ai to bridge the gap you can start building immediately. start with a simple supply and demand bot that looks for major coin trends and only enters when the odds are heavily in your favor by checking the trend of bitcoin ethereum and solana simultaneously you can ensure you aren't fighting the overall market direction. i look for at least two out of those three to be trending before my bot is even allowed to look for an entry. this simple filter alone can save you from thousands of dollars in paper cuts during choppy sideways markets if you can't fly then run and if you can't run then walk but by all means you must keep moving toward automation. the process of taking an idea out of your brain and putting it into a system is the most secretive and valuable skill in the world. don't follow the pack and try to solve the same problems as everyone else but find your own edge and code it into existence the deal you make with yourself at the start of your journey is what determines if you will actually make it or not. i made a contract with myself to learn live and show everything because i believe that transparency is the only way to truly learn this craft. stick to your plan and iterate every single day because the systems you build today are the equalizers that will change your life tomorrow

Moon Dev

11,726 Aufrufe • vor 6 Monaten