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Got rejected by Apple on the first review. I fixed everything, resubmitted, and used the time to polish the product instead of waiting. Added smooth animations, improved water logging. Meanwhile, I spun up an AI influencer farm for TikTok, first warmed-up post hit 50K views. Rejection = free time... show more

Alex Nguyen

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176,752 просмотров • 6 месяцев назад •via X (Twitter)

Наука и технологии

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I got rejected by Apple for the 3rd time. Fixed everything and resubmitted. Used the wait time to: > Add dark mode 🌙 > Create new mascot animations for dark mode > Improve food scanning speed Meanwhile, I spun up an AI influencer farm for TikTok. Another warmed-up post just crossed 70K views. Rejection = free time to build distribution. Keep going 💪 Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS (for my next app, I’ll go back to NestJS) – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)

I got rejected by Apple for the 3rd time. Fixed everything and resubmitted. Used the wait time to: > Add dark mode 🌙 > Create new mascot animations for dark mode > Improve food scanning speed Meanwhile, I spun up an AI influencer farm for TikTok. Another warmed-up post just crossed 70K views. Rejection = free time to build distribution. Keep going 💪 Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS (for my next app, I’ll go back to NestJS) – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)

Alex Nguyen

71,581 просмотров • 6 месяцев назад

It’s been 10+ days since I submitted my app to Apple Still waiting for review 😌 Lesson learned: don’t submit your app during holidays. But not a loss. While waiting, I: – Updated the paywall – Added a first-time close discount – Improved conversion rate (i hope) 📈 Marketing progress: - I’ve finished warming up 3 TikTok accounts and have started posting the first videos. Sometimes delays are just free optimization time. Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)

It’s been 10+ days since I submitted my app to Apple Still waiting for review 😌 Lesson learned: don’t submit your app during holidays. But not a loss. While waiting, I: – Updated the paywall – Added a first-time close discount – Improved conversion rate (i hope) 📈 Marketing progress: - I’ve finished warming up 3 TikTok accounts and have started posting the first videos. Sometimes delays are just free optimization time. Tech Stack: – No code mobile app builder: Rork AI – Mobile: React Native (Expo) – IDE: Cursor – Frontend: Next.js – Payment: RevenueCat – Backend: HonoJS – Database: Supabase – Infrastructure: Railway – AI API: OpenAI (dropping the tech stack here because someone always asks 😂)

Alex Nguyen

151,002 просмотров • 6 месяцев назад

Expo + OpenAI + RevenueCat = $25K MRR AI product. Most AI apps fail because: → No monetization strategy → No structured UX → No reason for users to pay → No distribution loop Just structured input → AI orchestration → media → monetization → distribution. Mosaic fixes that: → Mobile-first AI experience → Subscription-based value delivery → Audio + personalization moat → Shareable links that drive installs Here’s how Mosaic works: → Mobile app (React Native + Expo) captures structured story inputs → Backend (Node + TypeScript) orchestrates OpenAI + Gemini + TTS → Audio pipeline (ElevenLabs) narrates stories at scale → Subscription system (Revenuecat) enforces credits & usage → Share URL layer (Next.js) converts stories into viral links Built as a system, not a hackathon app. Full breakdown in the video ↓ Like + comment “MVP” + repost, and I’ll DM it to you ( must be following )

Expo + OpenAI + RevenueCat = $25K MRR AI product. Most AI apps fail because: → No monetization strategy → No structured UX → No reason for users to pay → No distribution loop Just structured input → AI orchestration → media → monetization → distribution. Mosaic fixes that: → Mobile-first AI experience → Subscription-based value delivery → Audio + personalization moat → Shareable links that drive installs Here’s how Mosaic works: → Mobile app (React Native + Expo) captures structured story inputs → Backend (Node + TypeScript) orchestrates OpenAI + Gemini + TTS → Audio pipeline (ElevenLabs) narrates stories at scale → Subscription system (Revenuecat) enforces credits & usage → Share URL layer (Next.js) converts stories into viral links Built as a system, not a hackathon app. Full breakdown in the video ↓ Like + comment “MVP” + repost, and I’ll DM it to you ( must be following )

Harshil Tomar

23,360 просмотров • 6 месяцев назад

How I target US users for my B2C apps: > Buy a used iPhone (~$120) > VPN to the US > Warm up the account 3–7 days like a normal user > Pick a TikTok niche that’s already viral + fits your product (If your app isn’t Gen Z / 16–30 friendly, TikTok may not work) > Build an AI content factory / AI influencers > Post daily > If a video stays under 0->1k views → change content fast Instead of burning $200–$2,000/week hiring UGC creators. I build an AI influencer army at almost $0 cost. Virality doesn’t always happen immediately after posting. For example, the video below was posted at the end of last December and only got ~2k views at first. Today, it just started going viral, reaching 214k+ views in a few days (and it’s still growing). Consistency > luck. Distribution > everything.

How I target US users for my B2C apps: > Buy a used iPhone (~$120) > VPN to the US > Warm up the account 3–7 days like a normal user > Pick a TikTok niche that’s already viral + fits your product (If your app isn’t Gen Z / 16–30 friendly, TikTok may not work) > Build an AI content factory / AI influencers > Post daily > If a video stays under 0->1k views → change content fast Instead of burning $200–$2,000/week hiring UGC creators. I build an AI influencer army at almost $0 cost. Virality doesn’t always happen immediately after posting. For example, the video below was posted at the end of last December and only got ~2k views at first. Today, it just started going viral, reaching 214k+ views in a few days (and it’s still growing). Consistency > luck. Distribution > everything.

Alex Nguyen

146,924 просмотров • 6 месяцев назад

Mobile App + AI Influencer = $1400 Today 2 x $7.78 monthly subs ❎No Meta Ads ❎No TikTok Ads ✅Just an organic post In this video, I show the English version of the app because the Turkish one has everything the same with the TR text overlay For the US target, I am still warming up the account Why I make quick money from Turkey but not in the US? Here is the answer👇🏻 - In the US targetted audience is doing workouts like an army. Lots of fitness trainers and all jacked - For the TR side, I target women who doesnt workout (that is goldmine💰) It work latin americas country as well, believe me 🔑 If you speak Spanish or Portuguese, easier to run social media in those countries

Mobile App + AI Influencer = $1400 Today 2 x $7.78 monthly subs ❎No Meta Ads ❎No TikTok Ads ✅Just an organic post In this video, I show the English version of the app because the Turkish one has everything the same with the TR text overlay For the US target, I am still warming up the account Why I make quick money from Turkey but not in the US? Here is the answer👇🏻 - In the US targetted audience is doing workouts like an army. Lots of fitness trainers and all jacked - For the TR side, I target women who doesnt workout (that is goldmine💰) It work latin americas country as well, believe me 🔑 If you speak Spanish or Portuguese, easier to run social media in those countries

Muhammet A. 👉🏻 Mobile Dev

17,549 просмотров • 2 месяцев назад

From a factory worker to a full-stack developer in 1.5 years of grind. I’m not saying this to flex. I’m saying this because I didn’t believe it was possible either. 1.5 years ago, I was working in a vegetables factory. 10 hours a day. Packing. Picking. Standing. Physically exhausting. Mentally draining. I had dropped out of college because of financial issues. This felt like the end of the road. A friend told me: “Try learning to code.” I saved whatever money I could. Took some help from my parents. Bought a laptop. Quit the factory job. For a while, the internet became my university. I kept remembering something Elon Musk once said: “Everything you need to learn is available on the internet for free.” I used that line like a rule. HTML, CSS, JavaScript one month. Then React. No fancy courses. Just docs, projects, and breaking things. Got my first internship. Struggled. Learned. Improved. After 4 months, I pushed harder: – Deep React (no tutorial hopping) – Backend basics – Some DSA That grind got me a full-stack role at a US-based company (onsite in Bhopal). Life tested me again when my grandfather the person I always looked up to had a heart attack. It broke me. I quit. Took time. Regrouped. Started freelancing. Got 2 to 3 projects. Kept moving forward. My journey hasn’t been clean. It’s been messy, uncertain, and uncomfortable. But here I am. 2025 was just a warm-up. 2026 is execution. If you’re starting from zero don’t underestimate what 1–2 years of focused grind can do.

From a factory worker to a full-stack developer in 1.5 years of grind. I’m not saying this to flex. I’m saying this because I didn’t believe it was possible either. 1.5 years ago, I was working in a vegetables factory. 10 hours a day. Packing. Picking. Standing. Physically exhausting. Mentally draining. I had dropped out of college because of financial issues. This felt like the end of the road. A friend told me: “Try learning to code.” I saved whatever money I could. Took some help from my parents. Bought a laptop. Quit the factory job. For a while, the internet became my university. I kept remembering something Elon Musk once said: “Everything you need to learn is available on the internet for free.” I used that line like a rule. HTML, CSS, JavaScript one month. Then React. No fancy courses. Just docs, projects, and breaking things. Got my first internship. Struggled. Learned. Improved. After 4 months, I pushed harder: – Deep React (no tutorial hopping) – Backend basics – Some DSA That grind got me a full-stack role at a US-based company (onsite in Bhopal). Life tested me again when my grandfather the person I always looked up to had a heart attack. It broke me. I quit. Took time. Regrouped. Started freelancing. Got 2 to 3 projects. Kept moving forward. My journey hasn’t been clean. It’s been messy, uncertain, and uncomfortable. But here I am. 2025 was just a warm-up. 2026 is execution. If you’re starting from zero don’t underestimate what 1–2 years of focused grind can do.

Sambhav.apk▲

32,516 просмотров • 6 месяцев назад

How to build a viral Web3 app in an afternoon using the ChainGPT AI skill for Claude Code. No coding experience required. I built Roast My Wallet. Paste any Ethereum wallet address, get a savage AI-generated roast of your trading history, a Degen Score out of 100, an on-chain report card, and three AI-generated NFT portraits. Here's exactly how it came together. Setup (3 minutes): 🔸Install Claude Code at 🔸Run /plugin install ChainGPT-org/chaingpt-claude-skill 🔸Get an API key at 🔸Type /chaingpt and describe what you want to build What the skill actually does: The ChainGPT skill doesn't just give you starter code. It knows the entire API. Every endpoint, every parameter, every credit cost, every error code. When I asked it to build the roast feature, it knew to call the LLM endpoint, how to stream the response back to the browser in real time, and how to handle errors automatically. I didn't look up a single thing. How it works under the hood: 1. Pulls real ETH balance and transaction count from the Ethereum blockchain 2. Feeds those numbers into ChainGPT's LLM and streams the roast back live 3. Calculates a Degen Score from your tx count vs balance ratio 4. Generates a report card with letter grades across Trading, Patience, Risk, Diamond Hands, and NGMI 5. Uses the roast text to generate three custom NFT portraits in parallel via VeloGen 6. Packages everything into a downloadable PNG card ready to post 7. Every feature came from describing what I wanted: 8. "Make the API key server-side." Done. 9. "Add an animated arc gauge for the degen score." Done. 10. "Generate NFT portraits using the roast text as context." Done. I never wrote a function or debugged an API response. I described outcomes. The ChainGPT skill handled the rest. If you can describe what you want to build, you can build it. Get your API key. Install the skill. /plugin install ChainGPT-org/chaingpt-claude-skill Anyone can build with ChainGPT AI!

How to build a viral Web3 app in an afternoon using the ChainGPT AI skill for Claude Code. No coding experience required. I built Roast My Wallet. Paste any Ethereum wallet address, get a savage AI-generated roast of your trading history, a Degen Score out of 100, an on-chain report card, and three AI-generated NFT portraits. Here's exactly how it came together. Setup (3 minutes): 🔸Install Claude Code at 🔸Run /plugin install ChainGPT-org/chaingpt-claude-skill 🔸Get an API key at 🔸Type /chaingpt and describe what you want to build What the skill actually does: The ChainGPT skill doesn't just give you starter code. It knows the entire API. Every endpoint, every parameter, every credit cost, every error code. When I asked it to build the roast feature, it knew to call the LLM endpoint, how to stream the response back to the browser in real time, and how to handle errors automatically. I didn't look up a single thing. How it works under the hood: 1. Pulls real ETH balance and transaction count from the Ethereum blockchain 2. Feeds those numbers into ChainGPT's LLM and streams the roast back live 3. Calculates a Degen Score from your tx count vs balance ratio 4. Generates a report card with letter grades across Trading, Patience, Risk, Diamond Hands, and NGMI 5. Uses the roast text to generate three custom NFT portraits in parallel via VeloGen 6. Packages everything into a downloadable PNG card ready to post 7. Every feature came from describing what I wanted: 8. "Make the API key server-side." Done. 9. "Add an animated arc gauge for the degen score." Done. 10. "Generate NFT portraits using the roast text as context." Done. I never wrote a function or debugged an API response. I described outcomes. The ChainGPT skill handled the rest. If you can describe what you want to build, you can build it. Get your API key. Install the skill. /plugin install ChainGPT-org/chaingpt-claude-skill Anyone can build with ChainGPT AI!

ChainGPT

29,291 просмотров • 2 месяцев назад

Cal AI might be the most viral health app this year. 8M+ downloads, projected to do $30M revenue this year. Built by two teenagers. Everyone's using it. But nobody's talking about the fact that their AI is completely broken... To the point where users are manually correcting EVERY meal. • Bowl of grapes: 60 cal estimate (actually ~260) • 4 boiled eggs: 1,010 cal estimate (actually ~300) • Meat portions: consistently off by 50% These aren't my words, but the reviews you can see for yourself on App Store and other places. If the whole USP is saving time vs manual logging, and you still have to correct everything... what's the point? What Cal AI did get right: Distribution. • Viral TikTok content • Smart influencer partnerships • 8M downloads in under a year They absolutely crushed GTM. But the product doesn't work lol. The gap between the "90% accuracy" claim vs the actual user experience kills trust. And in health apps, trust is everything. This is the problem with AI apps across the board right now. Everyone's racing to ship fast and go viral. Nobody's asking: "Does this actually solve the problem?" Distribution > product quality is a losing game. As a result, you're bound to encounter problems: 1. Training data doesn't match real-world variety 2. No depth sensing for portion size 3. Poor training data on homemade meals 4. Zero context (is that chicken grilled or fried?) You only get fast & inaccurate answers. This is why, when I started building my own recipe app, I looked at Cal and other AI nutrition apps and noticed that being accurate was the biggest factor. Here's how we're building Nonna differently: ✓ Multi-model AI (different models for different foods) ✓ User feedback loop to improve estimates ✓ Manual override that actually trains the system ✓ Ship when it works, not when it's "good enough" If the AI can't nail it, we're not shipping it. But accuracy alone is boring. So we're also adding some additional features that make you want to use it daily: • Fridge Story: shareable infographic of your fridge contents • Mystery Ingredient: weekly cooking challenges • Cuisine Spin: random inspiration when you're stuck • Expectation vs Reality: before/after photo collages Tl;dr: Distribution gets downloads. Product keeps users. Cal got millions of downloads. How many people still use it daily after manually correcting every meal for a week? Viral marketing with a broken product = expensive way to disappoint people.

Cal AI might be the most viral health app this year. 8M+ downloads, projected to do $30M revenue this year. Built by two teenagers. Everyone's using it. But nobody's talking about the fact that their AI is completely broken... To the point where users are manually correcting EVERY meal. • Bowl of grapes: 60 cal estimate (actually ~260) • 4 boiled eggs: 1,010 cal estimate (actually ~300) • Meat portions: consistently off by 50% These aren't my words, but the reviews you can see for yourself on App Store and other places. If the whole USP is saving time vs manual logging, and you still have to correct everything... what's the point? What Cal AI did get right: Distribution. • Viral TikTok content • Smart influencer partnerships • 8M downloads in under a year They absolutely crushed GTM. But the product doesn't work lol. The gap between the "90% accuracy" claim vs the actual user experience kills trust. And in health apps, trust is everything. This is the problem with AI apps across the board right now. Everyone's racing to ship fast and go viral. Nobody's asking: "Does this actually solve the problem?" Distribution > product quality is a losing game. As a result, you're bound to encounter problems: 1. Training data doesn't match real-world variety 2. No depth sensing for portion size 3. Poor training data on homemade meals 4. Zero context (is that chicken grilled or fried?) You only get fast & inaccurate answers. This is why, when I started building my own recipe app, I looked at Cal and other AI nutrition apps and noticed that being accurate was the biggest factor. Here's how we're building Nonna differently: ✓ Multi-model AI (different models for different foods) ✓ User feedback loop to improve estimates ✓ Manual override that actually trains the system ✓ Ship when it works, not when it's "good enough" If the AI can't nail it, we're not shipping it. But accuracy alone is boring. So we're also adding some additional features that make you want to use it daily: • Fridge Story: shareable infographic of your fridge contents • Mystery Ingredient: weekly cooking challenges • Cuisine Spin: random inspiration when you're stuck • Expectation vs Reality: before/after photo collages Tl;dr: Distribution gets downloads. Product keeps users. Cal got millions of downloads. How many people still use it daily after manually correcting every meal for a week? Viral marketing with a broken product = expensive way to disappoint people.

Denislav Jeliazkov

37,989 просмотров • 8 месяцев назад

I just sold my startup Talknotes for $200,000 on acquire.com 💸🤯🤩💰🥳🎉 I launched it last August when I was looking for an idea I could grow with paid ads, and made a MVP in one week. I took it from $0 to $7500 MRR in just 11 months. 👉 Here is how I grew it from zero: 💡 Idea: I got the idea when I tried to write a tweet using Google Doc's transcription tool, but it was terrible. And I was pretty sure I wasn't the one too lazy to type. So I made my own solution, and Talknotes was created. The audience is pretty broad so it was a perfect fit for Meta ads However… ✅ Validation: My rule is to only reinvest what the project generates, so, no ads until I make enough cashflow ❌ Listing on startup directories + a few Twitter sales generated $700 after 10 days. Yes, it's not much, but more than enough to show there is interest in the product and tell me to keep working on it 🤩 I started adding the features users requested, but the launch effect started to wear off and daily revenues quickly went to $0 after a few weeks 🫥 I got depressed and almost gave up on the app... 😔 But luckily, my friends and Dan Kulkov pushed me to continue And I'm glad they did because In October, I launched on Product Hunt 😸 and it blew up 🤯 It got Product of the Day and reached $1500 MRR thanks to the media coverage 🚀🚀 Until then, everything was done using vanilla JS/CSS/HTML + Node for back end. It's simple and easy, but I saw the limitations, so I remade the app using Nuxt to make it easier in the future 🏗️ (thanks to @blackevilgoblin and Piotr Jura for the content/courses! Tim Bennetto as well for the basics!) After that, I took a break and then launched ads on Facebook. The strategy is simple: Catch people's attention, and show them how the app can help them improve their life. No need to over-complicate 🙅‍♂️ Making good creatives is 80% of the job when doing ads on Facebook, most of the technical stuff is done by AI now. Thanks to the boost in traffic, I implemented a feedback loop: 1) Get new users 👥 2) Learn to know them with the onboarding form 💬 3) Make more ads based on the data you get from onboarding 📝 And it completely blew up. MRR doubled in ~2 months However... In May, I had a bad burnout 🥵😩 Multiple bugs slipped into the app, and I had to spend 2 days fixing everything in an emergency while revenues plummeted. This completely fucked me up mentally and had a hard time working on the app after that ( 💀💀 So I decided to list it on acquire.com and made a Twitter post ( I listed it for $200,000, a pretty low price considering the revenues and fast growth. I could have gotten $300,000 if I accepted payment over time, but $200,000 today is better than $300,000 tomorrow for me. 🚨 The process went smoothly until we tried to use Escrow, which almost fucked up the whole deal. (details: I got extremely lucky because the buyer really wanted to buy the app, but this could have ended the deal. We had to wait over a week to get the money back from them, even tho they said they already refunded it. But luckily, after threatening them, they sent it back the next day 🙃 The buyer finally got the money back, I transferred every asset to him, and he sent me the wire. With the profit made from the app + the sale, and other projects, I'm 30% away from being a millionaire 🤯 With this amount, I can pretty much retire in Asia if I want to. But that's just the beginning, I’m going to launch new projects soon! 🚀 But before that, I need to take a real vacation and detox. My brain is completely fucked up by those last 2 months. I gained weight, and got brain rot from scrolling all day waiting for the acquisition to move forward 💀💀 Surprisingly, doing absolutely nothing is 10x more exhausting than working 15h per day 🥱 Now, all this might sound like an overnight success. It is not ‼️ This is the result of 7 years of failure and working like a madman. I launched over 40 projects in those 7 years, and most of them failed. But a few took off, and that’s all I needed All those weeks working 15h/day without weekends and vacation feels soul-sucking when you don’t see the end, but this is what took me there You only need to win once to snowball everything. Work hard, focus, fail a lot and keep shipping fast. 🚀🚀 Thanks to you for reading until here, and thanks to everyone who supported me 🤞

I just sold my startup Talknotes for $200,000 on acquire.com 💸🤯🤩💰🥳🎉 I launched it last August when I was looking for an idea I could grow with paid ads, and made a MVP in one week. I took it from $0 to $7500 MRR in just 11 months. 👉 Here is how I grew it from zero: 💡 Idea: I got the idea when I tried to write a tweet using Google Doc's transcription tool, but it was terrible. And I was pretty sure I wasn't the one too lazy to type. So I made my own solution, and Talknotes was created. The audience is pretty broad so it was a perfect fit for Meta ads However… ✅ Validation: My rule is to only reinvest what the project generates, so, no ads until I make enough cashflow ❌ Listing on startup directories + a few Twitter sales generated $700 after 10 days. Yes, it's not much, but more than enough to show there is interest in the product and tell me to keep working on it 🤩 I started adding the features users requested, but the launch effect started to wear off and daily revenues quickly went to $0 after a few weeks 🫥 I got depressed and almost gave up on the app... 😔 But luckily, my friends and Dan Kulkov pushed me to continue And I'm glad they did because In October, I launched on Product Hunt 😸 and it blew up 🤯 It got Product of the Day and reached $1500 MRR thanks to the media coverage 🚀🚀 Until then, everything was done using vanilla JS/CSS/HTML + Node for back end. It's simple and easy, but I saw the limitations, so I remade the app using Nuxt to make it easier in the future 🏗️ (thanks to @blackevilgoblin and Piotr Jura for the content/courses! Tim Bennetto as well for the basics!) After that, I took a break and then launched ads on Facebook. The strategy is simple: Catch people's attention, and show them how the app can help them improve their life. No need to over-complicate 🙅‍♂️ Making good creatives is 80% of the job when doing ads on Facebook, most of the technical stuff is done by AI now. Thanks to the boost in traffic, I implemented a feedback loop: 1) Get new users 👥 2) Learn to know them with the onboarding form 💬 3) Make more ads based on the data you get from onboarding 📝 And it completely blew up. MRR doubled in ~2 months However... In May, I had a bad burnout 🥵😩 Multiple bugs slipped into the app, and I had to spend 2 days fixing everything in an emergency while revenues plummeted. This completely fucked me up mentally and had a hard time working on the app after that ( 💀💀 So I decided to list it on acquire.com and made a Twitter post ( I listed it for $200,000, a pretty low price considering the revenues and fast growth. I could have gotten $300,000 if I accepted payment over time, but $200,000 today is better than $300,000 tomorrow for me. 🚨 The process went smoothly until we tried to use Escrow, which almost fucked up the whole deal. (details: I got extremely lucky because the buyer really wanted to buy the app, but this could have ended the deal. We had to wait over a week to get the money back from them, even tho they said they already refunded it. But luckily, after threatening them, they sent it back the next day 🙃 The buyer finally got the money back, I transferred every asset to him, and he sent me the wire. With the profit made from the app + the sale, and other projects, I'm 30% away from being a millionaire 🤯 With this amount, I can pretty much retire in Asia if I want to. But that's just the beginning, I’m going to launch new projects soon! 🚀 But before that, I need to take a real vacation and detox. My brain is completely fucked up by those last 2 months. I gained weight, and got brain rot from scrolling all day waiting for the acquisition to move forward 💀💀 Surprisingly, doing absolutely nothing is 10x more exhausting than working 15h per day 🥱 Now, all this might sound like an overnight success. It is not ‼️ This is the result of 7 years of failure and working like a madman. I launched over 40 projects in those 7 years, and most of them failed. But a few took off, and that’s all I needed All those weeks working 15h/day without weekends and vacation feels soul-sucking when you don’t see the end, but this is what took me there You only need to win once to snowball everything. Work hard, focus, fail a lot and keep shipping fast. 🚀🚀 Thanks to you for reading until here, and thanks to everyone who supported me 🤞

Nico

457,894 просмотров • 2 лет назад

For new followers: - I'm a long-time investor and builder in this space. - Founding Contributor of Realms.World ☁️. - Co-founder of Dojo. - Builder with the kings at Cartridge. - Starknet (Privacy Arc) class of '21. - Founder and Game Director of ETERNUM HAS MOVED. - Founder of Daydreams.Systems (x402, 8004 agents) My prime purpose for the past three years has been to build onchain infrastructure to enable the next generation of onchain experiences. This is done Starknet (Privacy Arc) as it is the superior VM for building complex applications—this will become clear soon enough. I work up and down the entire stack, from low-level indexing and contracts to GUI design. Nothing is out of scope. I have been pushing on agents for two years, mostly using existing frameworks like , until I came across @ElizaOS_ai in October. As I focused on building agents for ETERNUM HAS MOVED, it became clear that agents playing games require infinite paths to achieve goals. Thus, it's not scalable to hardcode functions—agents need to have total fluidity to take any action or call anything the game requires in any order. And ironically onchain infra is perfect for agent playgrounds because of its open nature. This exploration led me to create Daydreams.Systems (x402, 8004 agents), which focuses on the hardest problems of agents: long time-horizon goals using Hierarchical task networks (HTN). Daydreams agents don't require custom code—they work entirely based on 'sleeves'—which are just markdown files that explain how the agent can interact with the service (API docs, game guides, etc.) My thesis is simple. By focusing on the hardest problem (games), the design of the library will naturally lean towards an optimal structure for any problem an agent could face. We are early in this path and iterating with speed. If you are an onchain app developer or game builder—DM me, I want to know the architecture of your game so we can build sleeves together.

For new followers: - I'm a long-time investor and builder in this space. - Founding Contributor of Realms.World ☁️. - Co-founder of Dojo. - Builder with the kings at Cartridge. - Starknet (Privacy Arc) class of '21. - Founder and Game Director of ETERNUM HAS MOVED. - Founder of Daydreams.Systems (x402, 8004 agents) My prime purpose for the past three years has been to build onchain infrastructure to enable the next generation of onchain experiences. This is done Starknet (Privacy Arc) as it is the superior VM for building complex applications—this will become clear soon enough. I work up and down the entire stack, from low-level indexing and contracts to GUI design. Nothing is out of scope. I have been pushing on agents for two years, mostly using existing frameworks like , until I came across @ElizaOS_ai in October. As I focused on building agents for ETERNUM HAS MOVED, it became clear that agents playing games require infinite paths to achieve goals. Thus, it's not scalable to hardcode functions—agents need to have total fluidity to take any action or call anything the game requires in any order. And ironically onchain infra is perfect for agent playgrounds because of its open nature. This exploration led me to create Daydreams.Systems (x402, 8004 agents), which focuses on the hardest problems of agents: long time-horizon goals using Hierarchical task networks (HTN). Daydreams agents don't require custom code—they work entirely based on 'sleeves'—which are just markdown files that explain how the agent can interact with the service (API docs, game guides, etc.) My thesis is simple. By focusing on the hardest problem (games), the design of the library will naturally lean towards an optimal structure for any problem an agent could face. We are early in this path and iterating with speed. If you are an onchain app developer or game builder—DM me, I want to know the architecture of your game so we can build sleeves together.

loaf

43,320 просмотров • 1 год назад

Elon Musk just identified the next crisis in AI. It’s not a shortage. It’s an unusable surplus. Musk: “By the end of this year, chip production will outpace the ability to turn chips on.” For three years the world was starved for silicon. Every lab, every government, every company racing to secure the chips that determine who wins the AI era. That bottleneck is ending. A new one is replacing it. Musk: “The chips are going to be piling up and not be able to be turned on.” Billions of dollars of the most advanced AI hardware ever built. Sitting dark. Not because the chips don’t work. Because there isn’t enough electricity to run them. You can’t print a power plant the way you print a chip. The fabrication plants scaled. The grid didn’t. And now the most valuable hardware in history is about to hit a wall that no amount of capital can instantly solve. Compute is about to become abundant. Electricity is about to become the most valuable commodity on earth. Three years obsessing over silicon yields. Physics doesn’t care about your chip architecture if your data center can’t pull enough megawatts. The war isn’t about who can manufacture the most silicon anymore. It’s about who has the raw power to plug it in. Whoever solves energy first doesn’t just win. They own the infrastructure everyone else needs to compete. The losers stack useless chips in warehouses waiting for power that never arrives. We built a trillion dollar engine and forgot the fuel. That’s the AI race right now.

Elon Musk just identified the next crisis in AI. It’s not a shortage. It’s an unusable surplus. Musk: “By the end of this year, chip production will outpace the ability to turn chips on.” For three years the world was starved for silicon. Every lab, every government, every company racing to secure the chips that determine who wins the AI era. That bottleneck is ending. A new one is replacing it. Musk: “The chips are going to be piling up and not be able to be turned on.” Billions of dollars of the most advanced AI hardware ever built. Sitting dark. Not because the chips don’t work. Because there isn’t enough electricity to run them. You can’t print a power plant the way you print a chip. The fabrication plants scaled. The grid didn’t. And now the most valuable hardware in history is about to hit a wall that no amount of capital can instantly solve. Compute is about to become abundant. Electricity is about to become the most valuable commodity on earth. Three years obsessing over silicon yields. Physics doesn’t care about your chip architecture if your data center can’t pull enough megawatts. The war isn’t about who can manufacture the most silicon anymore. It’s about who has the raw power to plug it in. Whoever solves energy first doesn’t just win. They own the infrastructure everyone else needs to compete. The losers stack useless chips in warehouses waiting for power that never arrives. We built a trillion dollar engine and forgot the fuel. That’s the AI race right now.

Dustin

705,220 просмотров • 5 месяцев назад

If you’ve ever managed custom icons in React Native, you know the frustration of choosing between performance and developer experience. Libraries like 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝘀𝘃𝗴 are flexible but heavy. Every icon creates its own React subtree. The alternative? Manual icon fonts that force you into a constant back-and-forth of using web tools like IcoMoon and syncing font assets every time a design changes. 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 𝗟𝗮𝗯𝘀 just released 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 to solve exactly this. It’s a build-time icon font generator that gives you the performance of native fonts with the flexibility of simple SVG files. 𝗪𝗵𝗮𝘁’𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴? Instead of rendering complex vector paths at runtime, this library automatically converts your folder of SVGs into an optimized icon font during the build process. It essentially teaches your app to treat icons like standard text characters, which allows it to bypass React’s component tree and layout engine entirely. ➡️ 𝗕𝘂𝗶𝗹𝗱-𝘁𝗶𝗺𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: It handles the entire pipeline—watching your icon folder, converting SVGs to .ttf files, and linking them to your native project automatically. ➡️ 𝗡𝗮𝘁𝗶𝘃𝗲 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: Because icons render as native text glyphs, it is significantly faster than traditional SVG rendering, making it the ideal choice for long, scrollable lists or icon-heavy dashboards. ➡️ 𝗘𝘅𝗽𝗼 𝗖𝗼𝗻𝗳𝗶𝗴 𝗣𝗹𝘂𝗴𝗶𝗻: It features first-class support for Expo, automating the native plumbing like Info.plist updates and asset linking during the prebuild phase. ➡️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗧𝘆𝗽𝗲 𝗦𝗮𝗳𝗲𝘁𝘆: The library generates TypeScript definitions for your icon set, providing full IDE autocomplete and ensuring you never break the UI with a misspelled icon name. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀? In high-performance applications, small overheads add up. By shifting the heavy lifting from the mobile device to your build machine, 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 ensures your UI stays buttery smooth while keeping your developer workflow modern. It’s another great example of how 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 continues to solve the "last mile" of performance friction in the ecosystem. Before you migrate your entire library, keep in mind: this is designed for the 𝗡𝗲𝘄 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 (Fabric) and requires React Native 0.74 or higher. #ReactNative #Expo #SoftwareMansion #Icons #MobileDev #Performance #DeveloperExperience #OpenSource #JavaScript #TypeScript #SVG #Fabric

If you’ve ever managed custom icons in React Native, you know the frustration of choosing between performance and developer experience. Libraries like 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝘀𝘃𝗴 are flexible but heavy. Every icon creates its own React subtree. The alternative? Manual icon fonts that force you into a constant back-and-forth of using web tools like IcoMoon and syncing font assets every time a design changes. 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 𝗟𝗮𝗯𝘀 just released 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 to solve exactly this. It’s a build-time icon font generator that gives you the performance of native fonts with the flexibility of simple SVG files. 𝗪𝗵𝗮𝘁’𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝗶𝗻𝗴? Instead of rendering complex vector paths at runtime, this library automatically converts your folder of SVGs into an optimized icon font during the build process. It essentially teaches your app to treat icons like standard text characters, which allows it to bypass React’s component tree and layout engine entirely. ➡️ 𝗕𝘂𝗶𝗹𝗱-𝘁𝗶𝗺𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: It handles the entire pipeline—watching your icon folder, converting SVGs to .ttf files, and linking them to your native project automatically. ➡️ 𝗡𝗮𝘁𝗶𝘃𝗲 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: Because icons render as native text glyphs, it is significantly faster than traditional SVG rendering, making it the ideal choice for long, scrollable lists or icon-heavy dashboards. ➡️ 𝗘𝘅𝗽𝗼 𝗖𝗼𝗻𝗳𝗶𝗴 𝗣𝗹𝘂𝗴𝗶𝗻: It features first-class support for Expo, automating the native plumbing like Info.plist updates and asset linking during the prebuild phase. ➡️ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰 𝗧𝘆𝗽𝗲 𝗦𝗮𝗳𝗲𝘁𝘆: The library generates TypeScript definitions for your icon set, providing full IDE autocomplete and ensuring you never break the UI with a misspelled icon name. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀? In high-performance applications, small overheads add up. By shifting the heavy lifting from the mobile device to your build machine, 𝗿𝗲𝗮𝗰𝘁-𝗻𝗮𝘁𝗶𝘃𝗲-𝗻𝗮𝗻𝗼-𝗶𝗰𝗼𝗻𝘀 ensures your UI stays buttery smooth while keeping your developer workflow modern. It’s another great example of how 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗠𝗮𝗻𝘀𝗶𝗼𝗻 continues to solve the "last mile" of performance friction in the ecosystem. Before you migrate your entire library, keep in mind: this is designed for the 𝗡𝗲𝘄 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 (Fabric) and requires React Native 0.74 or higher. #ReactNative #Expo #SoftwareMansion #Icons #MobileDev #Performance #DeveloperExperience #OpenSource #JavaScript #TypeScript #SVG #Fabric

The React Native Rewind

24,992 просмотров • 2 месяцев назад

For the past few weeks I’ve been teaching 50+ kids how to create their own games with AI. The results have been incredible 🤯 I started with my 5 y/o nephew because I was worried about him spending hours doomscrolling and consuming brainrot content. He built his first game using v0, though I had to walk him through each step. Watching kids interact with these tools taught me so much about how they think, where they get stuck, and what keeps them motivated. The moment that really struck me came right after he finished that first game. Every time I saw him afterward, he’d run up and ask, “Did you bring your laptop so I can keep playing?”. For him, “playing” meant creating. That kind of excitement is organic pull. Don’t get me wrong, I love v0 and Lovable. They’re insanely powerful. Their UIs just aren’t designed for kids, and that’s totally fine. Kids still need guidance, structure, and a bit of tutoring to turn ideas into something playable. I’m seeing tech leaders push in this direction too, and I think there’s a real opportunity here (Matias Woloski Thomas Wolf). Kids are the future, and I don’t want to live in a world where they spend precious time consuming instead of creating. That’s why I love tools like v0, Lovable, wabi , Cursor . They’re empowering more people to become creators. I want that same feeling for kids. What Guillermo is saying is real. Kids need to be AI-literate from the outset. It honestly makes me sad to think about my nephew growing up and falling behind on AI and everything happening around him because he’s stuck in Roblox or TikTok. That’s why I built Rabbit 🐰 for him. It started as a simple prototype, but somehow I ended up talking with 200+ parents and kids, tech leaders, investors, and people I never imagined meeting around the world. Rabbit now has 100+ people on the waitlist, and 10 kids are using it two to three times per week on average to create their own games 🫡 I’m not sure yet if this will become my full-time project, but I deeply care about it. If you’re building in this space, I’d love to connect and share ideas. And if you’re a parent interested in Rabbit, I’d love your feedback. Sharing a short video of kids using Rabbit below:

For the past few weeks I’ve been teaching 50+ kids how to create their own games with AI. The results have been incredible 🤯 I started with my 5 y/o nephew because I was worried about him spending hours doomscrolling and consuming brainrot content. He built his first game using v0, though I had to walk him through each step. Watching kids interact with these tools taught me so much about how they think, where they get stuck, and what keeps them motivated. The moment that really struck me came right after he finished that first game. Every time I saw him afterward, he’d run up and ask, “Did you bring your laptop so I can keep playing?”. For him, “playing” meant creating. That kind of excitement is organic pull. Don’t get me wrong, I love v0 and Lovable. They’re insanely powerful. Their UIs just aren’t designed for kids, and that’s totally fine. Kids still need guidance, structure, and a bit of tutoring to turn ideas into something playable. I’m seeing tech leaders push in this direction too, and I think there’s a real opportunity here (Matias Woloski Thomas Wolf). Kids are the future, and I don’t want to live in a world where they spend precious time consuming instead of creating. That’s why I love tools like v0, Lovable, wabi , Cursor . They’re empowering more people to become creators. I want that same feeling for kids. What Guillermo is saying is real. Kids need to be AI-literate from the outset. It honestly makes me sad to think about my nephew growing up and falling behind on AI and everything happening around him because he’s stuck in Roblox or TikTok. That’s why I built Rabbit 🐰 for him. It started as a simple prototype, but somehow I ended up talking with 200+ parents and kids, tech leaders, investors, and people I never imagined meeting around the world. Rabbit now has 100+ people on the waitlist, and 10 kids are using it two to three times per week on average to create their own games 🫡 I’m not sure yet if this will become my full-time project, but I deeply care about it. If you’re building in this space, I’d love to connect and share ideas. And if you’re a parent interested in Rabbit, I’d love your feedback. Sharing a short video of kids using Rabbit below:

Fausto

44,125 просмотров • 6 месяцев назад

Eleven years ago I founded my first startup. One of the first things I did was to get a desk at the startup coworking space at Google Campus in Old Street. Through that community, I met so many of the people who would shape my career and learned so much about what the startup ethos is truly about. As we have scaled Attio, we've partnered with Google Cloud to build on top of the mind blowing technologies they've created like Spanner, Colossus and Gemini to power a new generation of CRM for our customers. For all these reasons, Google is deeply woven into my startup journey and that makes today's announcement so special to me. I'm beyond excited to announce our $52 million Series B, led by Michael McBride and the GV, along with the continued support of our incredible partners from Redpoint , Point Nine , Balderton Capital and 01A. We're entering a software renaissance driven by AI and we're unbelievably excited about continuing the hard work of delivering the next generation of CRM. We're building a truly AI-native platform that can run code, integrate anywhere and bring unified context for the next generation of autonomous workflows. None of this would have been possible without the support of the more than 5,000 customers who have already chosen Attio as the backbone of their GTM stack. Your belief in our vision is what has made this possible and I can't wait to share more about some of the incredible functionality that's still to come. I'm incredibly grateful for the continued support of alex bard , Patrick Chase, Ricardo Sequerra Amram, Daniel Waterhouse and dick costolo whose belief in Attio from the earliest days has been so essential to our progress so far and to my co-founder Nicolas Sharp, for the many sleepless nights and challenging decisions that got us this far. We've got so much still to build, and we're always hiring, so if you are interested in being part of reinventing the core of the GTM stack, please take a look at For now though, it's back to building!

Eleven years ago I founded my first startup. One of the first things I did was to get a desk at the startup coworking space at Google Campus in Old Street. Through that community, I met so many of the people who would shape my career and learned so much about what the startup ethos is truly about. As we have scaled Attio, we've partnered with Google Cloud to build on top of the mind blowing technologies they've created like Spanner, Colossus and Gemini to power a new generation of CRM for our customers. For all these reasons, Google is deeply woven into my startup journey and that makes today's announcement so special to me. I'm beyond excited to announce our $52 million Series B, led by Michael McBride and the GV, along with the continued support of our incredible partners from Redpoint , Point Nine , Balderton Capital and 01A. We're entering a software renaissance driven by AI and we're unbelievably excited about continuing the hard work of delivering the next generation of CRM. We're building a truly AI-native platform that can run code, integrate anywhere and bring unified context for the next generation of autonomous workflows. None of this would have been possible without the support of the more than 5,000 customers who have already chosen Attio as the backbone of their GTM stack. Your belief in our vision is what has made this possible and I can't wait to share more about some of the incredible functionality that's still to come. I'm incredibly grateful for the continued support of alex bard , Patrick Chase, Ricardo Sequerra Amram, Daniel Waterhouse and dick costolo whose belief in Attio from the earliest days has been so essential to our progress so far and to my co-founder Nicolas Sharp, for the many sleepless nights and challenging decisions that got us this far. We've got so much still to build, and we're always hiring, so if you are interested in being part of reinventing the core of the GTM stack, please take a look at For now though, it's back to building!

Alexander Christie

16,506 просмотров • 11 месяцев назад

I'M LOOKING FOR A TECHNICAL PARTNER I'm looking for a coding wizard to help me build software (and to bounce ideas with). The deal is simple: you build / I distribute You do all technical work. I do all marketing, distribution, customer research. What I bring to the table: • deep expertise in social media marketing/distribution/email marketing/copywriting • total audience of 160k + 42k newsletter (that's a lot of eyeballs ready to see what we build) • big network of creators we can use to co-market • experience building media companies from scratch • sold over 7 figs worth of products to an audience before I deeply care about product so I'll be involved in everything but the coding side. I will document our journey with build in public content (X, LinkedIn, YouTube). You don't need to be part of the content if you don't want to, I'll gladly be the dancing monkey. What I AM looking for: • Full stack (at least to certain extent to get decent MVPs out there) • high agency, high creativity and product sense< • you've made money with your software before • a love for cash-flow • you love homemade goulash as much as I do (well, this one is not set in stone) • someone to share shitposts and memes with (you can't compete with someone who's having fun, I deeply believe this) • someone who is obsessed with building something that people LOVE instead of just use • someone who wants to build something to be really proud of What I'm NOT looking for: • ideas that need VC funding to get started • 2 years of building before we see a dollar • someone who started coding 12 months ago • someone running 3 other side projects • someone addicted to call-culture I'm not 100% certain on the idea yet. We'll figure this out together by testing demand with an audience. We'll probably test a few ideas quickly before going all-in on whatever gets the best signal from the market. Areas I find interesting right now: • AI enhanced-B2B content/GTM/marketing tools • Financial market analytics/consumer finance • Gamified health/longevity apps (probably mobile) Building and creativity is a way of life for me. It goes far beyond the money-creation part of work. I love bringing things into the world. Best case it's similar for you. We'll shoot the shit a lot, send memes, and have fun while working hard on whatever we build. There's also an option to do this on a salary instead of a split I'm open to both. Answer a few quick questions in the form below (next post) I will reach out to people that seem like a good fit. Please tag people who might be interested. RT for visibility so your coding genius friends can build something awesome with me!

I'M LOOKING FOR A TECHNICAL PARTNER I'm looking for a coding wizard to help me build software (and to bounce ideas with). The deal is simple: you build / I distribute You do all technical work. I do all marketing, distribution, customer research. What I bring to the table: • deep expertise in social media marketing/distribution/email marketing/copywriting • total audience of 160k + 42k newsletter (that's a lot of eyeballs ready to see what we build) • big network of creators we can use to co-market • experience building media companies from scratch • sold over 7 figs worth of products to an audience before I deeply care about product so I'll be involved in everything but the coding side. I will document our journey with build in public content (X, LinkedIn, YouTube). You don't need to be part of the content if you don't want to, I'll gladly be the dancing monkey. What I AM looking for: • Full stack (at least to certain extent to get decent MVPs out there) • high agency, high creativity and product sense< • you've made money with your software before • a love for cash-flow • you love homemade goulash as much as I do (well, this one is not set in stone) • someone to share shitposts and memes with (you can't compete with someone who's having fun, I deeply believe this) • someone who is obsessed with building something that people LOVE instead of just use • someone who wants to build something to be really proud of What I'm NOT looking for: • ideas that need VC funding to get started • 2 years of building before we see a dollar • someone who started coding 12 months ago • someone running 3 other side projects • someone addicted to call-culture I'm not 100% certain on the idea yet. We'll figure this out together by testing demand with an audience. We'll probably test a few ideas quickly before going all-in on whatever gets the best signal from the market. Areas I find interesting right now: • AI enhanced-B2B content/GTM/marketing tools • Financial market analytics/consumer finance • Gamified health/longevity apps (probably mobile) Building and creativity is a way of life for me. It goes far beyond the money-creation part of work. I love bringing things into the world. Best case it's similar for you. We'll shoot the shit a lot, send memes, and have fun while working hard on whatever we build. There's also an option to do this on a salary instead of a split I'm open to both. Answer a few quick questions in the form below (next post) I will reach out to people that seem like a good fit. Please tag people who might be interested. RT for visibility so your coding genius friends can build something awesome with me!

Ole Lehmann

117,700 просмотров • 7 месяцев назад

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:

For 6 months I woke up at 5 AM to catch Asian markets on Polymarket. During that time I lost my girlfriend, gained 8 kg, and got used to drinking coffee instead of breakfast Then I wrote an agent that monitors everything for me while I sleep. In the 1st month income went up 15% and I finally deleted the 5 AM alarm Turns out a half-asleep human trades worse than a 200-line script I thought discipline meant waking up early. In reality it was just stubbornness that cost me money and health. When I finally sat down to build the agent it became clear why Here is what is under the hood: 1. Sentiment analysis powered by Claude. Every 15 minutes the agent runs a feed from 40+ Asian sources: Reuters Asia, Nikkei, South China Morning Post, Yonhap 2. NLP tone classification. It compares sentiment shifts to open markets on Polymarket through the API, and if the news has already dropped but the odds have not reacted yet that is the entry window 3. Kelly criterion. A mathematical formula for position sizing instead of my usual "I will bet more, feeling lucky" 4. A hard stop at 5% of the deposit per trade so that 1 mistake cannot kill the entire account 5. A cooldown between entries so the agent does not stack up a cluster of correlated positions These are exactly the rules I was missing at 5 AM. I knew them perfectly well but consistently ignored them because on adrenaline and caffeine every bet felt like an "obvious opportunity" When I ran a backtest on my old trades it was genuinely painful: 60% of the bets I placed by hand in a half-asleep state would have been rejected by the agent for failing the expected value filter Those were the exact ones dragging the whole result down When I was building my agent I needed a benchmark. A wallet that already trades on similar logic so I could compare my results to someone else's Found 1 that works almost like a mirror of what I described: same Asian markets, same cold calculation without emotion. I still keep it bookmarked and periodically check how it handles the same situations: That is actually the wallet I started with when testing auto-copying through a bot before I launched my own agent. A useful thing if you want to see how a strategy works on someone else's example first and only then build your own:

Blaze

126,718 просмотров • 3 месяцев назад

$I genuinely think the Terafab is going to end up being one of the biggest moves ever made in human history to secure the future of AI... and I think most people still don’t fully see what Elon is trying to do here. The signs are clear to me. This is Tesla, xAI, and SpaceX essentially hinting to us that they are not going to wait on the world to give them the compute the team needs. They are going to build it themselves at a scale no one has ever attempted. When you really break it down, it gets a bit nutty. This is going to be a fully vertically integrated chip factory that will be producing over 1 terawatt of AI compute per year. This is NEXT LEVEL BIG. Today, AI is limited by chips. You can have the best models, the best engineers, the best everything... but if you don’t have enough compute, you will eventually hit a wall. Elon told us, the world can only supply a tiny fraction of the chips his companies will need. So this is the solution. Terafab puts everything under one roof like design, manufacturing, memory, packaging, testing, which means that they can build chips very fast.. like really fast. I'm talking about 100-200 billion custom AI chips per year at full capacity. Chips designed specifically for: • Tesla cars and Optimus robots • xAI models • Space-based compute You see, while other companies and CEOs are thinking Earth, Elon is planning for AI in space. Around ~80% of the compute is expected to go orbital, powered by solar energy bc Earth simply doesn’t have enough electricity. The U.S. grid is only about ~0.5 terawatts, while space has basically UNLIMITED energy if you can capture it. And this is the steps to get it: Starship launches → space compute → solar-powered AI → feeds back into everything to Earth. Bro... Elon and his companies are playing at a whole different level... And this is why I keep telling people that the Terafab is going to be the secret ingredient that will be the real unlock for everything: • Robotaxis at scale • Billions of Optimus robots • Massive AI models running 24/7 • Future off-world, other planet infrastructure Without these chips, none of this can happen... but with the Terafab, all of this becomes possible. That’s why Elon is calling it “the final missing piece.” I agree.$

I genuinely think the Terafab is going to end up being one of the biggest moves ever made in human history to secure the future of AI... and I think most people still don’t fully see what Elon is trying to do here. The signs are clear to me. This is Tesla, xAI, and SpaceX essentially hinting to us that they are not going to wait on the world to give them the compute the team needs. They are going to build it themselves at a scale no one has ever attempted. When you really break it down, it gets a bit nutty. This is going to be a fully vertically integrated chip factory that will be producing over 1 terawatt of AI compute per year. This is NEXT LEVEL BIG. Today, AI is limited by chips. You can have the best models, the best engineers, the best everything... but if you don’t have enough compute, you will eventually hit a wall. Elon told us, the world can only supply a tiny fraction of the chips his companies will need. So this is the solution. Terafab puts everything under one roof like design, manufacturing, memory, packaging, testing, which means that they can build chips very fast.. like really fast. I'm talking about 100-200 billion custom AI chips per year at full capacity. Chips designed specifically for: • Tesla cars and Optimus robots • xAI models • Space-based compute You see, while other companies and CEOs are thinking Earth, Elon is planning for AI in space. Around ~80% of the compute is expected to go orbital, powered by solar energy bc Earth simply doesn’t have enough electricity. The U.S. grid is only about ~0.5 terawatts, while space has basically UNLIMITED energy if you can capture it. And this is the steps to get it: Starship launches → space compute → solar-powered AI → feeds back into everything to Earth. Bro... Elon and his companies are playing at a whole different level... And this is why I keep telling people that the Terafab is going to be the secret ingredient that will be the real unlock for everything: • Robotaxis at scale • Billions of Optimus robots • Massive AI models running 24/7 • Future off-world, other planet infrastructure Without these chips, none of this can happen... but with the Terafab, all of this becomes possible. That’s why Elon is calling it “the final missing piece.” I agree.

Teslaconomics

25,482 просмотров • 4 месяцев назад

My first offer for my first job in tech was part-time as an intern making $12.00/hr. I was a 46-year-old man with a wife, kids, and a mortgage but I accepted it. I had no idea days later I'd be called for an additional interview and as a result of that interview have the offer bumped up to a fulltime role. I had no idea but I was willing to take the leap. I'm sharing pieces of the offer letter because Claire Huxtable said "let the record show" 😂. I was so excited I started to make the video below. While I never finished the video, I have taken advantage of numerous opportunities since then to tell my story and share an example for other adults considering a transition into a technical career. Some relevant things in this short clip is that it is filmed from the "lonely loft" I've spoken of in numerous podcasts and Twitter spaces. You'll see a goals board behind me which I have spoken about many times as well. Those stories aren't fairy tales; this is my life. You'll notice on the board a goal of being hired in 2017. I didn't make it. I 100% did not achieve that goal. But I kept going and that's all I want to share with someone who may need encouragement today. No matter where someone may appear to me, often there's so many bumps in the road, setbacks, and letdowns that they may or may not choose to share. Don't YOU go feeling down in the dumps because of setbacks - we all have them. ALL OF US. Keep learning, building, teaching, pressing, pushing, strategizing, applying, relating, growing, and most importantly, KEEP GOING.

My first offer for my first job in tech was part-time as an intern making $12.00/hr. I was a 46-year-old man with a wife, kids, and a mortgage but I accepted it. I had no idea days later I'd be called for an additional interview and as a result of that interview have the offer bumped up to a fulltime role. I had no idea but I was willing to take the leap. I'm sharing pieces of the offer letter because Claire Huxtable said "let the record show" 😂. I was so excited I started to make the video below. While I never finished the video, I have taken advantage of numerous opportunities since then to tell my story and share an example for other adults considering a transition into a technical career. Some relevant things in this short clip is that it is filmed from the "lonely loft" I've spoken of in numerous podcasts and Twitter spaces. You'll see a goals board behind me which I have spoken about many times as well. Those stories aren't fairy tales; this is my life. You'll notice on the board a goal of being hired in 2017. I didn't make it. I 100% did not achieve that goal. But I kept going and that's all I want to share with someone who may need encouragement today. No matter where someone may appear to me, often there's so many bumps in the road, setbacks, and letdowns that they may or may not choose to share. Don't YOU go feeling down in the dumps because of setbacks - we all have them. ALL OF US. Keep learning, building, teaching, pressing, pushing, strategizing, applying, relating, growing, and most importantly, KEEP GOING.

LawrenceDCodes

12,626 просмотров • 1 год назад

if you know me, you know i only work on & talk about products i actually use as a trader first. given i wanted to get really deep on Backpack Futures, i deposited ~$5k into a fresh subacct when i started my new role at Backpack 🎒 & built a scaling schedule straight out of my prop days simple start → drawdown → clip size sheet. 13 levels, $5k to $100k, with trade count + drawdown rules at each level. the same framework we used to grow accounts in prop took ~4 months, but last week i completed the challenge: → 123 trades logged → ~$30M in volume → $BTC, $ETH, $SOL, $PAXG, $HYPE perps, all on Backpack nothing teaches you an exchange’s dynamics like actually trading on it. all the small nits, the microstructure quirks — you only find them by living in the product so what’s next? topping up with a fresh $100k and going deep on stock trading with Backpack Securities. public beta is live, v2 right around the corner, and i’ve been wanting to make this pivot for a while given everything happening on the equities side — AI, robotics, quantum, space time to run it back from $200k this time 😉🎒

if you know me, you know i only work on & talk about products i actually use as a trader first. given i wanted to get really deep on Backpack Futures, i deposited ~$5k into a fresh subacct when i started my new role at Backpack 🎒 & built a scaling schedule straight out of my prop days simple start → drawdown → clip size sheet. 13 levels, $5k to $100k, with trade count + drawdown rules at each level. the same framework we used to grow accounts in prop took ~4 months, but last week i completed the challenge: → 123 trades logged → ~$30M in volume → $BTC, $ETH, $SOL, $PAXG, $HYPE perps, all on Backpack nothing teaches you an exchange’s dynamics like actually trading on it. all the small nits, the microstructure quirks — you only find them by living in the product so what’s next? topping up with a fresh $100k and going deep on stock trading with Backpack Securities. public beta is live, v2 right around the corner, and i’ve been wanting to make this pivot for a while given everything happening on the equities side — AI, robotics, quantum, space time to run it back from $200k this time 😉🎒

Sting 🎒

71,464 просмотров • 1 месяц назад

Hermes Agent + Higgsfield Marketing Studio = AI UGC Content Factory I built a fully automated system inside Higgsfield that repurposes, localizes, and launches winning TikTok Shop content across hundreds of creator-style accounts. It's so effective it feels like running Facebook ads in 2008. No actors. No products in hand. No ghost creators. Just viral TikTok Shop sales - 24/7. The results speak louder than any pitch: • CPMs as low as $0.10 • 550+ cinematic, product-ready ads per day from a single prompt • 100 hooks tested in the time it used to take to test 10 • $100/mo replacing a $50k+ creative budget Here's the full pipeline - all native inside Higgsfield Marketing Studio: > Hermes Agent analyzes your product, scrapes Meta Ads + TikTok Ads, identifies winning content, and localizes every angle to your brand. > Seedance 2.0 turns data into AI UGC ads - captions, pacing, hooks, your website showcase, all auto-edited inside Higgsfield Marketing Studio. > AI UGC personas are spun up with realistic faces, voices, and personalities - cloned voiceovers in seconds. > Our phone farm pushes every finished video straight to TikTok Shop, daily, on autopilot. >No setup. No switching between five tools. Everything lives inside Higgsfield Marketing Studio. Here's how it actually runs: Hermes Agent researches the niche, scrapes winning TikTok Shop videos, and rebuilds them with fresh hooks, angles, and UGC visuals tailored to your brand. Agents create and post daily to affiliate accounts - fully automated. Then we activate the MPS (Multi-Platform Swarm): once a concept wins on TikTok Shop, Higgsfield deploys hundreds of AI Agents to flood the niche with variations that all drive back to our shot. Most brands are still paying $300–$500 per video. Testing 10 hooks costs $5,000 and takes three weeks. With this system, we test 100 hooks in the same timeframe - and the winners scale automatically. TikTok doesn't reward the best video. It rewards the brand that shows up the most - with content that converts. The brands automating content at scale will be the biggest winners of 2026.

Noah Frydberg | Tiktok Shop For Brands

27,037 просмотров • 3 месяцев назад