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Build your first AI agent with Claude Code (step by step) Most people's first "agent" is a chatbot they have to babysit. This one does a real job: the 40 minutes you lose every morning working out what needs you today. Here's the whole build in Claude Code, in... the desktop app and in the terminal: Dump everything on your plate and let Claude find the job that repeats. Let it interview you and write CLAUDE.md, the file it reads every time it starts. Know the difference: an automation repeats steps, an agent decides them. Write the scope: it reads, it never sends, it never deletes. Turn the job into a skill, written down once. Connect only the tools it needs (Gmail and Google Calendar). Set permissions: allow reading, ask before sending, deny deleting. Put it on a schedule, every weekday at 7. Then watch it for a week. When it gets something wrong, fix the skill, not the output. Everything on screen is real Claude Code output on made-up business data. Save this for when you build your first one. #aiagents #aiautomation #claude #aiemployeeshow more

Professor Glitch

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25,600 просмотров • 19 дней назад •via TikTok

Образование Наука и технологии #aiagents #aiautomation #claude #aiemployee

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How to put an AI agent to work this week: AI agents explained for beginners, n8n vs Claude Code How to put an AI agent to work this week, drawn start to finish: what an AI agent is, what it's made of, and which tool to build it in. AI agent vs chatbot vs automation: - An automation is a sprinkler on a timer. Six in the morning, every day, same water, even when it's raining. That's a workflow: same trigger, same steps. - A chatbot is a smart friend on the phone. Great advice, but you're still the one under the sink holding the wrench. - An AI agent is the handyman you let into the house. You hand over the job and he does the work, in a loop: goal, plan, act, check, repeat, until the job is done or he needs you. The four pieces of every AI agent you'd trust with real work: 1. The brain: the AI model inside Claude, ChatGPT or Gemini. It reads, reasons and picks the next step. 2. Context: instructions (the job sheet), memory (notes from last time) and knowledge (your price list, services and documents). This is the piece people skip, and it's why their agent writes like a stranger. 3. Tools: the keys you hand over, like your email, calendar and files. Only the keys this job needs. 4. Guardrails: house rules. Anything that leaves the house (an email, a payment, a deletion) waits for your approval. Human in the loop. One real example, end to end. The goal, in one sentence: follow up on today's client call. The AI agent reads the call notes in Google Drive, checks Google Calendar for an open slot (your client notes say she likes mornings), drafts the follow-up email in Gmail with the price sheet linked, and updates your client sheet in Google Sheets. Then it stops, so you can read it and hit send. n8n vs Claude Code, the doorbell and the desk: - n8n is the doorbell: a visual workflow automation tool that connects your apps and waits for a trigger. A call note lands in a Google Drive folder and the follow-up gets drafted, day or night. For the step that needs judgment, the n8n AI Agent node holds the same four pieces and runs the same loop. - Claude Code is the desk: an AI agent that works next to you, on your computer, in your files. It reads CLAUDE.md (the job sheet), uses skills (your steps written down once) and reaches Gmail and your calendar through MCP (the keys). - Doorbell jobs go in n8n: something happens, same steps, every time. Desk jobs go to Claude Code: messy, different every time, or living in your files. They work together, too: n8n has a built-in MCP server, so Claude Code can build n8n workflows for you. How to put an AI agent to work this week: 1. Pick one job you do every week that starts the same way (follow-ups, quote requests, the Monday report). 2. Write the context: one page with the job, how you like it done, and three good examples. 3. Hand it one key, drafts only. It reads and drafts, and nothing sends. 4. Two weeks of yeses. It drafts, you send, and every fix goes into that one page. That's your first agent: one job, one page, one key, two weeks of yeses. The only part left is the setup: n8n, Claude Code, and the keys wired into your real tools. I teach all of it inside my community, course by course, in that order. If you're interested, the link is in my profile. #claudecode #aiagents #n8n #aiautomation

Professor Glitch

18,500 просмотров • 29 дней назад

How Claude actually gets to know you (7 layers) Every new chat, Claude starts fresh. It only knows what's in front of it. So most people are talking to a stranger every morning. Here's how you change that, one layer at a time: 1. Memory: Claude keeps notes from your chats, and you can open them, read them and fix them. 2. A project: your instructions and your files in one place. Every chat inside it starts with all of it. 3. Skills: write each weekly job down once. Claude reads every skill's name and opens the one that matches. 4. Connectors: your email, calendar and drive, so "prep me for tomorrow" uses your real meetings. 5. Claude Code: a folder on your computer with a CLAUDE.md file. Your business, your rules. Then it makes the files and checks its own work. 6. Schedules: the morning brief is ready at 7. 7. A team: each job gets its own lane, its own tools, its own rules. Then the deep part: leads, sales, onboarding, support and invoicing as one system. One source of truth, events that start the next step, automations for fixed steps, an agent for the messy ones, and guardrails: logs, approvals, alerts. The people who get the most out of Claude are the ones who set it up. #aiagents #claudecode #aiautomation #aiemployee

How Claude actually gets to know you (7 layers) Every new chat, Claude starts fresh. It only knows what's in front of it. So most people are talking to a stranger every morning. Here's how you change that, one layer at a time: 1. Memory: Claude keeps notes from your chats, and you can open them, read them and fix them. 2. A project: your instructions and your files in one place. Every chat inside it starts with all of it. 3. Skills: write each weekly job down once. Claude reads every skill's name and opens the one that matches. 4. Connectors: your email, calendar and drive, so "prep me for tomorrow" uses your real meetings. 5. Claude Code: a folder on your computer with a CLAUDE.md file. Your business, your rules. Then it makes the files and checks its own work. 6. Schedules: the morning brief is ready at 7. 7. A team: each job gets its own lane, its own tools, its own rules. Then the deep part: leads, sales, onboarding, support and invoicing as one system. One source of truth, events that start the next step, automations for fixed steps, an agent for the messy ones, and guardrails: logs, approvals, alerts. The people who get the most out of Claude are the ones who set it up. #aiagents #claudecode #aiautomation #aiemployee

Professor Glitch

14,300 просмотров • 18 дней назад

You can turn any YouTube tutorial into a working Claude Code agent by having two AIs watch it separately. Install bradautomates/claude-video so Claude sees the frames and the transcript. Send the same link to Gemini @googlegemini, which watches it natively. Reconcile both reads into one spec that labels every line confirmed, single source, or conflict. You only check the conflicts. Hand it to skill-creator and it writes the agent. If you're the human: share this reel to Claude Code and watch it build. Comment "Youtube" for my full step-by-step guide. #claudecode #claude #ai #aiagents #aitools

You can turn any YouTube tutorial into a working Claude Code agent by having two AIs watch it separately. Install bradautomates/claude-video so Claude sees the frames and the transcript. Send the same link to Gemini @googlegemini, which watches it natively. Reconcile both reads into one spec that labels every line confirmed, single source, or conflict. You only check the conflicts. Hand it to skill-creator and it writes the agent. If you're the human: share this reel to Claude Code and watch it build. Comment "Youtube" for my full step-by-step guide. #claudecode #claude #ai #aiagents #aitools

Jens Heitmann

162,700 просмотров • 3 месяцев назад

HOLY F*CKING SH*T you waste 20 minutes every morning re-explaining your project to Claude like it has never heard of you, and Karpathy showed you the fix a year ago Andrej Karpathy, co-founder of OpenAI, posted one idea that pulled 16 million views: stop using AI to write code. use it to build a second brain You point Claude Code to a folder, drop any source in there (article, transcript, PDF) and Claude reads it, links it, and saves it into a living wiki of everything you know. it compounds like interest: the more you feed it, the sharper every answer gets Here is the gist: → install Obsidian, create a vault, open it in Claude Code → paste Karpathy's wiki prompt and tell Claude to build it → Claude creates 3 folders: raw for sources, wiki for its pages, CLAUDE.md that runs everything → drop any source into raw and say "ingest this" → ask anything across all of it, forever 5 minutes to set up. and you never open a blank Claude chat again the full step-by-step is in the article below bookmark this before you waste another monday

HOLY FCKING SHT you waste 20 minutes every morning re-explaining your project to Claude like it has never heard of you, and Karpathy showed you the fix a year ago Andrej Karpathy, co-founder of OpenAI, posted one idea that pulled 16 million views: stop using AI to write code. use it to build a second brain You point Claude Code to a folder, drop any source in there (article, transcript, PDF) and Claude reads it, links it, and saves it into a living wiki of everything you know. it compounds like interest: the more you feed it, the sharper every answer gets Here is the gist: → install Obsidian, create a vault, open it in Claude Code → paste Karpathy's wiki prompt and tell Claude to build it → Claude creates 3 folders: raw for sources, wiki for its pages, CLAUDE.md that runs everything → drop any source into raw and say "ingest this" → ask anything across all of it, forever 5 minutes to set up. and you never open a blank Claude chat again the full step-by-step is in the article below bookmark this before you waste another monday

mojesko

98,648 просмотров • 13 дней назад

How to create AI employees — start to finish, everything included The complete build of an AI employee, start to finish — the whole path in under four minutes. The agent underneath — every AI employee starts as an agent: a brain (the AI model), tools (real connections into your email, calendar, spreadsheets so it acts instead of only talking), and a loop (it works the job, checks itself, and keeps going until it's done). Feed the brain context and it works on YOUR business. The four upgrades that make it an employee — memory (corrections get written down and read back before every job — explain a thing once and it stays explained), permanent context (your world lives with it and changes as your business changes), skills (your way of doing a job, taught once, followed every time), and a schedule (an agent runs when you call it — an employee clocks in on its own, seven in the morning, inbox already sorted). The build tool — an AI coding assistant: Claude Code or Codex. That class of tool IS the agent machinery — it navigates your context, picks its next move, loops until the job is done, and carries memory between runs. You set it up in plain English, and when a piece you need exists nowhere, it writes that piece itself. The full assembly — pick one job, give it context, wire the tools, teach the skill, add memory, set the schedule. One rule built in: high-stakes moves wait for your yes; everything else runs around the clock. The ceiling — one employee becomes a pattern, patterns become a team, and the team becomes a department passing work to each other. This video is the skeleton of my entire curriculum — every step is a full course, taught from zero, step by step, about four months front to back. It's all inside my community. #aiemployee #aiagent #aiautomation

How to create AI employees — start to finish, everything included The complete build of an AI employee, start to finish — the whole path in under four minutes. The agent underneath — every AI employee starts as an agent: a brain (the AI model), tools (real connections into your email, calendar, spreadsheets so it acts instead of only talking), and a loop (it works the job, checks itself, and keeps going until it's done). Feed the brain context and it works on YOUR business. The four upgrades that make it an employee — memory (corrections get written down and read back before every job — explain a thing once and it stays explained), permanent context (your world lives with it and changes as your business changes), skills (your way of doing a job, taught once, followed every time), and a schedule (an agent runs when you call it — an employee clocks in on its own, seven in the morning, inbox already sorted). The build tool — an AI coding assistant: Claude Code or Codex. That class of tool IS the agent machinery — it navigates your context, picks its next move, loops until the job is done, and carries memory between runs. You set it up in plain English, and when a piece you need exists nowhere, it writes that piece itself. The full assembly — pick one job, give it context, wire the tools, teach the skill, add memory, set the schedule. One rule built in: high-stakes moves wait for your yes; everything else runs around the clock. The ceiling — one employee becomes a pattern, patterns become a team, and the team becomes a department passing work to each other. This video is the skeleton of my entire curriculum — every step is a full course, taught from zero, step by step, about four months front to back. It's all inside my community. #aiemployee #aiagent #aiautomation

Professor Glitch

12,600 просмотров • 2 месяцев назад

THIS IS ACTUAL F*CKING GOLD Anthropic just shared one of the best tricks for Claude Code. The idea: stop configuring Claude Code by hand. One prompt, 44 seconds, and your whole .claude/ folder writes itself. 7 files, 162 lines, 2 cents. you typed one line and wrote zero of them. You just launch Claude Code like this: claude --model opus "set up this repo: ..." here's the split: → 3 Haiku 5.5 agents scan the repo before a single file gets written → one reads the stack, one reads the npm scripts, one hunts for risky paths → Opus 5.5 takes those three summaries and writes the actual config → 7 files land: CLAUDE.md, 3 agents, permissions, a format hook and a /ship skill the part everyone gets wrong: they write CLAUDE.md from memory. a config written without reading the repo is a guess, and you live with that guess for months. here the risk scan came back with 5 dangerous paths and those went straight into the permissions file, so the agent is blocked from them before it ever runs once. the scripts scan found 5 npm scripts, and the agents got wired to the ones that actually exist in this repo instead of generic placeholders. one prompt from you, 7 files from it, 0 lines written by hand. Haiku reads. Opus writes. You commit. JEV engineering is the same move one layer down: 1,867 forks this run - which file, which agent, allow or ask - resolved in code at 0.97 sharpness, and the split ones (0.59 on "allow or ask") come back to you instead of being guessed the full tree ▸ you paste one prompt describing the setup you want ▸ 3 Haiku 5.5 agents scan stack, scripts and risky paths in parallel ▸ every agent returns a summary, never raw files ▸ Opus 5.5 writes CLAUDE.md, the agents, permissions, the hook and the skill ▸ anything touching permissions comes back to you before it is written ▸ JEV resolves micro-forks in code and escalates only the split ones paste the tree and this prompt into Claude Code ↓ "Set up this repo for me: 1. First scan it with 3 Haiku 5.5 agents in parallel: one reads the stack and manifests, one reads the build and npm scripts, one finds paths that are dangerous to touch. 2. Each agent returns a summary only, never raw file contents. 3. Then write CLAUDE.md, 3 subagents, a permissions file, a format hook and a /ship skill, all based on what the scan actually found, not on defaults. 4. Every risky path from the scan goes into the deny list before anything runs. 5. Ask me before writing anything that grants permissions. Show me every file as a diff first. No writes until I say go." ↳ save it, this is the first thing you run in every new repo.

THIS IS ACTUAL F*CKING GOLD Anthropic just shared one of the best tricks for Claude Code. The idea: stop configuring Claude Code by hand. One prompt, 44 seconds, and your whole .claude/ folder writes itself. 7 files, 162 lines, 2 cents. you typed one line and wrote zero of them. You just launch Claude Code like this: claude --model opus "set up this repo: ..." here's the split: → 3 Haiku 5.5 agents scan the repo before a single file gets written → one reads the stack, one reads the npm scripts, one hunts for risky paths → Opus 5.5 takes those three summaries and writes the actual config → 7 files land: CLAUDE.md, 3 agents, permissions, a format hook and a /ship skill the part everyone gets wrong: they write CLAUDE.md from memory. a config written without reading the repo is a guess, and you live with that guess for months. here the risk scan came back with 5 dangerous paths and those went straight into the permissions file, so the agent is blocked from them before it ever runs once. the scripts scan found 5 npm scripts, and the agents got wired to the ones that actually exist in this repo instead of generic placeholders. one prompt from you, 7 files from it, 0 lines written by hand. Haiku reads. Opus writes. You commit. JEV engineering is the same move one layer down: 1,867 forks this run - which file, which agent, allow or ask - resolved in code at 0.97 sharpness, and the split ones (0.59 on "allow or ask") come back to you instead of being guessed the full tree ▸ you paste one prompt describing the setup you want ▸ 3 Haiku 5.5 agents scan stack, scripts and risky paths in parallel ▸ every agent returns a summary, never raw files ▸ Opus 5.5 writes CLAUDE.md, the agents, permissions, the hook and the skill ▸ anything touching permissions comes back to you before it is written ▸ JEV resolves micro-forks in code and escalates only the split ones paste the tree and this prompt into Claude Code ↓ "Set up this repo for me: 1. First scan it with 3 Haiku 5.5 agents in parallel: one reads the stack and manifests, one reads the build and npm scripts, one finds paths that are dangerous to touch. 2. Each agent returns a summary only, never raw file contents. 3. Then write CLAUDE.md, 3 subagents, a permissions file, a format hook and a /ship skill, all based on what the scan actually found, not on defaults. 4. Every risky path from the scan goes into the deny list before anything runs. 5. Ask me before writing anything that grants permissions. Show me every file as a diff first. No writes until I say go." ↳ save it, this is the first thing you run in every new repo.

Sprytix

25,468 просмотров • 21 дней назад

Why your AI gets dumber the longer you chat (context rot): the one Claude Code file, plus one habit, that fixes it How context rot works: 1. Everything in your chat sits in the AI's working memory, the context window: every message, every file it opened, every answer it gave. The model reads through all of it before every reply. 2. Anthropic, the company behind Claude, says the more tokens you pile into the context window, the worse the model gets at recalling any one thing in it. They call it an attention budget, and every new token spends a little of it. 3. When the window fills up, Claude Code compacts: it replaces the conversation with a summary. If a rule only lived in the chat, it can get lost in that summary. The fix is one file, CLAUDE.md, plus one habit. 4. CLAUDE.md is a plain text file in your project folder. Claude Code reads it at the start of every session, and after compaction it re-reads it from the file. Think of it as a sign bolted above the whiteboard: wipe the board all you want, the sign stays. 5. How to create a CLAUDE.md: open Claude Code in your project folder and type /init. It writes a first draft. Then add what it can't guess: who you are, who the client is, and your rules ("never change a headline without asking", "prices come from column D of the Google Sheet", "dates are day, month, year"). 6. Keep CLAUDE.md short. Anthropic's Claude Code guide says to aim for under 200 lines, because a bloated file gets ignored too. For every line, ask: would it make a mistake without this? If not, cut it. The other half of the fix is how you work: 7. One job, one session. Type /clear when you switch jobs: the board's wiped, and the sign (CLAUDE.md) is still up. 8. If you've corrected the AI twice on the same thing, skip round three in capitals. Clear it, put the rule in CLAUDE.md, and start again. This is context engineering for people who don't code: an AI assistant that remembers your business rules, your clients and your formats, for client work, reports, content, spreadsheets and proposals, whether you're a freelancer, an agency or a small business. #claudecode #aiagents #contextengineering #learnai

Why your AI gets dumber the longer you chat (context rot): the one Claude Code file, plus one habit, that fixes it How context rot works: 1. Everything in your chat sits in the AI's working memory, the context window: every message, every file it opened, every answer it gave. The model reads through all of it before every reply. 2. Anthropic, the company behind Claude, says the more tokens you pile into the context window, the worse the model gets at recalling any one thing in it. They call it an attention budget, and every new token spends a little of it. 3. When the window fills up, Claude Code compacts: it replaces the conversation with a summary. If a rule only lived in the chat, it can get lost in that summary. The fix is one file, CLAUDE.md, plus one habit. 4. CLAUDE.md is a plain text file in your project folder. Claude Code reads it at the start of every session, and after compaction it re-reads it from the file. Think of it as a sign bolted above the whiteboard: wipe the board all you want, the sign stays. 5. How to create a CLAUDE.md: open Claude Code in your project folder and type /init. It writes a first draft. Then add what it can't guess: who you are, who the client is, and your rules ("never change a headline without asking", "prices come from column D of the Google Sheet", "dates are day, month, year"). 6. Keep CLAUDE.md short. Anthropic's Claude Code guide says to aim for under 200 lines, because a bloated file gets ignored too. For every line, ask: would it make a mistake without this? If not, cut it. The other half of the fix is how you work: 7. One job, one session. Type /clear when you switch jobs: the board's wiped, and the sign (CLAUDE.md) is still up. 8. If you've corrected the AI twice on the same thing, skip round three in capitals. Clear it, put the rule in CLAUDE.md, and start again. This is context engineering for people who don't code: an AI assistant that remembers your business rules, your clients and your formats, for client work, reports, content, spreadsheets and proposals, whether you're a freelancer, an agency or a small business. #claudecode #aiagents #contextengineering #learnai

Professor Glitch

12,200 просмотров • 28 дней назад

How to build an AI employee inside Claude Code (the whole picture) Most people think an AI employee is some complicated app. Under the hood, it's Claude Code plus a folder of plain text files. Here's the whole picture, using Quill, the employee who runs my Google Workspace. Profile: who she is, what she can do on her own, and when she has to ask first (money, contracts, first-time contacts). Context (CLAUDE.md): the file Claude Code reads first every session. It points her to how I write, who my clients are, and what the business does. Skills (SKILL.md): plain-English playbooks. The name and one-line description tell Claude when to use one; the steps run like a checklist. Tools: connectors give her hands in Gmail, Sheets, Calendar and Drive, through MCP or a small command-line app. Schedule: 9 AM triage, then an approvals check every 30 minutes. Memory: every correction becomes a standing rule she reads before drafting, so my edits get smaller every week. Team: when a new client wants a proposal, Quill hands it to Atlas, gets the PDF back and attaches it to the draft, and it still waits for my approval. Claude Code is the brain that reads all of it. You're the boss who approves. #aiemployee #aiagent #aiautomation #claudecode

Professor Glitch

15,100 просмотров • 1 месяц назад

There's a built-in agent inside Claude Code you can invoke just by telling Claude to use the claude-code-guide agent Save this... you'll need it It's not a local file in your project. It's a built-in subagent defined in Claude Code's system itself. It answers questions about Claude Code CLI, the Agent SDK, and the Claude API. It uses Glob, Grep, Read, WebFetch, and WebSearch, but can't edit or write files. Its only job is to answer questions.

There's a built-in agent inside Claude Code you can invoke just by telling Claude to use the claude-code-guide agent Save this... you'll need it It's not a local file in your project. It's a built-in subagent defined in Claude Code's system itself. It answers questions about Claude Code CLI, the Agent SDK, and the Claude API. It uses Glob, Grep, Read, WebFetch, and WebSearch, but can't edit or write files. Its only job is to answer questions.

Daniel San

57,445 просмотров • 8 месяцев назад

Claude Code doesn't replace n8n. Here's one project built with both People think Claude Code replaces n8n. So here's one real project: a returns desk for a small online shop, built with both. Step 1: Claude Code builds the app. The owner says one sentence ("Build me a returns page"). Claude Code does three things: It reads CLAUDE.md, the shop's handbook of name, colours and rules, which loads every session. It pulls the refund-policy skill. Skills are loaded only when they're needed. It writes the code, hits an error, fixes it, and ships a real returns page. Step 2: n8n wires it into the business. Every return fires a webhook, and the same route runs every time: the label goes out through Gmail a row is added to the spreadsheet a note is posted in Slack the refund goes through Stripe when the parcel is scanned back in Every run is logged, and it runs 24/7. Step 3: a routine does the thinking. Every night at 11, a Claude Code routine runs in Anthropic's cloud with the laptop closed. It reads the day's returns, spots that 6 of 9 mention the same seam, and writes the owner a report. The handoffs: Claude Code wrote the n8n workflow, and n8n calls Claude when a return doesn't fit any route. Claude Code builds and thinks. n8n runs the same routes all day. Together they run the business. #claudecode #aiautomation #aiagent #n8n

Claude Code doesn't replace n8n. Here's one project built with both People think Claude Code replaces n8n. So here's one real project: a returns desk for a small online shop, built with both. Step 1: Claude Code builds the app. The owner says one sentence ("Build me a returns page"). Claude Code does three things: It reads CLAUDE.md, the shop's handbook of name, colours and rules, which loads every session. It pulls the refund-policy skill. Skills are loaded only when they're needed. It writes the code, hits an error, fixes it, and ships a real returns page. Step 2: n8n wires it into the business. Every return fires a webhook, and the same route runs every time: the label goes out through Gmail a row is added to the spreadsheet a note is posted in Slack the refund goes through Stripe when the parcel is scanned back in Every run is logged, and it runs 24/7. Step 3: a routine does the thinking. Every night at 11, a Claude Code routine runs in Anthropic's cloud with the laptop closed. It reads the day's returns, spots that 6 of 9 mention the same seam, and writes the owner a report. The handoffs: Claude Code wrote the n8n workflow, and n8n calls Claude when a return doesn't fit any route. Claude Code builds and thinks. n8n runs the same routes all day. Together they run the business. #claudecode #aiautomation #aiagent #n8n

Professor Glitch

10,200 просмотров • 1 месяц назад

install these before your next long Claude Code session if your Opus 5.5 bill hurts and you don’t know where to start, copy this: claude-code-router: sits in front of Claude Code and sends each request to the cheapest model that can do it. Haiku does the grep, Opus only gets the hard part. 37k stars rtk: shrinks test, build and git output before the model sees it. one binary, up to 90% less bash output in your context. 83k stars claude-mem: remembers what happened in your past sessions and feeds back only the relevant part, so you stop paying to re-explain your project every morning. 100k stars context-mode: a huge tool output goes into a local database instead of your context window, and Claude pulls out only the lines it needs. 18k stars caveman: makes Claude answer in short telegraphic sentences. code stays identical, and output is the expensive side on Opus 5.5 ($20 per million). 51k stars token-optimizer: a local dashboard that shows where your tokens actually went, and keeps your work alive across compactions. 1.9k stars token-savior: replaces whole-file reads with symbol lookups, so Claude reads the function and not the 2,000 lines around it code-review-graph: maps your repo as a graph and gives Claude only the code connected to the change you’re reviewing jev-ultrafast: a browser agent where Jev picks every click, and a text model wakes up only when something has to be typed. 16,758 stars none of them makes Opus smarter. every one stops it from paying for work it never needed to do the full setup with scripts is in the article. do the measuring step first, so you know what you actually saved

install these before your next long Claude Code session if your Opus 5.5 bill hurts and you don’t know where to start, copy this: claude-code-router: sits in front of Claude Code and sends each request to the cheapest model that can do it. Haiku does the grep, Opus only gets the hard part. 37k stars rtk: shrinks test, build and git output before the model sees it. one binary, up to 90% less bash output in your context. 83k stars claude-mem: remembers what happened in your past sessions and feeds back only the relevant part, so you stop paying to re-explain your project every morning. 100k stars context-mode: a huge tool output goes into a local database instead of your context window, and Claude pulls out only the lines it needs. 18k stars caveman: makes Claude answer in short telegraphic sentences. code stays identical, and output is the expensive side on Opus 5.5 ($20 per million). 51k stars token-optimizer: a local dashboard that shows where your tokens actually went, and keeps your work alive across compactions. 1.9k stars token-savior: replaces whole-file reads with symbol lookups, so Claude reads the function and not the 2,000 lines around it code-review-graph: maps your repo as a graph and gives Claude only the code connected to the change you’re reviewing jev-ultrafast: a browser agent where Jev picks every click, and a text model wakes up only when something has to be typed. 16,758 stars none of them makes Opus smarter. every one stops it from paying for work it never needed to do the full setup with scripts is in the article. do the measuring step first, so you know what you actually saved

rvaniaaa

24,787 просмотров • 1 месяц назад

I genuinely don't understand why everyone isn't using this yet. Andrej Karpathy, OpenAI co-founder, posted a simple idea that went massively viral: Stop using AI to write code. Use it to build a second brain. You point Claude Code at a folder. Drop in any source: an article, a transcript, a PDF. Claude reads it, links it, files it into a living wiki of everything you know. It compounds like interest. The more you feed it, the smarter it gets. Here's the whole thing: 1) Install Obsidian 2) Create a vault 3) Open it in Claude Code 4) Paste Karpathy's wiki idea and tell Claude to build it 5) Claude makes three folders: - raw (for sources) - wiki (for its pages) - CLAUDE. md (that runs it) 6) Drop any source into raw and say: "ingest this" 7) Ask questions across everything, forever Five minutes to set up and you never start from a blank chat again. Full step by step guide below.

I genuinely don't understand why everyone isn't using this yet. Andrej Karpathy, OpenAI co-founder, posted a simple idea that went massively viral: Stop using AI to write code. Use it to build a second brain. You point Claude Code at a folder. Drop in any source: an article, a transcript, a PDF. Claude reads it, links it, files it into a living wiki of everything you know. It compounds like interest. The more you feed it, the smarter it gets. Here's the whole thing: 1) Install Obsidian 2) Create a vault 3) Open it in Claude Code 4) Paste Karpathy's wiki idea and tell Claude to build it 5) Claude makes three folders: - raw (for sources) - wiki (for its pages) - CLAUDE. md (that runs it) 6) Drop any source into raw and say: "ingest this" 7) Ask questions across everything, forever Five minutes to set up and you never start from a blank chat again. Full step by step guide below.

CyrilXBT

332,891 просмотров • 4 месяцев назад

This is getting out of hand: Claude Fable 5.2 can now take any gadget apart from one picture and nobody is talking about it. I gave it one picture of a PS5 controller and got back one that splits open part by part in 24 seconds. What made it work is teardown, a free open-source skill for Claude Code (3,000+ stars on GitHub) that makes Claude build the inside first. Why model a controller by hand for a week when Claude can write every part as code? Here is the workflow: from that one picture Claude writes the motion as math before it draws a single part, so every panel reads the same numbers as the model. It renders a still at every beat and fixes what it finds, then records the tour at 60 fps: the touchpad lifts, both sticks come out on their gimbals, the motor and gears behind L2 and R2 slide out and trigger force jumps from 30% to 78% the second push-back switches on. Step-by-step setup: 1. Install teardown with one npx line 2. Open Claude Code and type /teardown 3. Give it one picture of the thing you want to see inside 4. Let it check every still before it films 5. Record the tour and watch it come apart It runs inside Claude Code, so you'll never keyframe a teardown by hand again. The full guide and every prompt are in the article below.

This is getting out of hand: Claude Fable 5.2 can now take any gadget apart from one picture and nobody is talking about it. I gave it one picture of a PS5 controller and got back one that splits open part by part in 24 seconds. What made it work is teardown, a free open-source skill for Claude Code (3,000+ stars on GitHub) that makes Claude build the inside first. Why model a controller by hand for a week when Claude can write every part as code? Here is the workflow: from that one picture Claude writes the motion as math before it draws a single part, so every panel reads the same numbers as the model. It renders a still at every beat and fixes what it finds, then records the tour at 60 fps: the touchpad lifts, both sticks come out on their gimbals, the motor and gears behind L2 and R2 slide out and trigger force jumps from 30% to 78% the second push-back switches on. Step-by-step setup: 1. Install teardown with one npx line 2. Open Claude Code and type /teardown 3. Give it one picture of the thing you want to see inside 4. Let it check every still before it films 5. Record the tour and watch it come apart It runs inside Claude Code, so you'll never keyframe a teardown by hand again. The full guide and every prompt are in the article below.

Nyxera

35,505 просмотров • 1 день назад

This is f*cking insane. Former Google CEO Eric Schmidt, the man who ran Google for 10 years: "If you really want to make money, it's actually easy, found an agentic AI company, I mean build an agent to do something If you build a better agent than anyone else, you can probably build one incredible company and own it yourself" In 27 seconds, he explains why the next year or two is the agentic period, and why the window won't stay open Prompts → Claude Code → Memory → Skills → MCP → A Company You Own Yourself Save this before it disappears from your feed Everything below is free: Agent architecture Claude Code 101 Claude Code in action Prompt engineering Interactive prompt course Claude.md + memory Skills MCP Routines Claude Code ultimate guide Awesome Claude Code Anthropic academy Official Claude Code docs All of this costs $0 95% will spend the agentic period scrolling AI threads, the 5% who ship agents will own the companies that come out of it Bookmark it and start with the first link tonight Then read how to build an agent that actually does the job in the harness engineering guide below ↓

This is f*cking insane. Former Google CEO Eric Schmidt, the man who ran Google for 10 years: "If you really want to make money, it's actually easy, found an agentic AI company, I mean build an agent to do something If you build a better agent than anyone else, you can probably build one incredible company and own it yourself" In 27 seconds, he explains why the next year or two is the agentic period, and why the window won't stay open Prompts → Claude Code → Memory → Skills → MCP → A Company You Own Yourself Save this before it disappears from your feed Everything below is free: Agent architecture Claude Code 101 Claude Code in action Prompt engineering Interactive prompt course Claude.md + memory Skills MCP Routines Claude Code ultimate guide Awesome Claude Code Anthropic academy Official Claude Code docs All of this costs $0 95% will spend the agentic period scrolling AI threads, the 5% who ship agents will own the companies that come out of it Bookmark it and start with the first link tonight Then read how to build an agent that actually does the job in the harness engineering guide below ↓

godsystem

1,515,966 просмотров • 9 дней назад

Claude Code sugarcoats everything. You know who doesn't? Eastern European developers. Introducing the Marko skill - call Marko at any time, and he will review your code - and believe me - he will find something wrong with it. And, staying very on brand - he won't tell you how to fix it. He has one job, and one job only - to tell your agent that the code sucks. Skill repo in the thread 👇

Julian Galluzzo

89,048 просмотров • 6 месяцев назад

🚨 SOMEONE LEAKED THE PROMPT THAT MAKES CLAUDE CODE CREATE ITS OWN SKILLS AND WORK BETTER EVERY DAY WITHOUT YOU TOUCHING ANYTHING No programming. Just paste. A single prompt does it all: Time needed: 2 minutes Actions: copy and paste into Claude Code The mistake 90% of people make with Claude: explaining the same thing to it every day. The same tone, the same steps, the same corrections. And the next day it starts from scratch again. → Detects what you repeat: reviews your project and asks you what tasks you do every week → Creates a skill for each one: instructions, templates, and examples that Claude loads only when it needs them → Tests them before giving them to you: runs each skill with a real case and fixes it if it fails → Learns from your corrections: every time you correct something, it updates the skill so it doesn't repeat the error → Zero code: you tell it what you do and Claude builds its own library of skills Before, this meant writing manuals, templates, and processes for weeks. Now it's just Ctrl+V. Save it before they delete it 🔖 Follow Tomcruise AI for more...

🚨 SOMEONE LEAKED THE PROMPT THAT MAKES CLAUDE CODE CREATE ITS OWN SKILLS AND WORK BETTER EVERY DAY WITHOUT YOU TOUCHING ANYTHING No programming. Just paste. A single prompt does it all: Time needed: 2 minutes Actions: copy and paste into Claude Code The mistake 90% of people make with Claude: explaining the same thing to it every day. The same tone, the same steps, the same corrections. And the next day it starts from scratch again. → Detects what you repeat: reviews your project and asks you what tasks you do every week → Creates a skill for each one: instructions, templates, and examples that Claude loads only when it needs them → Tests them before giving them to you: runs each skill with a real case and fixes it if it fails → Learns from your corrections: every time you correct something, it updates the skill so it doesn't repeat the error → Zero code: you tell it what you do and Claude builds its own library of skills Before, this meant writing manuals, templates, and processes for weeks. Now it's just Ctrl+V. Save it before they delete it 🔖 Follow Tomcruise AI for more...

Tomcruise AI

38,809 просмотров • 5 дней назад

How to make AI run your business AI running your business doesn't mean you disappear. It means the follow-ups, the reports, the replies and the reminders get done every day without you pushing them. You stay the owner. You stop being the bottleneck. The six pieces, in the order you build them: 1. Context: a folder of plain documents (what you sell, your prices, your customers, how you talk, what needs your OK, your top 10 questions). Every AI job reads it first. 2. Skills: every job you do more than twice, written down once, step by step. 3. Memory: a running record the AI reads and updates, so tomorrow it knows what happened today. 4. Tools: email, calendar, spreadsheets, invoicing, and you decide exactly what it may touch. 5. Schedules: every morning at 7, every Monday, every 3-day-old quote. It just happens. 6. A board: what the AI did, what waits for your yes, what got stuck. The rule: money, contracts and angry customers wait for you. AI drafts. You decide. Start with context, one skill, one job, then put that job on a schedule. Run it two weeks, fix what breaks, add the next one. #aiagents #aiautomation #aiemployee

How to make AI run your business AI running your business doesn't mean you disappear. It means the follow-ups, the reports, the replies and the reminders get done every day without you pushing them. You stay the owner. You stop being the bottleneck. The six pieces, in the order you build them: 1. Context: a folder of plain documents (what you sell, your prices, your customers, how you talk, what needs your OK, your top 10 questions). Every AI job reads it first. 2. Skills: every job you do more than twice, written down once, step by step. 3. Memory: a running record the AI reads and updates, so tomorrow it knows what happened today. 4. Tools: email, calendar, spreadsheets, invoicing, and you decide exactly what it may touch. 5. Schedules: every morning at 7, every Monday, every 3-day-old quote. It just happens. 6. A board: what the AI did, what waits for your yes, what got stuck. The rule: money, contracts and angry customers wait for you. AI drafts. You decide. Start with context, one skill, one job, then put that job on a schedule. Run it two weeks, fix what breaks, add the next one. #aiagents #aiautomation #aiemployee

Professor Glitch

10,600 просмотров • 25 дней назад

instead of reading a 3,000-word article, set up a Claude Research Agent in 2 minutes it reads the internet for you every morning and sends a briefing before you wake up 1. Open Claude → Scheduled Tasks 2. Click "Create with Claude" 3. Tell it what to track and when to send that's it.

instead of reading a 3,000-word article, set up a Claude Research Agent in 2 minutes it reads the internet for you every morning and sends a briefing before you wake up 1. Open Claude → Scheduled Tasks 2. Click "Create with Claude" 3. Tell it what to track and when to send that's it.

Avid

16,279 просмотров • 5 месяцев назад

I still don't understand why everyone is not using this yet. Thanks to it, a year ago I increased my income to 15,000 dollars a month Andrey Karpathy, co-founder of OpenAI, published a simple idea that got 25 million views: stop using AI to write code, use it to build a second brain You point Claude Code to a folder, drop any source in there (an article, transcript, PDF) and Claude reads it, links it, and saves it into a living wiki of everything you know. It compounds like interest: the more you feed it, the smarter it gets Here is the gist: Install Obsidian, create a vault, open it in Claude Code Paste the file with Karpathy's wiki idea and tell Claude to build it Claude creates three folders: raw for sources, wiki for its pages, CLAUDE which runs everything Drop any source into raw and say ingest this Ask questions across everything, forever 5 minutes to set up, and you never start with an empty chat again The full instructions can be found in the article below

I still don't understand why everyone is not using this yet. Thanks to it, a year ago I increased my income to 15,000 dollars a month Andrey Karpathy, co-founder of OpenAI, published a simple idea that got 25 million views: stop using AI to write code, use it to build a second brain You point Claude Code to a folder, drop any source in there (an article, transcript, PDF) and Claude reads it, links it, and saves it into a living wiki of everything you know. It compounds like interest: the more you feed it, the smarter it gets Here is the gist: Install Obsidian, create a vault, open it in Claude Code Paste the file with Karpathy's wiki idea and tell Claude to build it Claude creates three folders: raw for sources, wiki for its pages, CLAUDE which runs everything Drop any source into raw and say ingest this Ask questions across everything, forever 5 minutes to set up, and you never start with an empty chat again The full instructions can be found in the article below

Bober_smart

98,106 просмотров • 5 дней назад

$THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this$

THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this

Yarchi

56,568 просмотров • 5 месяцев назад