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Watch git diff while the code is changing! 🤯 👁️ livediff — A real-time diff viewer for the terminal 💯 Watch file changes live as generators, formatters, migrations & refactors modify your code 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #ratatui #tui #git #terminal #devtools #opensource

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Man, this looks beautiful 😍 🧲 superseedr — A full-featured BitTorrent client for the terminal. 🌐 Supports multi-torrent downloads, DHT, PEX, magnet links & rarest-first piece selection. 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #ratatui #tui #torrent #bittorrent #p2p #terminal #opensource
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Man, this looks beautiful 😍 🧲 superseedr — A full-featured BitTorrent client for the terminal. 🌐 Supports multi-torrent downloads, DHT, PEX, magnet links & rarest-first piece selection. 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #ratatui #tui #torrent #bittorrent #p2p #terminal #opensource

Orhun Parmaksız 👾

19,851 görüntüleme • 10 ay önce

Wow, I found a smart way to bookmark code! 🤯 🔖 codemark — Structural bookmarks that survive refactors, renames & reformatting. 🌳 Capture the semantic structure of what you marked via tree-sitter 🐀 Includes a TUI for exploring the codebase! 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #ratatui #tui #coding #bookmark #semantic #devtools #programming
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Wow, I found a smart way to bookmark code! 🤯 🔖 codemark — Structural bookmarks that survive refactors, renames & reformatting. 🌳 Capture the semantic structure of what you marked via tree-sitter 🐀 Includes a TUI for exploring the codebase! 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #ratatui #tui #coding #bookmark #semantic #devtools #programming

Orhun Parmaksız 👾

11,202 görüntüleme • 1 ay önce

New version of Ratty is out! 🎉🧀 🐀 Ratty — A GPU-rendered terminal emulator with inline 3D graphics. 💯 Now supports SSH-friendly object payloads, transform control and keyboard scrollback navigation! 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #terminal #ratty #ratatui #opensource
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New version of Ratty is out! 🎉🧀 🐀 Ratty — A GPU-rendered terminal emulator with inline 3D graphics. 💯 Now supports SSH-friendly object payloads, transform control and keyboard scrollback navigation! 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #terminal #ratty #ratatui #opensource

Orhun Parmaksız 👾

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This is gold if you're using async Rust 💯 🌀 channels-console — A TUI dashboard for inspecting std/tokio/futures/crossbeam channels. 📊 Watch messages, queue depth, throughput & memory usage live. 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #ratatui #tui #async #concurrency #tokio #debugging
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This is gold if you're using async Rust 💯 🌀 channels-console — A TUI dashboard for inspecting std/tokio/futures/crossbeam channels. 📊 Watch messages, queue depth, throughput & memory usage live. 🦀 Written in Rust & built with Ratatui ⭐ GitHub: #rustlang #ratatui #tui #async #concurrency #tokio #debugging

Orhun Parmaksız 👾

22,300 görüntüleme • 9 ay önce

cursor can now read ur terminal in real time! we built a subagent to watch logs, training runs, security alerts, and step in to patch code with the cursor-cli
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cursor can now read ur terminal in real time! we built a subagent to watch logs, training runs, security alerts, and step in to patch code with the cursor-cli

rajan agarwal

119,565 görüntüleme • 11 ay önce

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.
0:18

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

BuBBliK

200,402 görüntüleme • 2 ay önce

Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇
0:16

Claude Code Desktop now opens a new window for each session This makes it much easier to visualize multiple Claude Code agents running in parallel My current stack depends on the task: - Ghostty: when starting a project. Bash commands, git, env variables, provider connections. All manual through the terminal with a Claude panel running alongside. - Claude Code Desktop: once everything is configured. GitHub connected, CLAUDE.md, Skills, subagents and Hooks ready. Claude Code runs on its own, no more terminal setup, just panels running and outputs to review. - VSCode: when I need to review code by hand. I use it less and less, but there are moments where I have to confirm Claude got it right. I usually open the Claude extension inside VSCode, but it lacks most of the CLI features so it's limited Solid update. Worth trying once your workflows are already set up 👇

Daniel San

38,806 görüntüleme • 3 ay önce

Built a native macOS viewer for ledger plain-text accounting file format. Most expense tracking apps are built around lock-in. Proprietary formats, mandatory accounts, servers you don't control. When their VC funding dries up, they shut down or pivot, and you start over. Plain-text accounting takes the opposite approach: your finances live in a .ledger file. Open it in vim. Query it with awk. Put it in git and get a full audit trail of every change you've ever made. It's just a plain text file. Ledge is just a lens over that file. Fast, native, no cloud. Following kepano 's file over app philosophy
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Built a native macOS viewer for ledger plain-text accounting file format. Most expense tracking apps are built around lock-in. Proprietary formats, mandatory accounts, servers you don't control. When their VC funding dries up, they shut down or pivot, and you start over. Plain-text accounting takes the opposite approach: your finances live in a .ledger file. Open it in vim. Query it with awk. Put it in git and get a full audit trail of every change you've ever made. It's just a plain text file. Ledge is just a lens over that file. Fast, native, no cloud. Following kepano 's file over app philosophy

Karan Sharma

26,304 görüntüleme • 5 ay önce

Another WTF moment. A developer just open-sourced a coding agent harness that boots 245x faster than Claude Code. It's called jcode. You launch it and the first frame renders in 14 milliseconds. Claude Code takes 3,436. One active session uses 27.8 MB of RAM. Claude Code uses 386.6. Run ten sessions in parallel and jcode holds at 117 MB while OpenCode swells to 3.2 GB. Each agent has a semantic memory graph instead of a scratchpad. Every turn gets embedded as a vector. The graph is queried on every turn for related memories, and a sideagent verifies the hits before injecting them into context. Consolidation runs in the background to check for stale or conflicting facts. No manual /remember calls. No token burn on lookup tools. The provider list is 30+ deep. Claude, ChatGPT, Gemini, GitHub Copilot, Azure, OpenRouter, DeepSeek, Groq, Mistral, Perplexity, Fireworks, Ollama, LM Studio, and any OpenAI-compatible endpoint you point it at. Ran out of tokens on your first ChatGPT Pro sub? /account swaps to the second. Then there's Swarm. Spawn two agents in the same repo and the server manages them. When agent A edits a file agent B has been reading, agent B gets pinged and can check the diff. Agents can DM each other, broadcast to the room, or spawn their own worker teams for parallel tasks. Groups, channels, and completion statuses are handled automatically. The UI has live side panels that render mermaid diagrams inline. To make it fast, the author wrote a Rust mermaid renderer 1800x faster than the JavaScript one, then wrote a custom terminal called Handterm because no existing terminal could do smooth partial-line scrolling. Self-dev mode is where it gets wild. Tell your agent to enter self-dev and it starts editing jcode's own source code, rebuilds the binary, reloads it live, and keeps working across your existing sessions. You can also resume broken sessions from Claude Code, Codex, OpenCode, or pi directly inside jcode. Anthropic's cache goes cold at the 5-minute mark and you're staring down a big cache miss on your next turn? The UI warns you before you spend the tokens. Written in Rust. MIT licensed. Runs on macOS, Windows, Linux, and Termux. Sitting at 11.2k stars with a native iOS app coming.
0:17

Another WTF moment. A developer just open-sourced a coding agent harness that boots 245x faster than Claude Code. It's called jcode. You launch it and the first frame renders in 14 milliseconds. Claude Code takes 3,436. One active session uses 27.8 MB of RAM. Claude Code uses 386.6. Run ten sessions in parallel and jcode holds at 117 MB while OpenCode swells to 3.2 GB. Each agent has a semantic memory graph instead of a scratchpad. Every turn gets embedded as a vector. The graph is queried on every turn for related memories, and a sideagent verifies the hits before injecting them into context. Consolidation runs in the background to check for stale or conflicting facts. No manual /remember calls. No token burn on lookup tools. The provider list is 30+ deep. Claude, ChatGPT, Gemini, GitHub Copilot, Azure, OpenRouter, DeepSeek, Groq, Mistral, Perplexity, Fireworks, Ollama, LM Studio, and any OpenAI-compatible endpoint you point it at. Ran out of tokens on your first ChatGPT Pro sub? /account swaps to the second. Then there's Swarm. Spawn two agents in the same repo and the server manages them. When agent A edits a file agent B has been reading, agent B gets pinged and can check the diff. Agents can DM each other, broadcast to the room, or spawn their own worker teams for parallel tasks. Groups, channels, and completion statuses are handled automatically. The UI has live side panels that render mermaid diagrams inline. To make it fast, the author wrote a Rust mermaid renderer 1800x faster than the JavaScript one, then wrote a custom terminal called Handterm because no existing terminal could do smooth partial-line scrolling. Self-dev mode is where it gets wild. Tell your agent to enter self-dev and it starts editing jcode's own source code, rebuilds the binary, reloads it live, and keeps working across your existing sessions. You can also resume broken sessions from Claude Code, Codex, OpenCode, or pi directly inside jcode. Anthropic's cache goes cold at the 5-minute mark and you're staring down a big cache miss on your next turn? The UI warns you before you spend the tokens. Written in Rust. MIT licensed. Runs on macOS, Windows, Linux, and Termux. Sitting at 11.2k stars with a native iOS app coming.

Brady Long

205,781 görüntüleme • 28 gün önce

you don't need to re-explain your codebase's architecture to your agent every session. most tools stop at telling you what broke. sentrux is a real-time architectural sensor, it watches your codebase as a live treemap and turns file structure and dependencies into one continuous quality score. the loop is simple: codebase > agent scans structure and dependencies > sentrux scores 5 root cause metrics into one signal > agent sees exactly where risk concentrates > next session starts from a live map instead of a blind grep the binary carries zero built-in language knowledge, all 52 languages live in plugin.toml and tags.scm query files, so a new language needs zero rust code. small catch: it only scores the structure, it won't tell you why the cycle happened, that part's still on you. built pure Rust with no runtime dependencies, specifically so it could sit as one binary between an agent and a codebase without adding friction.
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you don't need to re-explain your codebase's architecture to your agent every session. most tools stop at telling you what broke. sentrux is a real-time architectural sensor, it watches your codebase as a live treemap and turns file structure and dependencies into one continuous quality score. the loop is simple: codebase > agent scans structure and dependencies > sentrux scores 5 root cause metrics into one signal > agent sees exactly where risk concentrates > next session starts from a live map instead of a blind grep the binary carries zero built-in language knowledge, all 52 languages live in plugin.toml and tags.scm query files, so a new language needs zero rust code. small catch: it only scores the structure, it won't tell you why the cycle happened, that part's still on you. built pure Rust with no runtime dependencies, specifically so it could sit as one binary between an agent and a codebase without adding friction.

Simplifying AI

18,308 görüntüleme • 13 gün önce

I thought my AI agent needed a bigger context window wrong the leak was my shell every time it ran git diff HEAD~5 the model ate 92,000 tokens after ztk 18,000 ls -la src 2,000 tokens became 53 cargo test passing 397 tokens became 21 the fix is a 260KB Zig binary that sits between your agent and the shell it compresses command output before it hits the model not by summarizing everything by knowing what each command actually needs to preserve > diffs keep changed lines > tests keep failures > ls keeps structure > logs dedupe repeats > JSON and errors pass through untouched 5.8M tokens saved in one 256 command session stop buying bigger context windows while feeding your agent raw terminal sewage
0:11

I thought my AI agent needed a bigger context window wrong the leak was my shell every time it ran git diff HEAD~5 the model ate 92,000 tokens after ztk 18,000 ls -la src 2,000 tokens became 53 cargo test passing 397 tokens became 21 the fix is a 260KB Zig binary that sits between your agent and the shell it compresses command output before it hits the model not by summarizing everything by knowing what each command actually needs to preserve > diffs keep changed lines > tests keep failures > ls keeps structure > logs dedupe repeats > JSON and errors pass through untouched 5.8M tokens saved in one 256 command session stop buying bigger context windows while feeding your agent raw terminal sewage

Alpha Batcher

17,516 görüntüleme • 3 ay önce

The ChainGPT AI skill for Claude Code is one of the most complete Web3-AI dev environment on the market. Let me prove it. Open Claude Code with the installed skill, and you have direct access to: • Built-in wallets across 33+ chains • DEX trading, perps, and Hyperliquid execution • Smart contract generation and auditing • NFT generation across 22 chains • Real-time crypto news API • Fine-tuned crypto LLM with live on-chain data Every part of the Web3 stack, one prompt away. Here's what that looks like in practice. I built a real-time on-chain whale tracker in a single afternoon. It's called Whale Watch. → Pulls live swap data from Ethereum DEX pools → Filters every trade over $100K → Runs each whale through the ChainGPT LLM for a trader-grade live analysis → Routes the user into 1inch with the token pair pre-loaded if they want to follow the trade Real data. Real AI. Real action layer. The skill wrote the server. It hit the right APIs. It generated the UI. It debugged itself when something broke. The only thing I supplied was the idea and the polish. Open Claude Code. Ship something with ChainGPT AI this weekend! /plugin install ChainGPT-org/chaingpt-claude-skill
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The ChainGPT AI skill for Claude Code is one of the most complete Web3-AI dev environment on the market. Let me prove it. Open Claude Code with the installed skill, and you have direct access to: • Built-in wallets across 33+ chains • DEX trading, perps, and Hyperliquid execution • Smart contract generation and auditing • NFT generation across 22 chains • Real-time crypto news API • Fine-tuned crypto LLM with live on-chain data Every part of the Web3 stack, one prompt away. Here's what that looks like in practice. I built a real-time on-chain whale tracker in a single afternoon. It's called Whale Watch. → Pulls live swap data from Ethereum DEX pools → Filters every trade over $100K → Runs each whale through the ChainGPT LLM for a trader-grade live analysis → Routes the user into 1inch with the token pair pre-loaded if they want to follow the trade Real data. Real AI. Real action layer. The skill wrote the server. It hit the right APIs. It generated the UI. It debugged itself when something broke. The only thing I supplied was the idea and the polish. Open Claude Code. Ship something with ChainGPT AI this weekend! /plugin install ChainGPT-org/chaingpt-claude-skill

ChainGPT

25,853 görüntüleme • 3 ay önce

Cohort 4 is done, and the certificates are already landing in our students' inboxes. Congratulations to everyone who made it through! With that, we're officially opening applications for the Solana Rust Security Bootcamp (Cohort 5). A 6-week intensive in Rust and Solana security, built for engineers who want to move beyond writing code to identifying how real systems fail. > Supported by Solana Foundation. > Free to join. > Only 125 seats. And this round comes with a little bit of spice. We're teaming up with industry leaders you wouldn't expect to see here 🤫 C5 starts June 22. Applications close June 18. We recommend applying early. Application form below (as always) 🦀
0:10

Cohort 4 is done, and the certificates are already landing in our students' inboxes. Congratulations to everyone who made it through! With that, we're officially opening applications for the Solana Rust Security Bootcamp (Cohort 5). A 6-week intensive in Rust and Solana security, built for engineers who want to move beyond writing code to identifying how real systems fail. > Supported by Solana Foundation. > Free to join. > Only 125 seats. And this round comes with a little bit of spice. We're teaming up with industry leaders you wouldn't expect to see here 🤫 C5 starts June 22. Applications close June 18. We recommend applying early. Application form below (as always) 🦀

Rektoff

57,909 görüntüleme • 2 ay önce

I built a custom TradingView indicator with Claude Code & Fable 5. It's called the Storm Gauge and is built off a real quant trading strategy. I open-sourced the full code on GitHub. Free to install, free to fork, yours to improve. Here's how to install a quant indicator on your TradingView chart: What it actually is The Storm Gauge is a live implementation of the GARCH model, a Nobel Prize-winning volatility framework that real quant desks run daily. It forecasts how "violent" tomorrow's market could be by combining three inputs: an asset's baseline volatility, yesterday's shock, and where volatility was already sitting before that shock happened. It doesn't predict market direction. Instead, it measures risk, in real time, on your actual chart. How to install it Method 1. Plugin command Open the GitHub repo: Find the installation section, copy the command, and paste it into Claude Code. It runs the plugin install automatically. Method 2. Manual config Open garchmethod.md in the repo, copy the entire file, and paste it into Claude Code. It fetches the skill files directly and verifies the strategy for you. (you only need one method; I'm just showing both) Getting it onto your TradingView chart Inside the repo, there's a Pine Script folder. Open it, copy the entire file. Go into TradingView's Pine Editor, paste it in, hit Enter, and refresh. That's it. The Storm Gauge now runs live on your chart as a real number. Once it's installed, just talk to it: → "What's the volatility forecast on Bitcoin?" → "Explain what the current volatility forecast means on $BTC and how it should impact my position sizing" → "Help me size my S&P500 position according to current market volatility" Does it actually work? I backtested the same EMA cross strategy two ways across 15 years of BTC data. Same entries, same exits. → Fixed position sizing: $17,957 final equity → Storm Gauge (GARCH) sizing: $21,205 final equity Fewer drawdowns, less risk, better result. Full breakdown of the entire build process in my recent article - pinned on my profile.
0:18

I built a custom TradingView indicator with Claude Code & Fable 5. It's called the Storm Gauge and is built off a real quant trading strategy. I open-sourced the full code on GitHub. Free to install, free to fork, yours to improve. Here's how to install a quant indicator on your TradingView chart: What it actually is The Storm Gauge is a live implementation of the GARCH model, a Nobel Prize-winning volatility framework that real quant desks run daily. It forecasts how "violent" tomorrow's market could be by combining three inputs: an asset's baseline volatility, yesterday's shock, and where volatility was already sitting before that shock happened. It doesn't predict market direction. Instead, it measures risk, in real time, on your actual chart. How to install it Method 1. Plugin command Open the GitHub repo: Find the installation section, copy the command, and paste it into Claude Code. It runs the plugin install automatically. Method 2. Manual config Open garchmethod.md in the repo, copy the entire file, and paste it into Claude Code. It fetches the skill files directly and verifies the strategy for you. (you only need one method; I'm just showing both) Getting it onto your TradingView chart Inside the repo, there's a Pine Script folder. Open it, copy the entire file. Go into TradingView's Pine Editor, paste it in, hit Enter, and refresh. That's it. The Storm Gauge now runs live on your chart as a real number. Once it's installed, just talk to it: → "What's the volatility forecast on Bitcoin?" → "Explain what the current volatility forecast means on $BTC and how it should impact my position sizing" → "Help me size my S&P500 position according to current market volatility" Does it actually work? I backtested the same EMA cross strategy two ways across 15 years of BTC data. Same entries, same exits. → Fixed position sizing: $17,957 final equity → Storm Gauge (GARCH) sizing: $21,205 final equity Fewer drawdowns, less risk, better result. Full breakdown of the entire build process in my recent article - pinned on my profile.

Miles Deutscher

56,355 görüntüleme • 1 ay önce

one of my favorite ways to use claude code skills right now - combining remotion with claude-in-chrome for motion video creation. the workflow is addictive. the clip you see here was produced with minimal prompting effort let me know if you would like me to write a full break down of this process. you describe to claude code what you want, claude code writes the remotion components, opens the remotion studio (via browser) with claude-in-chrome, sees the actual rendered output, and iterates on it in real time. need the arrows pointing to the center of the bubbles instead of the edge? just say it. need the layout shifted to the center? say it. claude sees the preview, adjusts the code, re-renders. then when you're happy you tell claude code to render the final video. but skills are what make this possible. remotion knowledge + browser automation + the taste to iterate visually. no copy pasting screenshots back and forth. no "can you try moving it 10px to the right" over chat. it just looks and fixes. this is the kind of workflow that makes you realize how much further claude code can go beyond just writing code in a terminal. i didn't touch any code while working on the clip you see if you haven't tried combining skills together like this - start experimenting. the skills combos is where the magic is at.
0:16

one of my favorite ways to use claude code skills right now - combining remotion with claude-in-chrome for motion video creation. the workflow is addictive. the clip you see here was produced with minimal prompting effort let me know if you would like me to write a full break down of this process. you describe to claude code what you want, claude code writes the remotion components, opens the remotion studio (via browser) with claude-in-chrome, sees the actual rendered output, and iterates on it in real time. need the arrows pointing to the center of the bubbles instead of the edge? just say it. need the layout shifted to the center? say it. claude sees the preview, adjusts the code, re-renders. then when you're happy you tell claude code to render the final video. but skills are what make this possible. remotion knowledge + browser automation + the taste to iterate visually. no copy pasting screenshots back and forth. no "can you try moving it 10px to the right" over chat. it just looks and fixes. this is the kind of workflow that makes you realize how much further claude code can go beyond just writing code in a terminal. i didn't touch any code while working on the clip you see if you haven't tried combining skills together like this - start experimenting. the skills combos is where the magic is at.

elvis

46,494 görüntüleme • 6 ay önce

🤯 Andrej Karpathy's coding rules have officially broken the internet. [BOOKMARK THIS NOW] 144,000 stars. #1 on GitHub for 28 days straight. But 99% of people still haven't heard of them. Here's what a CLAUDE.md ACTUALLY is, and why it quietly fixed the biggest problem with AI coding: It's a text file Claude reads before it touches your code. Standing instructions. It never forgets them. The 4 rules that went viral: - Think before coding. State assumptions. Ask when unsure. Never guess. - Simplicity first. Minimum code that solves the problem. Nothing extra. - Surgical changes. Touch only what was asked. Every line traces back to the request. - Goal-driven. Turn vague instructions into a test that proves it works, before writing code. The dev who built it says it took his accuracy from ~65% to ~94%. The rules aren't the interesting part though. The interesting part is that almost nobody knows you can do this at all.
0:15

🤯 Andrej Karpathy's coding rules have officially broken the internet. [BOOKMARK THIS NOW] 144,000 stars. #1 on GitHub for 28 days straight. But 99% of people still haven't heard of them. Here's what a CLAUDE.md ACTUALLY is, and why it quietly fixed the biggest problem with AI coding: It's a text file Claude reads before it touches your code. Standing instructions. It never forgets them. The 4 rules that went viral: - Think before coding. State assumptions. Ask when unsure. Never guess. - Simplicity first. Minimum code that solves the problem. Nothing extra. - Surgical changes. Touch only what was asked. Every line traces back to the request. - Goal-driven. Turn vague instructions into a test that proves it works, before writing code. The dev who built it says it took his accuracy from ~65% to ~94%. The rules aren't the interesting part though. The interesting part is that almost nobody knows you can do this at all.

Coin Bureau

59,242 görüntüleme • 3 ay önce

EVERYONE'S TRYING TO SOLVE AI TEAM MEMORY WITH SERVERS, VECTOR DATABASES, AND ORCHESTRATION PLATFORMS. THIS OPEN SOURCE TOOL DOES IT WITH ONE FOLDER IN YOUR REPO. Every dev on your team runs Claude Code. When one agent screws something up, the rest have no idea. They just repeat the mistake next week. It's called teamlore. When your agent gets corrected or breaks something, it writes a small lore file into a .lore/ folder. That file ships with your PR, gets reviewed like normal code, and after merge every teammate's agent automatically recalls it when they touch that part of the repo. No server. No datab No accounts. No SaaS bill. Just a folder in git. Which means code review catches bad lessons before they poison the team, git blame tells you when a rule was added and why, and the whole thing works offline. One command to install: npx teamlore init Companion command: npx teamlore scarmap. Turns your team's history of mistakes into a visual heat map of the codebase. Every red zone is a place your team has been burned before. Which means every red zone is a place your agents should slow down. Here's the wildest part. The teamlore repo's own .lore/ folder contains every mistake Claude made while building teamlore itself. Dogfooded end-to-end. You can literally open the folder and read the receipts. The author's public invitation: "Would love for someone to try and break it." Available on npm. Repo just launched. 100% open source. (link in the comments)
0:15

EVERYONE'S TRYING TO SOLVE AI TEAM MEMORY WITH SERVERS, VECTOR DATABASES, AND ORCHESTRATION PLATFORMS. THIS OPEN SOURCE TOOL DOES IT WITH ONE FOLDER IN YOUR REPO. Every dev on your team runs Claude Code. When one agent screws something up, the rest have no idea. They just repeat the mistake next week. It's called teamlore. When your agent gets corrected or breaks something, it writes a small lore file into a .lore/ folder. That file ships with your PR, gets reviewed like normal code, and after merge every teammate's agent automatically recalls it when they touch that part of the repo. No server. No datab No accounts. No SaaS bill. Just a folder in git. Which means code review catches bad lessons before they poison the team, git blame tells you when a rule was added and why, and the whole thing works offline. One command to install: npx teamlore init Companion command: npx teamlore scarmap. Turns your team's history of mistakes into a visual heat map of the codebase. Every red zone is a place your team has been burned before. Which means every red zone is a place your agents should slow down. Here's the wildest part. The teamlore repo's own .lore/ folder contains every mistake Claude made while building teamlore itself. Dogfooded end-to-end. You can literally open the folder and read the receipts. The author's public invitation: "Would love for someone to try and break it." Available on npm. Repo just launched. 100% open source. (link in the comments)

Harman

34,614 görüntüleme • 22 gün önce

i'm not fine after reading this a guy with a laptop got his own silicon chip manufactured with software Google gave away. the commercial version of that software rents for up to $1,000,000 a year. he never signed a vendor contract and never paid for a seat. he wrote the logic, pushed it to GitHub, and nine months later a wafer came out of a fab. getting silicon with your name in it used to take a company. now it takes nine months. his slot was 160 by 100 microns: about 1,000 logic gates, 8 inputs, 8 outputs, clocked past 50 MHz. more than 600 designs have already come back this way. this is the open silicon stack. Google and SkyWater published a complete 130nm manufacturing process, DARPA funded the software that turns code into a fab-ready file, and all of it sits in public repositories. turns out the whole flow fits in a git push: - write the logic in Verilog, or drag gates around in a browser if you have never done this - push to GitHub, an action runs synthesis, placement, routing and sign-off on the commit - OpenROAD finishes place-and-route with no human in the loop, code to fab file inside 24 hours - SKY130 carries the fab's real design rules, so passing the checks means it is manufacturable - a few hundred designs share one wafer, which is the only reason a person can afford the masks nobody puts this part in the thread: 130nm is roughly where the industry stood in 2001, and you wait six to nine months for silicon. this does not get you a GPU. it gets you a real object with your logic inside it. bookmark this. the video is one of those designs opened layer by layer, and every rectangle in it exists in the file that was sent to the fab.
0:16

i'm not fine after reading this a guy with a laptop got his own silicon chip manufactured with software Google gave away. the commercial version of that software rents for up to $1,000,000 a year. he never signed a vendor contract and never paid for a seat. he wrote the logic, pushed it to GitHub, and nine months later a wafer came out of a fab. getting silicon with your name in it used to take a company. now it takes nine months. his slot was 160 by 100 microns: about 1,000 logic gates, 8 inputs, 8 outputs, clocked past 50 MHz. more than 600 designs have already come back this way. this is the open silicon stack. Google and SkyWater published a complete 130nm manufacturing process, DARPA funded the software that turns code into a fab-ready file, and all of it sits in public repositories. turns out the whole flow fits in a git push: - write the logic in Verilog, or drag gates around in a browser if you have never done this - push to GitHub, an action runs synthesis, placement, routing and sign-off on the commit - OpenROAD finishes place-and-route with no human in the loop, code to fab file inside 24 hours - SKY130 carries the fab's real design rules, so passing the checks means it is manufacturable - a few hundred designs share one wafer, which is the only reason a person can afford the masks nobody puts this part in the thread: 130nm is roughly where the industry stood in 2001, and you wait six to nine months for silicon. this does not get you a GPU. it gets you a real object with your logic inside it. bookmark this. the video is one of those designs opened layer by layer, and every rectangle in it exists in the file that was sent to the fab.

Argona

150,347 görüntüleme • 24 gün önce

SOMEONE BUILT A CLAUDE CODE PLUGIN THAT REFUSES TO WORK UNTIL YOU DO PUSH-UPS OR SQUATS its called workout gate and it is exactly as cursed as it sounds when the hook fires, it blocks your prompt, opens your webcam, and makes you exercise to keep coding > it counts your reps live through the webcam with mediapipe, no honor system rounding down > only releases your prompt once you actually finish the reps > quit halfway and the leftover reps get saved as debt for your next session > chill, demo and hardcore presets, plus prompt based, time based or random triggers > tracks stats, streaks and personal records right in the claude code statusline we automated the coding, now we're automating the part where we actually take care of ourselves
0:12

SOMEONE BUILT A CLAUDE CODE PLUGIN THAT REFUSES TO WORK UNTIL YOU DO PUSH-UPS OR SQUATS its called workout gate and it is exactly as cursed as it sounds when the hook fires, it blocks your prompt, opens your webcam, and makes you exercise to keep coding > it counts your reps live through the webcam with mediapipe, no honor system rounding down > only releases your prompt once you actually finish the reps > quit halfway and the leftover reps get saved as debt for your next session > chill, demo and hardcore presets, plus prompt based, time based or random triggers > tracks stats, streaks and personal records right in the claude code statusline we automated the coding, now we're automating the part where we actually take care of ourselves

Om Patel

671,489 görüntüleme • 2 ay önce