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Bare imitation learning without robotic pre-training is an unfairly overlooked area. (it doesn't even have a name) When done right, it has the advantages of programming. It’s reliable, predictable, easy to modify and debug. The only difference is that the source of truth is a small dataset instead of...

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Igor Kulakov (MicroFactory)

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20,189 görüntüleme • 1 ay önce •via X (Twitter)

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Claude Code is the OpenClaw alternative you already had. I've been telling people this in person for three months. Now it's a piece on Every 📧. When OpenClaw was at peak hype a few months ago, everyone was going crazy over it — for good reasons. But almost nobody made the obvious comparison: Claude Code already does the thing you love about OpenClaw. In a lot of cases, better. Here's why people missed it. You have to understand the difference between a model and a harness. OpenClaw, at the end of the day, is just a harness on top of AI models. And Claude Code is too — it just got marketed as a coding tool, an alternative to Cursor. Until Cowork launched, almost nobody looked at it as a tool for non-programmers. Dan Shipper 📧 was one of the earliest to make that claim, and he was damn right. Let Claude Code run from the home folder of your computer with free access, and you get exactly what made OpenClaw exciting. Instead of just arguing it, here's a video walkthrough of a couple of my AI employees i built on the Claude Code harness. And here's the full article:
8:31

Claude Code is the OpenClaw alternative you already had. I've been telling people this in person for three months. Now it's a piece on Every 📧. When OpenClaw was at peak hype a few months ago, everyone was going crazy over it — for good reasons. But almost nobody made the obvious comparison: Claude Code already does the thing you love about OpenClaw. In a lot of cases, better. Here's why people missed it. You have to understand the difference between a model and a harness. OpenClaw, at the end of the day, is just a harness on top of AI models. And Claude Code is too — it just got marketed as a coding tool, an alternative to Cursor. Until Cowork launched, almost nobody looked at it as a tool for non-programmers. Dan Shipper 📧 was one of the earliest to make that claim, and he was damn right. Let Claude Code run from the home folder of your computer with free access, and you get exactly what made OpenClaw exciting. Instead of just arguing it, here's a video walkthrough of a couple of my AI employees i built on the Claude Code harness. And here's the full article:

Nityesh

22,895 görüntüleme • 1 ay önce

Been using the new Claude 3.5 model as a tester and now that it is out, I can say it is very very impressive, and the "artifacts" that it generates are like a simpler version of Code Interpreter This is a real-time video of me creating a playable game and editing it with Claude
1:51

Been using the new Claude 3.5 model as a tester and now that it is out, I can say it is very very impressive, and the "artifacts" that it generates are like a simpler version of Code Interpreter This is a real-time video of me creating a playable game and editing it with Claude

Ethan Mollick

162,293 görüntüleme • 2 yıl önce

Cursor CEO Michael Truell on the future of writing code: “ Our goal with Cursor is to invent a new type of programming.” “It looks like a world where you have a representation of the logic of your software that does look more like English.” “You can imagine kind of an evolution of programming language towards pseudocode. You have written down the logic of the software, and you can edit that at a high level.” “It won't be the impenetrable millions of lines of code, it'll instead be something that's much terser and easier to understand and easier to navigate.” Source: Michael Truell (CEO Cursor) with Lenny Rachitsky on Lenny's Podcast
2:50

Cursor CEO Michael Truell on the future of writing code: “ Our goal with Cursor is to invent a new type of programming.” “It looks like a world where you have a representation of the logic of your software that does look more like English.” “You can imagine kind of an evolution of programming language towards pseudocode. You have written down the logic of the software, and you can edit that at a high level.” “It won't be the impenetrable millions of lines of code, it'll instead be something that's much terser and easier to understand and easier to navigate.” Source: Michael Truell (CEO Cursor) with Lenny Rachitsky on Lenny's Podcast

a16z

812,698 görüntüleme • 9 ay önce

Weave is launching the number 1 prompt router in the world. It enables you to get 70% more efficient use of your tokens. We analyzed millions of prompts and found that the vast majority don't need a frontier model. Weave Router fixes that. It analyzes your prompt and routes it to the highest quality model with the lowest cost (across open and closed source models). This all happens in your current workflow on Claude, Cursor or Codex so you don't have to change a thing. Early customers have seen an ~70% reduction in costs without any slowdowns. Source code available.
0:47

Weave is launching the number 1 prompt router in the world. It enables you to get 70% more efficient use of your tokens. We analyzed millions of prompts and found that the vast majority don't need a frontier model. Weave Router fixes that. It analyzes your prompt and routes it to the highest quality model with the lowest cost (across open and closed source models). This all happens in your current workflow on Claude, Cursor or Codex so you don't have to change a thing. Early customers have seen an ~70% reduction in costs without any slowdowns. Source code available.

Adam Cohen

25,191 görüntüleme • 2 ay önce

Today we’re launching our first homegrown AI model: an open source turn detection model for building voice agents. Instead of relying solely on voice activity detection (VAD), which only considers when a user is speaking, our model also considers what has and is being said in the context of a conversation and predicts when a user is finished expressing their thoughts before the agent responds. Conversations with AI voice agents using this new model flow much more naturally without constant interruptions from the AI— check it out (more videos, details, and code in the thread):
2:36

Today we’re launching our first homegrown AI model: an open source turn detection model for building voice agents. Instead of relying solely on voice activity detection (VAD), which only considers when a user is speaking, our model also considers what has and is being said in the context of a conversation and predicts when a user is finished expressing their thoughts before the agent responds. Conversations with AI voice agents using this new model flow much more naturally without constant interruptions from the AI— check it out (more videos, details, and code in the thread):

LiveKit

126,898 görüntüleme • 1 yıl önce

The new Screenshot to Code from Vercel v0 is insane. I just took a screenshot of a pricing table and it was converted into code using AI in seconds! It even outputs the code and allows you to modify any specific parts.
0:20

The new Screenshot to Code from Vercel v0 is insane. I just took a screenshot of a pricing table and it was converted into code using AI in seconds! It even outputs the code and allows you to modify any specific parts.

Alvaro Cintas

378,020 görüntüleme • 2 yıl önce

Cursor CEO Michael Truell on the future of writing code: "Our goal with Cursor is to invent a new type of programming." "It looks like a world where you have a representation of the logic of your software that does look more like English." "You can imagine kind of an evolution of programming language towards pseudocode. You have written down the logic of the software, and you can edit that at a high level." "It won't be the impenetrable millions of lines of code, it'll instead be something that's much terser and easier to understand and easier to navigate." Michael Truell with Lenny Rachitsky on Lenny's Podcast
2:50

Cursor CEO Michael Truell on the future of writing code: "Our goal with Cursor is to invent a new type of programming." "It looks like a world where you have a representation of the logic of your software that does look more like English." "You can imagine kind of an evolution of programming language towards pseudocode. You have written down the logic of the software, and you can edit that at a high level." "It won't be the impenetrable millions of lines of code, it'll instead be something that's much terser and easier to understand and easier to navigate." Michael Truell with Lenny Rachitsky on Lenny's Podcast

a16z

1,015,754 görüntüleme • 2 ay önce

A small project I'm publishing for Neovim people: 🐠 butterfish.nvim This is a Neovim plugin to use language models for very fluent code editing. It veers away from the chatbox or codebase Q/A approaches and instead focuses on specific local edits, for example, select and rewrite a block of code. Do powerful things with few keypresses, without leaving the Neovim buffer!
4:56

A small project I'm publishing for Neovim people: 🐠 butterfish.nvim This is a Neovim plugin to use language models for very fluent code editing. It veers away from the chatbox or codebase Q/A approaches and instead focuses on specific local edits, for example, select and rewrite a block of code. Do powerful things with few keypresses, without leaving the Neovim buffer!

Peter Bakkum

29,069 görüntüleme • 2 yıl önce

BARIS: Trump promised no new wars and accountability for the Epstein class. Instead, he started a new war for the Epstein class. A year of this nonsense. So much of this business is fake. So much of it is news production and influence production. You’re only allowed to find out the truth when it’s too late, when the damage is already done.
4:03

BARIS: Trump promised no new wars and accountability for the Epstein class. Instead, he started a new war for the Epstein class. A year of this nonsense. So much of this business is fake. So much of it is news production and influence production. You’re only allowed to find out the truth when it’s too late, when the damage is already done.

Grace Chong, MBI

19,115 görüntüleme • 2 ay önce

THIS GUY TURNED A DESK LAMP INTO A LIVE CLAUDE CODE STATUS INDICATOR the lamp changes color based on what claude code is doing in real time when claude is thinking it's one color. when it's writing code it shifts. when it's done it changes again. when it errors out you know instantly without even looking at your screen the lamp is a moonside halo and i'm already tryna to buy one I might even buy multiple for the multiple claude sessions running in the background and turn my room into a disco if the color reflected the operational status of claude it would just be red 24/7 it could also track your usage limit. green at the start of the session, slowly fading to red as your tokens drain people are already hooking this up to their philips hue and govee setups at home
0:44

THIS GUY TURNED A DESK LAMP INTO A LIVE CLAUDE CODE STATUS INDICATOR the lamp changes color based on what claude code is doing in real time when claude is thinking it's one color. when it's writing code it shifts. when it's done it changes again. when it errors out you know instantly without even looking at your screen the lamp is a moonside halo and i'm already tryna to buy one I might even buy multiple for the multiple claude sessions running in the background and turn my room into a disco if the color reflected the operational status of claude it would just be red 24/7 it could also track your usage limit. green at the start of the session, slowly fading to red as your tokens drain people are already hooking this up to their philips hue and govee setups at home

Om Patel

108,062 görüntüleme • 3 ay önce

We'd like to remind everyone that @Dogecoin is an open-source project based on the code of #Bitcoin and that virtually all development of Dogecoin is done by volunteers. A small number of core developers & contributors also work here at the Dogecoin Foundation.
0:31

We'd like to remind everyone that @Dogecoin is an open-source project based on the code of #Bitcoin and that virtually all development of Dogecoin is done by volunteers. A small number of core developers & contributors also work here at the Dogecoin Foundation.

Dogecoin Foundation

247,134 görüntüleme • 1 yıl önce

Claude Code is now free to run. Most people still think you need a paid setup. Here’s the basic flow: → Install Claude Code with the official installer. → Create a free OpenRouter account. → Grab your API key. → Install Claude Code Router. → Point Claude Code to the local router. → Choose a free model with the :free suffix. → Run CCR code instead of normal Claude Code. → Check /status to confirm it works. You keep the Claude Code workflow. You just route it through a free model.
9:31

Claude Code is now free to run. Most people still think you need a paid setup. Here’s the basic flow: → Install Claude Code with the official installer. → Create a free OpenRouter account. → Grab your API key. → Install Claude Code Router. → Point Claude Code to the local router. → Choose a free model with the :free suffix. → Run CCR code instead of normal Claude Code. → Check /status to confirm it works. You keep the Claude Code workflow. You just route it through a free model.

Julian Goldie SEO

17,618 görüntüleme • 2 ay önce

Is your AI model losing focus on long tasks? Theo’s live stream showed Minimax M2.1 is built different, already outperforming other models that crumble under pressure. He had it grind on a feature for 400+ lines of code over 20 minutes without a single issue, while other models were making junior mistakes. It just plans, executes, and figures itself out. This is the kind of long-form consistency and reliability that most models only dream of. It’s fast, it’s solid, and it doesn’t lose track of instructions, a true workhorse for serious developers. Huge props to MiniMax (official) for building a model that can actually go the distance. See the future of AI development:
0:29

Is your AI model losing focus on long tasks? Theo’s live stream showed Minimax M2.1 is built different, already outperforming other models that crumble under pressure. He had it grind on a feature for 400+ lines of code over 20 minutes without a single issue, while other models were making junior mistakes. It just plans, executes, and figures itself out. This is the kind of long-form consistency and reliability that most models only dream of. It’s fast, it’s solid, and it doesn’t lose track of instructions, a true workhorse for serious developers. Huge props to MiniMax (official) for building a model that can actually go the distance. See the future of AI development:

FELIX

49,166 görüntüleme • 7 ay önce

Claude R Perrin Code SDK is under-rated One cool part with Claude Code SDK is that it supports full features out of box: - Skills - Sub agents - Hooks - ... Which means you can use claude code CLI as a debug tool to build agent, and then import to your Claude code powered agent Here is a quick example of a pptx presentation agent using Claude Code SDK + doc skills Code example from AI Builder Club by Kai:
0:25

Claude R Perrin Code SDK is under-rated One cool part with Claude Code SDK is that it supports full features out of box: - Skills - Sub agents - Hooks - ... Which means you can use claude code CLI as a debug tool to build agent, and then import to your Claude code powered agent Here is a quick example of a pptx presentation agent using Claude Code SDK + doc skills Code example from AI Builder Club by Kai:

Jason Zhou

11,981 görüntüleme • 9 ay önce

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.
0:22

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dan McAteer

174,267 görüntüleme • 1 ay önce

i been running Qwen3.5-35B-A3B UD-Q4_K_XL through Claude Code since llama.cpp merged the Anthropic endpoint. configured it in minutes. everything was great. projects grew from single scripts to multifile systems with 8 modules and 3,000+ lines. then the chains started breaking. 3 to 5 minutes of pure autonomy and suddenly it stops. tool call fails. reprompt. it recovers. 2 minutes later it stops again. the model is fine. the harness is the bottleneck. saw a comment suggesting OpenCode. installed it. pointed it at the same localhost endpoint running the same model on the same GPU. the game is different. instead of stopping on a bad tool call it just keeps going. on wrong read it adjusts. if file not found it retries. the flow is unbroken. i watched it plan a refactor across 8 files, read every module, and start building without a single pause. in Claude Code that same task would have stopped 4 times. the tradeoff is sometimes it loops. same tool call repeated because the model loses track of what it already read. but here is the thing. i choose loops over pauses. a loop you can interrupt and redirect. a broken chain stops the flow and you have to reprompt to get it moving again. someone is solving this at the core level and i have a feeling it is the open source community. the fact that i can run this level of autonomous coding intelligence on a single consumer GPU with 24gb VRAM at 112 tokens per second. respect to the chinese labs. respect to the open source builders making this possible.
2:00

i been running Qwen3.5-35B-A3B UD-Q4_K_XL through Claude Code since llama.cpp merged the Anthropic endpoint. configured it in minutes. everything was great. projects grew from single scripts to multifile systems with 8 modules and 3,000+ lines. then the chains started breaking. 3 to 5 minutes of pure autonomy and suddenly it stops. tool call fails. reprompt. it recovers. 2 minutes later it stops again. the model is fine. the harness is the bottleneck. saw a comment suggesting OpenCode. installed it. pointed it at the same localhost endpoint running the same model on the same GPU. the game is different. instead of stopping on a bad tool call it just keeps going. on wrong read it adjusts. if file not found it retries. the flow is unbroken. i watched it plan a refactor across 8 files, read every module, and start building without a single pause. in Claude Code that same task would have stopped 4 times. the tradeoff is sometimes it loops. same tool call repeated because the model loses track of what it already read. but here is the thing. i choose loops over pauses. a loop you can interrupt and redirect. a broken chain stops the flow and you have to reprompt to get it moving again. someone is solving this at the core level and i have a feeling it is the open source community. the fact that i can run this level of autonomous coding intelligence on a single consumer GPU with 24gb VRAM at 112 tokens per second. respect to the chinese labs. respect to the open source builders making this possible.

Sudo su

67,032 görüntüleme • 5 ay önce

Dario Amodei just dismantled the biggest myth in the AI industry. Open source AI isn’t free. It never was. Amodei: “It’s not free. You have to run it on inference and someone has to make it fast on inference.” For decades, open source meant something real. It meant a teenager in a basement could download the same tools as a Fortune 500 company. Could read the code. Could modify it. Could build something that competed with the giants. That was genuine democratization. That actually happened. AI is different. Fundamentally. Physically. In ways the ideology hasn’t caught up to yet. Downloading the weights is the easy part. The part that actually costs something is turning the weights into a running system. Into responses. Into intelligence operating in real time at scale. That requires compute. Power. Infrastructure. The kind measured in billions of dollars and years of construction. Amodei: “These are big models. They’re hard to do inference on. Ultimately you have to host it on the cloud. The people who host it on the cloud do inference.” The open source debate was never about who owns the model. It was always about who owns the cloud. And Amodei goes further. When a competitor drops a new open model, he doesn’t ask whether it’s open or closed. He doesn’t care about the licensing. He doesn’t engage the ideology. Amodei: “I don’t think it mattered that DeepSeek is open source. I think I ask, is it a good model? Is it better than us at the things that matter? That’s the only thing that I care about.” That’s the ruthless clarity of someone actually trying to win. While the media debates licensing frameworks, Amodei is asking one question. Is it better. Everything else is a distraction. Amodei: “I don’t think open source works the same way in AI that it has worked in other areas. Here we can’t see inside the model.” This isn’t Linux. You can’t read it. You can’t fork it. You can’t understand it the way generations of developers understood the tools they inherited. You can download it. And then you need a data center to run it. The teenager in the basement who was supposed to be empowered by this revolution needs a billion dollars of infrastructure before the empowerment starts. The era of the basement coder rewriting civilization on a laptop is over. The future belongs to whoever commands the compute, owns the power grid, and can actually turn the intelligence on. Open weights without infrastructure isn’t democratization. It’s a promise the physics of the universe won’t let us keep.
1:40

Dario Amodei just dismantled the biggest myth in the AI industry. Open source AI isn’t free. It never was. Amodei: “It’s not free. You have to run it on inference and someone has to make it fast on inference.” For decades, open source meant something real. It meant a teenager in a basement could download the same tools as a Fortune 500 company. Could read the code. Could modify it. Could build something that competed with the giants. That was genuine democratization. That actually happened. AI is different. Fundamentally. Physically. In ways the ideology hasn’t caught up to yet. Downloading the weights is the easy part. The part that actually costs something is turning the weights into a running system. Into responses. Into intelligence operating in real time at scale. That requires compute. Power. Infrastructure. The kind measured in billions of dollars and years of construction. Amodei: “These are big models. They’re hard to do inference on. Ultimately you have to host it on the cloud. The people who host it on the cloud do inference.” The open source debate was never about who owns the model. It was always about who owns the cloud. And Amodei goes further. When a competitor drops a new open model, he doesn’t ask whether it’s open or closed. He doesn’t care about the licensing. He doesn’t engage the ideology. Amodei: “I don’t think it mattered that DeepSeek is open source. I think I ask, is it a good model? Is it better than us at the things that matter? That’s the only thing that I care about.” That’s the ruthless clarity of someone actually trying to win. While the media debates licensing frameworks, Amodei is asking one question. Is it better. Everything else is a distraction. Amodei: “I don’t think open source works the same way in AI that it has worked in other areas. Here we can’t see inside the model.” This isn’t Linux. You can’t read it. You can’t fork it. You can’t understand it the way generations of developers understood the tools they inherited. You can download it. And then you need a data center to run it. The teenager in the basement who was supposed to be empowered by this revolution needs a billion dollars of infrastructure before the empowerment starts. The era of the basement coder rewriting civilization on a laptop is over. The future belongs to whoever commands the compute, owns the power grid, and can actually turn the intelligence on. Open weights without infrastructure isn’t democratization. It’s a promise the physics of the universe won’t let us keep.

Dustin

687,201 görüntüleme • 5 ay önce

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
13:23

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

55,345 görüntüleme • 2 ay önce