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I keep seeing the same pattern with Three.js games, shaders, p5.js, and now 3D UI. Give a coding agent a strong reference, the live URL, and the source repo. It can study the mechanics, recreate them, and give you a working place to experiment. For this one, I turned... show more

Meng To

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146,872 次观看 • 1 天前 •via X (Twitter)

艺术科学技术教育

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We built the best codebase search to give any agent grounded information from GitHub repos. Introducing Sandbox Search. Point it at any repo, and we’ll spin up a secure coding agent in its own sandbox to do research for you. Use inside claude code, openclaw, cursor, and more.

We built the best codebase search to give any agent grounded information from GitHub repos. Introducing Sandbox Search. Point it at any repo, and we’ll spin up a secure coding agent in its own sandbox to do research for you. Use inside claude code, openclaw, cursor, and more.

Arlan

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Wow. You can literally chat with any GitHub repo now! Just pop "talkto" in front of "github" in the URL, and BOOM, you're chatting with your codebase! 🤯 It launches a full chat UI where you can ask the code anything. 100% open-source. Repo link below ↓

Wow. You can literally chat with any GitHub repo now! Just pop "talkto" in front of "github" in the URL, and BOOM, you're chatting with your codebase! 🤯 It launches a full chat UI where you can ask the code anything. 100% open-source. Repo link below ↓

Charly Wargnier

15,055 次观看 • 1 年前

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Daniel San

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I feel like this could be turned into a cool hero effect for a component library site. Where you move your cursor to tear between the design and the code.... 🤔

I feel like this could be turned into a cool hero effect for a component library site. Where you move your cursor to tear between the design and the code.... 🤔

matt rothenberg

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Wow.. you can now instantly turn any GitHub repo into AI-generated documentation, just by changing the URL. Replace “github” with “deepwiki” in any GitHub URL and you’ll see: → Instant docs for any codebase → Chat with it like a conversation

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Oliver Prompts

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If I had to choose one thing to do, it would be just coding WebGL flowers It's a GLSL shader, a full-screen plane, and 2 render targets to swap on each frame Live demo & source code: Made with Three.js Hosted on CodePen.IO Special thanks to The Book of Shaders

If I had to choose one thing to do, it would be just coding WebGL flowers It's a GLSL shader, a full-screen plane, and 2 render targets to swap on each frame Live demo & source code: Made with Three.js Hosted on CodePen.IO Special thanks to The Book of Shaders

Ksenia Kondrashova

51,837 次观看 • 3 年前

Seeing this post from Zach inspired me to explore some eye tracking experiments, shared these before but consolidated them into a post, shared the code in my open source repo for the eye drawing experiment, let me know if anyone wants the code to the other experiments, link in replies

Seeing this post from Zach inspired me to explore some eye tracking experiments, shared these before but consolidated them into a post, shared the code in my open source repo for the eye drawing experiment, let me know if anyone wants the code to the other experiments, link in replies

Mike Lee

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Draw GLSL flowers with your cursor! 🌺 One full-screen plane, two render targets, and a bit of shader magic Live demo & source code: Made with Three.js Hosted on CodePen.IO Special thanks to The Book of Shaders #webgl #glsl #threejs #shader #drawingtool

Draw GLSL flowers with your cursor! 🌺 One full-screen plane, two render targets, and a bit of shader magic Live demo & source code: Made with Three.js Hosted on CodePen.IO Special thanks to The Book of Shaders #webgl #glsl #threejs #shader #drawingtool

Ksenia Kondrashova

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elvis

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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

200,319 次观看 • 1 个月前

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Tykra

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Jane Manchun Wong

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Chong-U

264,966 次观看 • 6 个月前

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💬 We get asked Can I manage my strategies without clicking through the platform? ❕ Answer from a GT App Top Trader: Yes, and it’s a total game-changer. I’ve started using the GT Protocol MCP server to connect the platform directly to my AI agent. 🔸 Fast Integration Grab the MCP server from the GT Protocol GitHub and follow the repo guide, it’s a quick setup that only takes a couple of minutes. Once it’s ready, you can connect Claude, Cursor, or Claude Code to your account. Just tell your agent to authenticate, and your tokens will be saved automatically. 🔸 Trading via conversation Now, I use natural language for everything. For example, I just ask for a backtest, get the win rate in seconds, and deploy to a demo account with one command. 🔸 Instant monitoring I don't click around anymore. I just ask "What’s running right now?" to get a full breakdown of active bots and profits delivered straight into the chat. No more forms or clicking, just pure AI-driven trading! 👉 Get the MCP Server

GT Protocol

36,479 次观看 • 3 个月前

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Warp

223,039 次观看 • 3 个月前

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Alrighty, everything is ready 😎 here’s an unofficial “2x Codex limits” promo from my side for you all. meet DevSpace — an MCP connector app that turns ChatGPT into Codex. npm install -g @waishnav/devspace After installing, tunnel the MCP server over the internet and enjoy 2x limits. You can use GPT-5.5 Pro, xHigh, or High for planning, then hand off the task to your local Codex/pi/opencode/cursor/claude code instance. Or you can just use it for reviewing code written by other local coding agents Go ahead, experiment with different workflows, and keep the feedback coming on GitHub Issues or in my DMs And let’s thank OpenAI for being so generous by giving us separate ChatGPT and Codex limits and by being so chill around this MCP :) Please use it sparingly, only when you run out of limits. Don’t overuse it — in the end, they do have a button to stop it 🙂

waishnav

529,621 次观看 • 1 个月前

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Karpathy's Agentic Engineering finally has proper tooling! (built by Google) Karpathy defined agentic engineering as the discipline that separates production agent work from vibe coding. The core skills he listed were spec design, eval loops, and security oversight. The problem has been that practicing this still requires a different tool for every phase: - editor for code - a terminal for scaffolding - a browser for testing - a cloud console for deployment - and a separate framework for evals. Every transition is a context switch. The solution to production-grade Agentic Engineering is now actually implemented in Google’s Agents CLI. It covers the entire workflow in one place for scaffolding, evaluating, and deploying ADK agents. One setup command injects 7 ADK-specific skills into a coding agent's context, which lets it handle scaffolding, evals, deployment, and enterprise registration through natural language. I tested this end-to-end by building a RAG agent from scratch using Claude Code. It scaffolded the full project from the ADK agentic_rag template, generated 20 eval scenarios with LLM-as-judge scoring, and returned a quantitative scorecard. Finally, it also deployed everything to Agent Runtime and registered the agent to Gemini Enterprise, so the entire org can discover and use it. The video below shows this in action, and I worked with the Google Cloud team to put this together. Agents CLI GitHub repo → (don't forget to star it ⭐ ) I wrote up the full build covering all six steps from install to enterprise registration. It includes the eval scorecard, the instruction loophole the eval caught before deployment, and what the deployment process actually looks like end-to-end. Read it below.

Akshay 🚀

256,388 次观看 • 1 个月前

been getting a lot of qs on how i vibe coded this demo. and the answer is: stop acting like a coder and start acting like a PM! my exact playbook👇 1. logic first ignore the UI/graphics. focus strictly on how it works. do a massive brain dump of every requirement into a plain txt file and drop it in your root folder. make it exhaustively detailed. 2. the stack · Nano Banana 2 (tiles/textures/3D refs) · Tripo AI (turning the 2D pics into actual 3D models) · Cursor + Opus 4.6 (doing the heavy lifting) · Netlify (deploy) 3. hire the AI PM feed your brain dump to an LLM. tell it to write a technical spec sheet like a senior PM would. drop that in the root too. 4. the scrum master have it break the entire project down into a markdown checklist by phases. notice we still haven't touched the codebase yet. that's the point. 5. let it cook go to your agent in Cursor and literally just prompt "Start Phase 1". test locally. bugs? tell it to fix. works? "Start Phase 2". loop this until you're done. Now you can focus on visuals, refine them with the agent. And yes, it can deploy it for you too if you give it perms. stop rushing to the editor. architect the idea and let the AI sweat the code. Open sourced repo in the qt post below

been getting a lot of qs on how i vibe coded this demo. and the answer is: stop acting like a coder and start acting like a PM! my exact playbook👇 1. logic first ignore the UI/graphics. focus strictly on how it works. do a massive brain dump of every requirement into a plain txt file and drop it in your root folder. make it exhaustively detailed. 2. the stack · Nano Banana 2 (tiles/textures/3D refs) · Tripo AI (turning the 2D pics into actual 3D models) · Cursor + Opus 4.6 (doing the heavy lifting) · Netlify (deploy) 3. hire the AI PM feed your brain dump to an LLM. tell it to write a technical spec sheet like a senior PM would. drop that in the root too. 4. the scrum master have it break the entire project down into a markdown checklist by phases. notice we still haven't touched the codebase yet. that's the point. 5. let it cook go to your agent in Cursor and literally just prompt "Start Phase 1". test locally. bugs? tell it to fix. works? "Start Phase 2". loop this until you're done. Now you can focus on visuals, refine them with the agent. And yes, it can deploy it for you too if you give it perms. stop rushing to the editor. architect the idea and let the AI sweat the code. Open sourced repo in the qt post below

TechHalla

70,060 次观看 • 4 个月前

I literally don't use Claude anymore... Just Claude Code and Codex in the web. This is a presentation I had Opus generate after doing research... And if you save the prompt you can have it generate in any style you want.

I literally don't use Claude anymore... Just Claude Code and Codex in the web. This is a presentation I had Opus generate after doing research... And if you save the prompt you can have it generate in any style you want.

Riley Brown

118,000 次观看 • 10 个月前