AI Dynamics

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  • Optimizing AI agent performance through harness layer refinement

    By

    @alphasignalai

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    You can now make your AI agent rewrite itself and get 6x better. Most AI optimization focuses on the model. Meta-Harness focuses on the harness instead. That's the code wrapping the model. It controls memory, retrieval, and execution. Changing just this layer creates a 6x

    → View original post on X — @alphasignalai

  • Company locks down subscriptions while competitors embrace OpenClaw

    By

    @steipete

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    Out of 8+ companies that offer subs they are the only company that lock things down – everyone else is embracing OpenClaw.

    → View original post on X — @steipete

  • ChatGPT Launches on Apple CarPlay for Hands-Free AI
    ChatGPT Launches on Apple CarPlay for Hands-Free AI

    By

    @vision_ia

    –

    ChatGPT is now in your car. OpenAI has just launched ChatGPT in Apple CarPlay. You speak. ChatGPT responds. Right from your dashboard screen. Hands-free. What's fascinating is the story behind it. A developer, Gui Ferreira, had tweeted in September 2025: "ChatGPT's voice mode

    → View original post on X — @vision_ia

  • Complete AI Learning Roadmap: Videos, Repos, Books, Papers, Courses
    Complete AI Learning Roadmap: Videos, Repos, Books, Papers, Courses

    By

    @nandodf

    –

    Stop wasting hours trying to learn AI. 📘📚 I have already done it for you. With one list. Zero confusion. And no fluff 📹 Videos: 1. LLM Introduction: lnkd.in/dMqbaZdK 2. LLMs from Scratch: lnkd.in/dYYwEhYy 3. Agentic AI Overview (Stanford): lnkd.in/dArmMt2i 4. Building and Evaluating Agents: lnkd.in/dBWd2W8u 5. Building Effective Agents: lnkd.in/dHfdebqw 6. Building Agents with MCP: lnkd.in/dXuNHrRJ 7. Building an Agent from Scratch: lnkd.in/da3ANw3w 8. Philo Agents: lnkd.in/dq-BfZE5 🗂️ Repos 1. GenAI Agents: lnkd.in/d3UDtwwv 2. Microsoft's AI Agents for Beginners: lnkd.in/dHvTmJnv 3. Prompt Engineering Guide: lnkd.in/gJjGbxQr 4. Hands-On Large Language Models: lnkd.in/dxaVF86w 5. AI Agents for Beginners: lnkd.in/dHvTmJnv 6. GenAI Agentshttps://lnkd.in/dEt72MEy 7. Made with ML: lnkd.in/d2dMACMj 8. Hands-On AI Engineering:lnkd.in/dgQtRyk7 9. Awesome Generative AI Guide: lnkd.in/dJ8gxp3a 10. Designing Machine Learning Systems: lnkd.in/dEx8sQJK 11. Machine Learning for Beginners from Microsoft: lnkd.in/dBj3BAEY 12. LLM Course: lnkd.in/diZgGACG 🗺️ Guides 1. Google's Agent Whitepaper: lnkd.in/gFvCfbSN 2. Google's Agent Companion: lnkd.in/gfmCrgAH 3. Building Effective Agents by Anthropic: lnkd.in/gRWKANS4. 4. Claude Code Best Agentic Coding practices: lnkd.in/gs99zyCf 5. OpenAI's Practical Guide to Building Agents: lnkd.in/guRfXsFK 📚Books: 1. Understanding Deep Learning: lnkd.in/dgcB68Qt 2. Building an LLM from Scratch: lnkd.in/g2YGbnWS 3. The LLM Engineering Handbook: lnkd.in/gWUT2EXe 4. AI Agents: The Definitive Guide – Nicole Koenigstein: lnkd.in/dJ9wFNMD 5. Building Applications with AI Agents – Michael Albada: lnkd.in/dSs8srk5 6. AI Agents with MCP – Kyle Stratis: lnkd.in/dR22bEiZ 7. AI Engineering: lnkd.in/gi-mQcXa 📜 Papers 1. ReAct: lnkd.in/gRBH3ZRq 2. Generative Agents: lnkd.in/gsDCUsWm. 3. Toolformer: lnkd.in/gyzrege6 4. Chain-of-Thought Prompting: lnkd.in/gaK5CXzD. 🧑🏫 Courses: 1. HuggingFace's Agent Course: lnkd.in/gmTftTXV 2. MCP with Anthropic: lnkd.in/geffcwdq 3. Building Vector Databases with Pinecone: lnkd.in/gCS4sd7Y 4. Vector Databases from Embeddings to Apps: lnkd.in/gm9HR6_2 5. Agent Memory: lnkd.in/gNFpC542 Repost for your network ♻️

    → View original post on X — @nandodf, 2026-04-04 11:30 UTC

  • 6 Prompts to Stress-Test Your Startup Idea
    6 Prompts to Stress-Test Your Startup Idea

    By

    @godofprompt

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    BREAKING: Claude can now refine your startup idea like Paul Graham evaluates YC startups (for free). Most ideas sound good. Few survive real scrutiny. Here are 6 insane Claude prompts that pressure-test your idea before you waste months. (Save before you build)

    → View original post on X — @godofprompt

  • Local AI Models: A Comprehensive Testing Guide

    By

    @scobleizer

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    Here's a decent report about all the local models that people should be trying out on various machines.

    → View original post on X — @scobleizer

  • Buzzy’s AI Agent Hunger Game Generates Perfect Videos Automatically

    By

    @aihighlight

    –

    140K people just watched Buzzy run an agent hunger game to build better videos. Five AI agents compete, every loss trains the system, and you never get a draft again. Only finished content. Buzzy Now (@Buzzy_now_AI) With Buzzy, you don't babysit AI to create videos step by step. You watch agents fight to compete for a perfect video. Every battle teaches the system. Every victory improves the next video. Seedance 2 + Agent hunger game = Guaranteed Perfect — https://nitter.net/Buzzy_now_AI/status/2040083467619418521#m

    → View original post on X — @aihighlight, 2026-04-04 09:24 UTC

  • Google Agent Skills: Engineering Best Practices für AI Coding Agents
    Google Agent Skills: Engineering Best Practices für AI Coding Agents

    By

    @datachaz

    –

    If you found this useful, a like or RT goes a long way 🦾 Follow me → @datachaz for insights on LLMs, AI agents, and data science! Charly Wargnier (@DataChaz) 🚨 You need to see this. @addyosmani from Google just dropped his new Agent Skills and it's incredible. It brings 19 engineering skills + 7 commands to AI coding agents, all inspired by Google best practices 🤯 AI coding agents are powerful, but left alone, they take shortcuts. They skip specs, tests, and security reviews, optimizing for "done" over "correct." Addy built this to fix that. Each skill encodes the workflows and quality gates that senior engineers actually use: spec before code, test before merge, measure before optimize. The full lifecycle is covered: → Define – refine ideas, write specs before a single line of code → Plan – decompose into small, verifiable tasks → Build – incremental implementation, context engineering, clean API design → Verify – TDD, browser testing with DevTools, systematic debugging → Review – code quality, security hardening, performance optimization → Ship – git workflow, CI/CD, ADRs, pre-launch checklists Features 7 slash commands: (/spec, /plan, /build, /test, /review, /code-simplify, /ship) that map to this lifecycle. It works with: ✦ Claude Code ✦ Cursor ✦ Antigravity ✦ … and any agent accepting Markdown. Baking in Google-tier engineering culture (Shift Left, Chesterton's Fence, Hyrum's Law) directly into your agent's step-by-step workflow! `npx skills add addyosmani/agent-skills` Free and open-source. Repo link in 🧵↓ — https://nitter.net/DataChaz/status/2040357775830814798#m

    → View original post on X — @datachaz, 2026-04-04 09:16 UTC

  • Addy Osmani’s Agent Skills: Engineering Best Practices for AI Coding Agents
    Addy Osmani’s Agent Skills: Engineering Best Practices for AI Coding Agents

    By

    @datachaz

    –

    🚨 You need to see this. @addyosmani from Google just dropped his new Agent Skills and it's incredible. It brings 19 engineering skills + 7 commands to AI coding agents, all inspired by Google best practices 🤯 AI coding agents are powerful, but left alone, they take shortcuts. They skip specs, tests, and security reviews, optimizing for "done" over "correct." Addy built this to fix that. Each skill encodes the workflows and quality gates that senior engineers actually use: spec before code, test before merge, measure before optimize. The full lifecycle is covered: → Define – refine ideas, write specs before a single line of code → Plan – decompose into small, verifiable tasks → Build – incremental implementation, context engineering, clean API design → Verify – TDD, browser testing with DevTools, systematic debugging → Review – code quality, security hardening, performance optimization → Ship – git workflow, CI/CD, ADRs, pre-launch checklists Features 7 slash commands: (/spec, /plan, /build, /test, /review, /code-simplify, /ship) that map to this lifecycle. It works with: ✦ Claude Code ✦ Cursor ✦ Antigravity ✦ … and any agent accepting Markdown. Baking in Google-tier engineering culture (Shift Left, Chesterton's Fence, Hyrum's Law) directly into your agent's step-by-step workflow! `npx skills add addyosmani/agent-skills` Free and open-source. Repo link in 🧵↓

    → View original post on X — @datachaz, 2026-04-04 09:16 UTC

  • EdgeClaw Reduces Token Usage 85% with New Skill System
    EdgeClaw Reduces Token Usage 85% with New Skill System

    By

    @aihighlight

    –

    85% token reduction, that is what EdgeClaw's new skill system delivers compared to the standard Claude Code loading phase. Open source teams are shipping faster than the labs right now. See what they built: github.com/OpenBMB/EdgeClaw Yukun Yan (@AIYKun) 🚀 [OpenClaw x Claude Code DAY 3 – Almost Done!] 🚀 Three more CC features—including the highly requested Buddy—are now live in EdgeClaw 2.2! 🦞 Try it now: github.com/OpenBMB/EdgeClaw Here is what we shipped today: 👇 ⚡️ ClawXskills: Progressive, high-efficiency skill calling. The loading phase now consumes just 15% of the original tokens! 🧠 ClawXcontext: Hierarchical context compression with on-demand expansion. Say goodbye to context bloat and lost information! 🐾 ClawXBuddy: Draw a random "blind box" to get your own unique companion pet! (Warning: No abandoning allowed! 🙅♂️❤️) The reconstruction of CC features is complete, but EdgeClaw’s evolution has just begun. We will keep pushing boundaries! 🌊🚀 #ClaudeCode #OpenClaw #EdgeClaw #LLMs #OpenSource — https://nitter.net/AIYKun/status/2040061511809520006#m

    → View original post on X — @aihighlight, 2026-04-04 08:51 UTC