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12 Awesome GitHub repos to upgrade your AI coding Coding is the field where AI is welcomed with open arms. Here’s a collection to help you take your AI-assisted coding workflows to the next level of convenience and efficiency: 1. Smol Developer → https://github.com/smol-ai/developer A lightweight AI “junior dev” that takes your product spec and automatically scaffolds or helps you build full codebases 2. Tabby → https://github.com/TabbyML/tabby A self-hosted AI coding assistant that runs locally as an alternative to GitHub Copilot. Easy to integrate, GPU-friendly, and doesn’t rely on the cloud 3. Beads (bd) Issue Tracker → https://github.com/steveyegge/beads Gives coding agents long-term memory, letting them organize, plan, and execute complex tasks reliably across sessions 4. MetaGPT → https://github.com/FoundationAgents/MetaGPT A multi-agent framework that imitates a software company team using LLMs. It assigns AI agents roles like PM, Architect, and Developer to produce user stories, designs, specs, and final code 5. Open Interpreter → https://github.com/openinterpreter/open-interpreter Gives you ChatGPT’s coding power with full local control – no limits, no sandbox – so you can automate, analyze, and create anything right from your desktop through a chat interface 6. OpenSpec → https://github.com/Fission-AI/OpenSpec A lightweight, spec-driven development tool that helps humans and AI agree on what to build before any code is written 7. PR-Agent → https://github.com/qodo-ai/pr-agent An AI code reviewer that automatically reviews, describes, and improves pull requests across GitHub, GitLab, and other platforms 8. BabyAGI → https://github.com/yoheinakajima/babyagi A self-building AI framework that gives agents the ability to write, manage, and refine their own functions, turning them from passive tools into active, self-building systems 9 ...⬇️ Subscribe to the Turing Post: https://www.turingpost.com/subscribe – your shortcut to deep, clear AI analysis
posted an update 1 day ago
12 Awesome GitHub repos to upgrade your AI coding Coding is the field where AI is welcomed with open arms. Here’s a collection to help you take your AI-assisted coding workflows to the next level of convenience and efficiency: 1. Smol Developer → https://github.com/smol-ai/developer A lightweight AI “junior dev” that takes your product spec and automatically scaffolds or helps you build full codebases 2. Tabby → https://github.com/TabbyML/tabby A self-hosted AI coding assistant that runs locally as an alternative to GitHub Copilot. Easy to integrate, GPU-friendly, and doesn’t rely on the cloud 3. Beads (bd) Issue Tracker → https://github.com/steveyegge/beads Gives coding agents long-term memory, letting them organize, plan, and execute complex tasks reliably across sessions 4. MetaGPT → https://github.com/FoundationAgents/MetaGPT A multi-agent framework that imitates a software company team using LLMs. It assigns AI agents roles like PM, Architect, and Developer to produce user stories, designs, specs, and final code 5. Open Interpreter → https://github.com/openinterpreter/open-interpreter Gives you ChatGPT’s coding power with full local control – no limits, no sandbox – so you can automate, analyze, and create anything right from your desktop through a chat interface 6. OpenSpec → https://github.com/Fission-AI/OpenSpec A lightweight, spec-driven development tool that helps humans and AI agree on what to build before any code is written 7. PR-Agent → https://github.com/qodo-ai/pr-agent An AI code reviewer that automatically reviews, describes, and improves pull requests across GitHub, GitLab, and other platforms 8. BabyAGI → https://github.com/yoheinakajima/babyagi A self-building AI framework that gives agents the ability to write, manage, and refine their own functions, turning them from passive tools into active, self-building systems 9 ...⬇️ Subscribe to the Turing Post: https://www.turingpost.com/subscribe – your shortcut to deep, clear AI analysis
posted an update 8 days ago
5 Lectures and keynotes defining AI right now If you want to understand the multifaceted AI landscape in 2025 and see where the field is heading – start with (or revisit) these legendary talks. They can help you capture what’s happening in AI from multiple angles: 1. Andrej Karpathy: Software Is Changing (Again) → https://www.youtube.com/watch?v=LCEmiRjPEtQ Unveils Software 3.0 – a paradigm where LLMs are the new computers, programmed with prompts instead of code. The key: developers must now master coding, training, and prompting as AI becomes the heart of software building 2. Richard Sutton, The OaK Architecture: A Vision of SuperIntelligence from Experience → https://www.youtube.com/watch?v=gEbbGyNkR2U Unveils the OaK (Options and Knowledge) architecture – a model-based RL framework for continual intelligence, where every component learns, meta-learns & builds hierarchical abstractions 3. GTC March 2025 Keynote with NVIDIA CEO Jensen Huang → https://www.youtube.com/watch?v=_waPvOwL9Z8 Dives into the accelerated computing and the importance of Physical AI. From the Blackwell GPU architecture & AI factories to breakthroughs in agentic AI & robotics, Jensen Huang explains how NVIDIA aims to power every layer of the AI ecosystem 4. Yann LeCun "Mathematical Obstacles on the Way to Human-Level AI" → https://www.youtube.com/watch?v=ETZfkkv6V7 Yann LeCun always argues we need a new path to machines that reason about the world – not LLMs or RL. So this lecture is about self-supervised systems with world models, planning, memory and energy-based learning 5. Andrew Ng: State of AI Agents → https://www.youtube.com/watch?v=4pYzYmSdSH4 Highlights one of the most pressing topics of 2025 – agents, explaining why most effective AI agents rely on simple, linear workflows built from modular “Lego-brick” tasks + what predicts AI startup success in the new agent era Subscribe to the Turing Post: https://www.turingpost.com/subscribe –your shortcut to deep, clear AI analysis
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