The coolest repositories on GitHub — AI agents, prompting resources, local models, dev tools — each with a plain-English take on why it matters. The shelf reshuffles every day, so tomorrow's top picks won't be today's. All free, all open source.
The original prompt collection
The repo that proved prompts were worth collecting: hundreds of 'Act as a…' personas that defined early prompt sharing. A time capsule and a starting point — the craft has moved on (that's where we come in), but this is where it began.
One man's public quest to become a Google engineer
John Washam's complete self-study computer science curriculum, built while grinding toward a big-tech job and shared with the world. Equal parts study plan and motivation — the repo that proves the path is walkable.
Agents as flowcharts you can actually debug
LangGraph models an AI agent as a graph — nodes think, edges decide where to go next, and you can checkpoint or rewind any step. It's what production teams reach for when 'a loop around an LLM' stops being reliable enough.
Turn your old devices into an AI cluster
Exo lets you run big models across whatever hardware you have lying around — MacBooks, phones, Raspberry Pis — automatically splitting the work between them. Frontier-lab ambition, garage-sale hardware.
One API for every AI model
LiteLLM lets you call 100+ models — OpenAI, Anthropic, Google, local Ollama — through one consistent interface, with budgets, fallbacks, and spend tracking built in. The plumbing every multi-model app ends up needing.
Leaked system prompts from thousands of custom GPTs
A giant collection of the hidden instructions behind popular custom GPTs. Ethically gray at the edges, but as prompt education it's unmatched — you learn more from reading fifty real system prompts than from any tutorial.
Chat with your documents, privately
AnythingLLM turns your PDFs, notes, and websites into a private AI knowledge base you can chat with — local models welcome. One of the smoothest 'RAG in a box' experiences going.
A command-line arsenal of battle-tested prompts
Fabric collects hundreds of curated 'patterns' — extract wisdom, summarize, analyze a paper — and pipes them through any AI from your terminal. It treats prompts as reusable tools, which is exactly the right way to think about them.
The Swiss-army framework that defined LLM apps
LangChain coined half the vocabulary of modern AI development — chains, retrievers, memory — and connects language models to basically everything. Sprawling and opinionated, but its cookbook of patterns is a genuine education.
PewDiePie's self-hosted AI workspace — yes, really
Felix built a full AI workspace — chat, agents, deep research, email, notes — that runs entirely on your own machine, then open-sourced it. 77k stars in three weeks. The 'own your AI instead of renting it' philosophy, shipped as working code.
The free textbook of prompt engineering
DAIR.AI's guide covers every major prompting technique — few-shot, chain-of-thought, self-consistency — with papers and examples to back each one. If you want the theory behind why good prompts work, it's here, free, in ten languages.
An autonomous coding agent inside VS Code
Cline plans, edits files, runs commands, and uses your browser — with a human-approval gate on every step. It's one of the best showcases of what agentic coding feels like when you stay in the loop.
An open-source AI software engineer
OpenHands (formerly OpenDevin) gives an AI a terminal, browser, and code editor, then lets it fix issues and ship pull requests like a junior dev. Watching it work is a preview of how software gets built next.
A gorgeous ChatGPT-style interface for your local models
Open WebUI gives your self-hosted models the polished chat experience they deserve — conversations, documents, voice, image generation, multi-user — all offline-capable. Pair it with Ollama and you've replaced a subscription.
Microsoft's framework for AI agents that talk to each other
AutoGen lets you build teams of AI agents that debate, delegate, and check each other's work before answering you. It pioneered the multi-agent conversation pattern most frameworks now copy. Great starting point if one AI isn't enough.
Run powerful AI models on your own machine with one command
Ollama made local AI boring in the best way: 'ollama run llama3' and you're chatting with a model that never leaves your laptop. It's the de-facto standard for private, offline, zero-subscription AI. If you try one local-AI tool, try this.
The research agent that fixes real GitHub issues
From Princeton researchers: SWE-agent takes an actual GitHub issue and autonomously produces the fix, and its papers taught the field that the *interface* you give an AI matters as much as the model. Where a lot of agent best practices were born.
Build a language model from first principles
Sebastian Raschka's book-as-repo walks you through implementing a GPT-style model line by line in PyTorch — pretraining, fine-tuning, everything. The deepest 'no magic' understanding of LLMs you can get.
The open-source Firebase that AI apps love
Postgres, auth, storage, and realtime APIs in one open-source package. Supabase became the default backend of the AI-app boom for a simple reason: it turns weekend projects into products. (This very site runs on it.)
Microsoft's free 21-lesson generative AI course
A structured, genuinely beginner-friendly path through generative AI: prompting, RAG, agents, fine-tuning — with videos and code in multiple languages. The syllabus your 'how do I start with AI?' friend is looking for.
The CLI behind LM Studio's local model magic
LM Studio is the friendliest desktop app for running models locally; lms is its command-line companion for loading, serving, and scripting those models. Great bridge from 'clicking around' to automating your local AI.
Learn by rebuilding the tools you use
A master list of tutorials for building your own Redis, Git, Docker, database, or programming language from scratch. The single best repository for turning 'I use it' into 'I understand it.'
The self-taught LLM engineer's curriculum
A complete course for going from developer to LLM engineer: fundamentals, fine-tuning, quantization, deployment — with notebooks for everything. Regularly updated, ruthlessly practical, entirely free.
The framework behind half the modern web
Next.js is the React framework that powers a staggering share of new websites — including this one. Server components, instant deploys, and enough momentum that AI tools generate Next.js code by default.
How the big AI tools really prompt their models
The extracted system prompts of Cursor, v0, Devin, and other famous AI products. Reading how professional teams structure instructions, tools, and guardrails is the fastest masterclass in serious prompt architecture.
The repo that started the autonomous-agent craze
AutoGPT was the first project to ask 'what if GPT could give itself its own to-do list?' — and the internet lost its mind. Today it's a full platform for building agents that plan, act, and self-correct. Historically important, still evolving fast.
The most-starred repo on GitHub — free coding education
freeCodeCamp has taught millions to code with free certifications in web development, Python, and machine learning. It tops GitHub's star charts because it might be the highest-impact educational project on the internet.
The legendary Stable Diffusion interface
The scrappy web UI that put image generation in everyone's hands and accumulated a decade of features in two years. ComfyUI has the momentum now, but A1111 remains the most approachable on-ramp to local image AI.
Desktop AI chat that runs on anything
GPT4All was among the first projects to make local models genuinely easy: download an app, pick a model, chat — no GPU required. Still one of the gentlest introductions to private AI.
Visual maps for every developer career path
Interactive roadmaps showing exactly what to learn — and in what order — for frontend, backend, DevOps, AI engineering, and more. One of the most-starred repos on GitHub because it answers the eternal question: 'what next?'
Anthropic's own hands-on prompting course
A nine-chapter interactive tutorial from the people who make Claude, teaching prompt construction with exercises and answer keys. Straight-from-the-source technique — most of it transfers to any model.
The engine that made local AI possible
This is the legendary C++ project that squeezed billion-parameter models onto laptops and phones, spawning the entire local-AI ecosystem — Ollama included. Deeply technical, endlessly optimized, and quietly running inside half the AI apps you've heard of.
Let your AI drive a real web browser
Browser-use gives language models eyes and hands on the web: it reads pages, clicks buttons, fills forms, and completes tasks on real sites. It's the missing piece between 'AI that talks about the web' and 'AI that uses it.'
Node-based image generation for power users
ComfyUI turns AI image generation into a visual circuit board: wire nodes together to control every step of the pipeline. Steeper than a prompt box, but it's how the most impressive AI art workflows actually get built.
Serve AI models at production speed
vLLM is what companies use when they need to serve language models to thousands of users without melting their GPUs. Its PagedAttention trick massively increased throughput and became an industry standard overnight.
The editor the world writes code in
VS Code is the most-used code editor on earth and one of the most successful open-source projects ever. Every AI coding tool you've heard of is either an extension of it or a fork of it — understanding it is understanding the terrain.
Andrej Karpathy's tiny, readable GPT
The simplest serious GPT training code in existence — a few hundred lines you can actually read, from one of the field's great teachers. Pair it with his YouTube lectures and you'll understand transformers better than most engineers.
The virtual whiteboard everything sketches on
Excalidraw is the hand-drawn-style diagramming tool that became the internet's shared whiteboard — open-source, end-to-end encrypted collaboration, zero accounts. Perfect for sketching how your agents talk to each other.
Assemble a crew of role-playing AI agents
CrewAI's big idea is casting: give each agent a role, a goal, and a backstory, then let the crew collaborate like coworkers. It made multi-agent workflows feel like writing a job description instead of code. One of the fastest-growing agent frameworks.
Build your own AI code assistant
Continue is the open-source alternative to Copilot that lets you wire ANY model — local or cloud — into VS Code and JetBrains, with custom rules, docs, and prompts. The escape hatch from assistant lock-in.
The API client that keeps your data on your machine
Bruno is the open-source Postman alternative that stores collections as plain files in your git repo — no cloud, no accounts, no sync fees. A model example of local-first developer tooling done right.
Pair programming with AI in your terminal
Aider is the beloved open-source AI coding companion: it maps your git repo, makes surgical edits, and commits with clean messages. Its benchmark leaderboards are also required reading for anyone comparing coding models.
Build AI apps on a visual canvas
Dify is an open-source platform where you assemble chatbots, agents, and workflows by dragging blocks instead of writing glue code — then ship them with monitoring included. A favorite for teams who want AI apps without an ML team.
Anthropic's agentic coding tool, in your terminal
Claude Code puts a frontier model directly in your terminal where it can read your codebase, run commands, and ship real changes. The docs double as a masterclass in how to prompt an agent well — worth reading even if you use something else.
Most of these work even better with the right prompts. NeLocker is a free library of field-tested prompts for every AI tool on this list.
Browse the vault →