A skills set and methodology for coding agents: clarify the task, plan, write tests, then code. The agent works with more discipline.
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224 living projects — from agent frameworks to prompt-injection defense. Each comes with our own note: why it matters, who it is for and how to start in three steps.
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A service that turns any website into clean Markdown or structured data for models. It can search, scrape, crawl a whole site and even click through a page.
A small Microsoft utility that converts PDF, Word, PowerPoint, Excel and other files into Markdown that is easy to hand to a language model.
An open coding agent for the terminal with a desktop app. It is not tied to one provider: plug in whichever models you have.
A toolkit for spec-driven development: principles and a spec first, then a plan and tasks, and only then code. Works with several coding agents.
OpenAI's lightweight coding agent that runs in the terminal and works on your project's code. Written in Rust.
Categories
Agent frameworksFrameworks and orchestration: what agents and multi-agent systems are built from.23 repositoriesCoding agents & CLIAgents that write code in the terminal and editor, and the methods for working with them.21 repositoriesMCPThe Model Context Protocol spec, official SDKs and the best servers.20 repositoriesOpen models & inferenceOpen weights, local runs, fast inference and fine-tuning.38 repositoriesRAG & vector DBsSearch over your own data: document parsing, crawlers, vector databases, knowledge graphs.19 repositoriesEvals & observabilityHow to measure a model or agent and see what happens inside it.17 repositoriesPrompting & contextPrompts, structured output, skills and context engineering.16 repositoriesVoice, video, multimodalSpeech recognition and synthesis, voice agents, images and video.19 repositoriesAutomationNo-code workflows, browser and computer-use agents.15 repositoriesAwesome lists & learningCourses, books and awesome lists worth starting with.21 repositoriesSecurityPrompt injection, guardrails, red teaming and agent scanners.15 repositoriesMissing your favorite?Suggest a repository — we will review it and add it if it earns a spot.Suggest a repo →
Catalog
25 repositories
A large collection of ready-made LLM apps: agents, RAG systems and skills for coding agents. Every template can be run and taken apart piece by piece.
A free 21-lesson Microsoft course that goes from generative AI basics and prompting to working applications. Each lesson ships with code.
A 12-week course on classic machine learning: 26 lessons and 52 quizzes. The foundation that makes modern models easier to understand.
A three-part LLM roadmap: fundamentals, the LLM Scientist (building models) and the LLM Engineer (building apps). Topics come with Colab notebooks.
A Microsoft course of 18 lessons on building AI agents: tools, memory, planning, multiple agents. Code examples live in the code_samples folder.
A collection of examples and guides for the OpenAI API: from basic requests to function calling and RAG. Most code is Python.
More than 60 PyTorch implementations of research papers with notes next to the code: transformers, optimizers, GANs, reinforcement learning. The website shows code and notes side by side.
A minimal, readable GPT implementation in PyTorch by Andrej Karpathy: training from scratch and fine-tuning in a few hundred lines. The best way to see how a language model works.
The whole path from zero to your own ChatGPT-like chat in one repo: tokenizer, pretraining, fine-tuning and UI. Designed to train for roughly a hundred dollars.
Recipes from Anthropic as notebooks: tools, RAG, multimodality, subagents and other techniques for working with Claude. The code is ready to copy into your projects.
Anthropic's interactive prompting course: 9 chapters with exercises where you can try things right away and see how Claude's answer changes.
More than 90 projects on LLMs, RAG and agents, sorted by difficulty from beginner to advanced. Each project has its own write-up and code.
A free Hugging Face course on agents in four units: fundamentals, the smolagents, LlamaIndex and LangGraph frameworks, agentic RAG and a final benchmark assignment.
GPT-2 training in plain C and CUDA, no PyTorch. Shows what happens under the hood while a model learns.
More than 40 runnable notebooks with RAG techniques, from basic retrieval to advanced setups. Each one has the idea, the code and references.
Code for every example in Jay Alammar and Maarten Grootendorst's book Hands-On Large Language Models. Twelve chapter notebooks, from tokens and transformers to RAG, multimodality and fine-tuning.
Andrej Karpathy's video course: you code neural networks from scratch, from backpropagation up to a GPT-style language model. Lectures come with notebooks.
Code notebooks for François Chollet's Deep Learning with Python (third edition, on Keras 3). Runs on JAX, TensorFlow or PyTorch. Legacy notebooks for the two earlier editions are included.
A tiny autograd engine with a small neural net on top and a PyTorch-like API. Very little code, yet it shows exactly how backpropagation works.
Companion materials for Chip Huyen's book AI Engineering: table of contents, chapter summaries, study notes, prompt examples and case studies. The book covers adapting foundation models to real tasks.
A free MCP course from Microsoft: from basics and security to first servers, with examples in C#, Java, JavaScript, Rust, Python and TypeScript.
A project template for context engineering with Claude Code: rules in CLAUDE.md, code examples and commands that turn a feature description into a detailed brief and then into a working implementation.
Code for the first edition of Sebastian Raschka's Python Machine Learning (2015): classic algorithms in NumPy and scikit-learn, from the perceptron to clustering. A newer edition lives in a separate repo.
Materials for research on indirect prompt injection: how malicious instructions in emails, web pages and code break LLM-integrated apps. Includes attack demos.
The archive of the OWASP Top 10 for LLM Applications: the ten main risks with descriptions and mitigations. The current 2026 release has moved to the GenAI Security Project repository.
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