6 GitHub Repositories Every AI Builder Should Bookmark in 2025
Top open-source resources for building LLMs, AI agents, and generative AI applications
If you're building real GenAI products, most GitHub repos are noise.
These six are different. They’re battle-tested, well-documented, and used by developers pushing AI into production.
1. Hands-On Large Language Models by Jay Alammar
Jay Alammar is one of the clearest voices in AI education. This repo contains all the code examples from his book Hands-On Large Language Models.
It’s packed with step-by-step notebooks covering everything from tokenizer basics to fine-tuning models like GPT and LLaMA.
Think of this as your LLM playground.
▫️ Best for: Engineers who want to really understand how LLMs work under the hood
▫️ Bonus: Includes chapters on retrieval, vector search, adapters, and LoRA
2. AI Agents for Beginners by Microsoft
Microsoft’s beginner-friendly course helps you go from ChatGPT tinkerer to full-stack agent builder.
It walks you through the concepts, architecture, and practical implementations to build your first AI agent.
▫️ Best for: Engineers who want to go from ChatGPT tinkerer to agent builder
▫️ Bonus: Comes with a learning plan, projects, and pre-trained models
3. GenAI Agents by Nir Diamant
This advanced repo covers AI agent design using LangChain, CrewAI, and ReAct. Topics include planning, tool use, long-term memory, and agent collaboration.
▫️ Best for: Builders ready to go beyond ReAct and AutoGPT
▫️ Bonus: Great explanations of agent architectures and decision flows
4. Prompt Engineering Guide by DAIR.AI
A living knowledge base of the best prompt engineering techniques. This repo includes curated research, practical guides, and real-world examples used by top LLM teams.
▫️ Best for: Founders, PMs, and devs who use LLMs daily and want to get 10x better at it
▫️ Bonus: Constantly updated, very well structured, and easy to reference
5. Awesome Generative AI Guide by Aishwarya Naresh Reganti
This is a curated list of the best GenAI tools, papers, jobs, and frameworks. Less code-heavy, but perfect for keeping up with trends and ecosystem changes.
▫️ Best for: Anyone building or investing in GenAI
▫️ Bonus: Includes hands-on notebooks, frameworks, and paper summaries
6. Agents Towards Production by Nir Diamant
This repo teaches you how to move agents from prototype to production. It covers authentication, logging, monitoring, evaluation, memory management, and error handling.
▫️ Best for: Engineers deploying AI in production
▫️ Bonus: End-to-end, code-first, and extremely actionable
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Thanks for sharing. My audience will love these. I've Restacked it for them 🌞
Very cool