Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
AI system design guide for engineers building production AI systems and evals.
| Date | Stars |
|---|---|
| 2026-07-24 | 2291 |
| 2026-07-25 | 2304 |
| 2026-07-28 | 2304 |
| 2026-07-30 | 2304 |
| 2026-08-06 | 2304 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# 🧠 AI System Design Guide ### The Complete Interview & Production Reference <p align="center"> <a href="https://www.aidaddy.tech"><img src="https://img.shields.io/badge/Read%20it%20online%20%E2%86%92-7C3AED?style=for-the-badge&logo=bookstack&logoColor=white" alt="Read the guide online at aidaddy.tech"></a> </p> <p align="center"> <sub>🌐 Instant search, linked chapters, and a cleaner reader at <b><a href="https://www.aidaddy.tech">aidaddy.tech</a></b>. ⭐ Star the repo to support the work.</sub> </p> <p align="center"> <a href="https://github.com/ombharatiya"><img src="https://img.shields.io/badge/Follow%20on%20GitHub-ombharatiya-181717?style=for-the-badge&logo=github" alt="Follow on GitHub"></a> <a href="https://x.com/ombharatiya"><img src="https://img.shields.io/badge/Follow%20on%20Twitter-@ombharatiya-1DA1F2?style=for-the-badge&logo=x" alt="Follow on Twitter"></a> <a href="https://linkedin.com/in/ombharatiya"><img src="https://img.shields.io/badge/Connect%20on%20LinkedIn-ombharatiya-0A66C2?style=for-the-badge&logo=linkedin" alt="Connect on LinkedIn"></a> </p> <p align="center"> <b>If this guide helps you, follow <a href="https://github.com/ombharatiya">@ombharatiya</a> on GitHub, <a href="https://x.com/ombharatiya">X</a>, and <a href="https://linkedin.com/in/ombharatiya">LinkedIn</a> to get notified when new chapters, model refreshes, and interview prompts ship.</b> </p> <p align="center"> <a href="https://github.com/ombharatiya/ai-system-design-guide/commits/main"><img src="https://img.shields.io/github/last-commit/ombharatiya/ai-system-design-guide?label=updated&color=blue" alt="Last commit"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/License-MIT-green.svg" alt="License"></a> <a href="#-contributing"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg" alt="PRs Welcome"></a> <a href="https://github.com/ombharatiya/ai-system-design-guide/stargazers"><img src="https://img.shields.io/github/stars/ombharatiya/ai-system-design-guide?style=social" alt="Stars"></a> <a href="https://github.com/ombharatiya/ai-system-design-guide/graphs/contributors"><img src="https://img.shields.io/github/contributors/ombharatiya/ai-system-design-guide?color=blueviolet" alt="Contributors"></a> <a href="https://github.com/ombharatiya/ai-system-design-guide/issues"><img src="https://img.shields.io/github/issues/ombharatiya/ai-system-design-guide?color=orange" alt="Open issues"></a> </p> > **The living reference for production AI systems.** Continuously updated. Interview-ready depth. A practical, continuously updated guide to AI system design, RAG architectures, LLM engineering, agentic AI, MCP and A2A protocols, and AI engineering interview preparation. Covers production patterns, model selection, evaluation, and real-world case studies from staff-level interviews. **New here?** Jump to the [116-question Interview Bank](00-interview-prep/01-question-bank.md), the [RAG Fundamentals chapter](06-retrieval-systems/01-rag-fundamentals.md), or pick the [right LLM for production](02-model-landscape/01-model-taxonomy.md). --- ## 📚 Quick Navigation | I want to... | Start here | |--------------|------------| | **Prepare for interviews** | [Question Bank](00-interview-prep/01-question-bank.md) → [Answer Frameworks](00-interview-prep/02-answer-frameworks.md) | | **Learn AI systems fast** | [LLM Internals](01-foundations/01-llm-internals.md) → [RAG Fundamentals](06-retrieval-systems/01-rag-fundamentals.md) | | **Build production RAG** | [Chunking](06-retrieval-systems/02-chunking-strategies.md) → [Vector DBs](06-retrieval-systems/04-vector-databases.md) → [Reranking](06-retrieval-systems/06-reranking-strategies.md) → [Production RAG](06-retrieval-systems/14-production-rag-at-scale.md) | | **Advanced retrieval** | [Contextual Retrieval](06-retrieval-systems/10-contextual-retrieval.md) → [ColBERT](06-retrieval-systems/11-late-interaction-colbert.md) → [Multi-modal RAG](06-retrieval-systems/12-multi
Excerpt of 24,215 characters
Read on GitHub
166
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:63beaf1bf98b52fe, topic:agentic-ai, topic:agentic-workflow, readme:agentic
matched fp:63beaf1bf98b52fe, topic:llm
matched fp:63beaf1bf98b52fe, topic:natural-language-processing
matched fp:63beaf1bf98b52fe, topic:rag