ombharatiya/ai-system-design-guide resource

Health v2 · maintenance only

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Adoption not part of the score

2885 stars · 579 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

An open-source, continuously updated guide to AI system design covering RAG architectures, LLM engineering, agentic AI, MCP/A2A protocols, and evaluation. It serves as both a production reference and an interview preparation resource with a 128-question interview bank.

Use cases

• prepare for AI system design interviews
• learn how to design RAG architectures for production
• understand agentic AI workflows and MCP protocols
• study LLM evaluation and model selection patterns
• review staff-level AI engineering interview questions
• learn production patterns for building AI systems

When to choose

• you are preparing for AI/ML engineering or forward-deployed engineer interviews
• you want a curated, continuously updated reference on production AI system design
• you need practical patterns for RAG, agents, and evals in one place

When to avoid

• you need executable code or a working framework rather than written guidance
• you want deep academic treatment of machine learning theory
• you need vendor-specific official documentation

Facets

learning-resource · maturity active

documentation rag llm-inference agent-framework prompt-engineering artificial-intelligence large-language-models tutorials education system-design interview-preparation ai-engineering evals mcp guide retrieval-augmented-generation ai-agents web-server

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markdown · JSON · MCP: product_card(name="ombharatiya/ai-system-design-guide")