adongwanai/AgentGuide

# Technical Summary Provides a systematic, job-market-oriented learning pathway covering the full AI Agent tech stack—from LangGraph/LangChain frameworks and advanced RAG techniques (GraphRAG, reranking) to multi-agent orchestration and context engineering strategies. Distinguishes between algorithm (research-focused, model optimization via SFT/LoRA/RLHF) and engineering (production systems, retrieval pipelines, deployment) career tracks, with curated open-source projects and 1000+ interview problems tied to job preparation. The guide integrates vector databases, embedding models, and workflow orchestration tools (Dify, n8n) while emphasizing portfolio-building through complete end-to-end systems—RAG agents, multi-agent workflows, web automation—rather than isolated demos, designed for both researchers publishing papers and engineers shipping production services.

2,340 stars. Actively maintained with 10 commits in the last 30 days.