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Open-Source AI Agent Book Delivers 92 Hands-On Experiments and Architecture Principles
An open-source textbook breaks down AI agent engineering into 10 detailed chapters based on the formula Agent = LLM + Context + Tools. It includes 92 executable lab experiments covering Model Context Protocol, prompt distillation, and reinforcement learning.
Why it matters. Provides an end-to-end open-source roadmap for building, training, and evaluating production-grade AI agents across web, voice, and robotics.