Agentic Engineering Handbook — Development skill for Claude Code

Agentic Engineering Handbook

The definitive OpenAI, Anthropic, Google, MCP, Harness, Evals, and Production Agent Systems learning roadmap.

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Why This Repository?

The AI industry has entered the **Agentic Era**. Building production-grade AI systems now requires mastering agents, tool use, MCP, memory, long-running workflows, coding agents, agent harnesses, evals, and safety — but the knowledge is scattered across OpenAI blogs, Anthropic engineering posts, SDK docs, cookbooks, and research papers.

This repository consolidates **217 curated resources** into one structured learning roadmap.

**The goal: Become a world-class Agentic Engineer.**

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How To Use This Handbook

Pick the path that matches your starting point:

• New to agents: follow the Learning Roadmap through the core Phases 0–6, then continue to Phase 7 for advanced coursework. Treat each Read First, Then Read, and Build Exercise as a checklist.
• Already building LLM apps: start at Phase 2 or Phase 3, then fill gaps in agent loop, tool calling, evals, and production engineering.
• Trying to build projects: use the phase-level Build Exercise prompts, then branch into Applied Practice Tracks for coding agents, security, code review, or SRE.
• Looking for references: jump to the Full Reading Table. Read P0 first, use P1 for implementation detail, and keep P2 as optional background.

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AI Engineering Skills Map

Start with Andrew Ng's [The AI Engineering Skills Map](https://www.linkedin.com/pulse/ai-engineering-skills-map-andrew-ng-m479c/) (P