Get oriented on how AI and LLMs work before building with them.

Reference this as you learn — it maps out the full AI landscape from narrow AI to LLMs.

Learn the taxonomy of agents before building one — knowing which type fits which problem saves time.

Real-world experience from intensive AI Agent training — practical and grounded.

Calibrate your perspective on what's real vs. overhyped before you start building.

Understand how your role as an engineer is shifting — and what skills will matter most.

Learn the protocols that move agents from prototype to production: MCP, A2A, and beyond.

Apply what you know about microservices to agent design — the patterns translate directly.

Understand the cultural shift happening in engineering teams — you'll be operating in this environment.

Learn to modularize agent capabilities into reusable skills — this is how you scale agent systems.

Straight from Anthropic's engineering team — the practical patterns behind agent design: when to use workflows vs autonomous agents, and how to engineer tools that agents can actually use reliably. (EXTERNAL)