Production AI Engineering in 2026

A practical map of production AI engineering across thirteen layers, including retrieval, inference, evaluation, LLMOps, safety, cost optimization, observability, governance, UX, agents, fine-tuning, organizational mechanics, and how to prioritize when you cannot do everything at once.

Most "AI engineering" content stops at prompts and models. The actual discipline is the set of deterministic control layers built around probabilistic systems. This is the long-form map: 13 areas, every corner case that goes wrong in production, and where to start when you have to fix it under pressure.