Home / Applied AI / 01. AI Engineering / 13. Prompt Lifecycle Operations Prompt Lifecycle Operations¶ The chapters in this module, in reading order. # Chapter 00 Prompt Ops — The Five-Year-Old Version 01 Prompts as code — why the string in your source file is a production asset 02 The prompt registry — the recipe book that every trace can name 03 Versioning and rollback — every change has a SHA, a diff, and a way back 04 Review gates — who can edit a prompt, and what must happen first 05 Shadow and A/B testing — the trial bake before the real customers 06 Prompt drift detection — did the small wording fix change behavior? 07 Prompt observability — tracing a bad answer back to the exact recipe that ran 08 Prompt eval suites — the taste test that decides what ships 09 Multi-tenant prompts — one recipe book, many customers 10 Prompt feature flags — the dial that ramps and the switch that kills 11 Prompt incidents and rollback — the five-minute loop 12 Tooling landscape — what each prompt ops tool actually solves 13 Honest admission — what prompt ops still does not solve