Your team has 30 prompts across 6 features, edited by 5 people. How do you manage prompts like production code?

Question

Accepted Answer

Treat prompts as what they are, production logic with an unusual editor population, and give them the code lifecycle with friction tuned so iteration survives. Versioning first: prompts live in source control as templates with typed variables, and every change is a diff with an author and a reason, the dashboard-edited prompt that nobody can reconstruct after an incident is the baseline failure here. Review and testing: every prompt edit triggers the owning feature eval suite automatically, results on the change request, a 100-case suite runs in about 5 minutes, and the gate is regression against baseline with per-slice deltas, because prompt edits classically fix the case someone was staring at and quietly break three others. For the 2 of my 5 editors who are not engineers, the interface matters: a playground where they iterate freely against sample cases, and a submit path that runs the same eval gate, review means the suite passed plus a colleague glance, which keeps PMs iterating without shipping vibes. Deployment: prompts deploy like config, decoupled from code, versioned, with canary, new version on say 10 percent of traffic with quality signals watched, and rollback as a config flip measured in seconds, which converts the worst prompt incident from an emergency deploy into a toggle. Tracing closes the loop: every production request logs its prompt version alongside model and parameters, so "answers got weird Tuesday" resolves to "v41 shipped Tuesday 14:00, here is the diff" in minutes, and A/B comparison of prompt versions on live traffic becomes possible because attribution exists. Two disciplines around the machinery: an owner per prompt, five people editing 30 prompts without ownership is how contradictory instructions accrete; and a monthly prune, because prompts grow by accretion of special cases until nobody knows which sentences still do anything, the eval suite is what makes deleting a sentence safe.

Answer

A prompt change passed the suite and still caused a production regression. What does the postmortem look for?

A coverage gap: the regressed slice was not in the suite. The production traces become new cases, and the interesting question is whether that slice was knowable in advance, and why canary quality signals did not catch it either.

Answer

The same behavioural rule now lives in 12 prompts. What do you do?

Shared template fragments with versioning, edit once, every consuming prompt suite runs, all owners see the change. Copy-paste rules drift; composition with testing does not.

Your team has 30 prompts across 6 features, edited by 5 people. How do you manage prompts like production code?

Your team has 30 prompts across 6 features, edited by 5 people. How do you manage prompts like production code?

The follow-ups they ask next

What the interviewer is listening for

What sinks the answer

If you genuinely do not know

Keep going with prompting

Knowing the answer is not the same as recalling it under pressure