Picking a model used to be a one-time decision. Today it is a per-request decision, and the difference in cost between a good and a great choice is often 10x for the same answer quality.
The problem with doing it by hand
Manual review does not scale past a handful of prompts. Changes pile up, context gets lost in chat threads and nobody can say which version is actually running in production. Worse, the feedback loop is measured in days, not seconds.
What we do instead
We treat prompts as code. Each change is a versioned commit with a diff, an owner and an automatic evaluation run. Nothing merges unless it holds up against real traffic.
Three rules we never break
Every prompt change runs against a golden dataset before merge.
Every production call is traced, with cost and latency attached.
Every deploy can be rolled back in one click, without a code release.
The best prompt is the one you can prove is better than the last one.
If you want to try this workflow on your own prompts, the free plan includes everything in this post. Start at zero, ship today.
