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Judgment gate — prompt, RAG, or fine-tune — step 1 of 4

Three failure modes, three levers

Before anyone opens a trainer, name the failure. Most "we should fine-tune" threads are really one of these three:

  1. Bad brief. The prompt never said the output must be one of flake | product-bug | needs-human, or it said it in a paragraph the model treats as flavor. Fix: rewrite the brief. Add a schema. Add two worked examples. Measure again.
  2. Missing documents. The label depends on a runbook, an allowlist, or yesterday's incident writeup that is not in the prompt. The model is guessing because the file is missing. Fix: retrieve the file. Fine-tune will freeze last quarter's guess into weights.
  3. Format or label drift. The brief is tight. The docs are present or irrelevant. The model still wanders — extra prose around the label, swapped synonyms, needs_human vs needs-human, a fourth label it invented. Fix: a reviewed example set and a specialist adapter, after you can show the prompt-only baseline on a held-out set.

The gate is evidence, not vibes. You need a short golden set you already scored under the current prompt. If prompt-only already hits the acceptance tests, you do not fine-tune. If RAG is the only thing that would have supplied a changing fact, you do not fine-tune. If the remaining miss is consistency on a stable job, you may.

Wrong CLEARED (the chapter pass) is fine-tuning a knowledge gap. That run can look "smarter" in a demo and then lie with confidence the first week a policy changes.