Silent Regressions Have No Stack Trace: A Minimal Prompt Eval Harness
A prompt regression is the only production bug that never throws an exception and never writes to your error log. When you change a prompt, the API still returns 200, the JSON still parses, and the latency chart still looks healthy, but the model quietly stops honoring a constraint it used to follow. The reliable fix is not more careful diff reading; it is a small eval harness with golden cases,…
A prompt regression is an insidious production defect that goes unnoticed because it does not generate any error messages or log entries. When a prompt changes, the API continues to respond with a 200 status code, the JSON still parses properly, and the system maintains its normal latency. However, the model starts disregarding constraints it previously followed, resulting in subtle quality issues.
The only reliable solution is not to perform a meticulous review of prompt changes, but rather to implement a minimal test harness that includes a set of golden cases, grading functions, and a baseline comparison mechanism. This approach catches regressions that manual testing often overlooks, as humans tend to focus on typical use cases while the problematic regressions manifest in edge cases and constraints.
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