Your outputs changed in style and quality overnight with no deploy. You suspect the provider updated the model. How do you confirm it and respond?

30-second answerSay your answer out loud first, then reveal.

Check the evidence: response metadata (model version fields), provider changelogs and status pages, and whether you're using an alias. Rerun your golden eval suite now and compare with the last baseline. Look at production metrics (output lengths, refusal rates, format errors, judge scores) for a step change at a specific time. Respond by pinning to the previous dated version if it's still available, adapting prompts for the new behaviour if not, and adding scheduled evals and drift alerts so you detect it within hours next time.

Confirmation steps

Metadata: does the API response report a different model version? Were you using an alias like "-latest"?
Timeline: plot output token length, JSON failure rate, refusal rate and judge scores. Is there a step change at a specific timestamp?
Controlled test: run the golden set against the current endpoint and (if available) the pinned old version, then diff.
Provider communications: release notes, deprecation emails, support ticket.

Response

Situation	Action
Old pinned version still available	Pin to it immediately; evaluate the new version properly before migrating
Only the new version is available	Rapid prompt adaptation using failing eval cases; consider an alternative model; tighten validation
Regression only in some features	Route those features to a different model temporarily

Prevention: always pin dated versions; nightly scheduled evals against production config; drift monitors on output statistics; a model-change runbook.

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Your outputs changed in style and quality overnight with no deploy. You suspect the provider updated the model. How do you confirm it and respond?

Confirmation steps

Response

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