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hardScenarioDesignMidSeniorStaff

A model scored well in validation and performs badly in production, with no errors anywhere. What do you check first?

5 min readUpdated 2026-08-15

Answer

Short answer

Check whether training and serving compute the same features from the same definitions, because the usual cause is two implementations that disagree slightly. Nothing raises an error when they diverge - the model receives plausible numbers that mean something different from the ones it learned on.

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Likely follow-ups

  • Training averages a customer's last 30 days. What does serving have to be careful about?
  • How would you detect this without waiting for the business metric to fall?
  • What is the difference between this and drift, and does the fix differ?
  • Where would a feature store help, and where is it overkill?

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