Five Debugging Lessons From Trusting a 200 OK Response Too Much

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A developer discovered that a 200 OK HTTP status code from a free model API endpoint does not confirm which AI model actually responded, prompting a deeper look at silent routing and fallback behaviour. The article outlines five common misconceptions, including the false belief that a successful status code proves correct model delivery, that rate limits reflect billing issues, or that free endpoints require no personal logging. The author argues that token entitlements and compute allocations are separate systems that fail in distinct ways and should never share the same retry policy. Environment differences between local and remote machines — such as Python versions and PATH order — can silently affect behaviour and should be recorded alongside every API request. The piece concludes that maintaining a personal append-only provenance log is especially critical when using free endpoints, since no external invoice exists to verify what ran, when, or against which model.

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