Developer Builds 3-Stage Vetting System After AI Model Silently Corrupted Docs

A software developer writing for DEV Community describes how an AI model swap based on social media hype led to a week of corrupted API documentation on their docs site, with the error only caught after a reader flagged it. The incident revealed that the most dangerous model failures are subtle and plausible rather than loud and obvious. In response, the developer built a three-stage evaluation process — an interview, an observation period, and limited duty — that every new model must pass before gaining access to real work. The interview stage alone, taking roughly an hour, filters out more than half of hyped releases through tests covering format compliance, hallucination detection, scope discipline, latency, and accuracy on a known task. No model earns production access on launch day regardless of benchmark scores or viral reception.