How Limiting AI Responses Improved Resume Review Accuracy and Trust

A development team building a resume review tool found that the core challenge was not making AI generate useful feedback, but preventing it from speaking when uncertain. Their original tool used a large language model to produce lengthy critiques, which blended high-confidence insights with weak guesses in the same authoritative tone. The team rebuilt the reviewer around Jev, a structured decision model that returns probabilities on narrow questions rather than generating open-ended prose. This shift reduced hallucinated advice, such as fabricated performance metrics, and gave users clearer signals about which feedback was reliable. The key lesson from the project was that effective AI review depends on enforcing silence until the model has sufficient confidence to earn the right to respond.