An eval harness found what qualitative review couldn't: AI models are most confident when wrong

What happened

VentureBeat reports: An eval harness found what qualitative review couldn't: AI models are most confident when wrong. There is a step in the development process for large language model (LLM)-assisted tooling that most teams skip because it's tedious, time-consuming, and doesn't produce results visible to end users: Verifying that what the model is saying is actually correct. Not fluent, not coherent, not topically relevant — correct…

The technical detail

Read the original coverage at VentureBeat via the source link above for the complete details and primary quotes.

Market and competitive context

Cross-check release notes and official docs before changing production systems based on early reporting.