Agent evaluation reaches ambiguous projects as reliability moves into the harness
After several days centered on executable feedback inside coding loops, today’s evidence broadens the control surface.
After several days centered on executable feedback inside coding loops, today’s evidence broadens the control surface.
Agent evaluations can test reliability more precisely by locating clarification, formal verification, and specialist review at the decisions where errors become expensive to reverse.
The day’s strongest work makes AI coding more usable by narrowing where the model is allowed to improvise and by adding checks that run on real behavior.
The clearest near-term builds add hard structure around what the model is allowed to produce and keep verification active after generation.