Two agents answer the same question correctly. One made two tool calls; the other pulled irrelevant context and called the same API twice. Your pass/fail suite scores both 100 percent, and you pay for the difference in tokens and rate limits. This talk scores the answer with an LLM judge and a rubric, then scores the path the agent took to get there, so waste that produces a correct answer stops being invisible. You leave with the rubrics, the trajectory checks, and code to run them in CI.

Outline:
• Introduction: The Binary Metrics Problem
• Part 1: LLM-as-Judge Evaluation
• Part 2: Trajectory Evaluation
• Part 3: Combining Both Techniques