Turning cost, quality and latency into one math score for agent evaluation
Doc1000 · reddit · 2026-10-21
An author argues CTOs now want cost-efficient agents, not flashy demos. The method: define per-trace cost thresholds with penalties and weights, repeat for quality/latency/turns, combine dimensions via an exponential into a smooth convex score, then apply root squared loss to capture both average loss and variance — evaluating models, prompts, workflows, skills and tools on a single business-aligned number. Published on Towards Data Science.
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