Beyond Benchmarks: Evaluating Agent Reasoning in the Real World

Leaderboard scores are seductive and misleading. An agent that tops a public benchmark can still fail spectacularly on your specific workflows. Real-world evaluation requires a different approach.

Evaluate on your distribution

The only benchmark that matters is your own traffic. We help teams build eval sets from anonymized production data, so quality is measured on the tasks that actually matter to them.

Measure trajectories, not just outcomes

A correct answer reached through a reckless path is a latent failure. We score the full trajectory — the plan, the tools used, the recoveries from error — not just the final output.

Close the loop

Evaluation is only useful if it drives change. We wire eval results into deployment gates, so regressions block releases and improvements are provable.

Rigorous, continuous evaluation is what separates agents that impress in a demo from agents you can depend on.