Demystifying evals for AI agents

Demystifying evals for AI agents

Good evaluations keep agents useful, predictable, and less likely to surprise your users. I’ve seen teams move fast with manual testing and dogfooding, get excellent early feedback, then suddenly hit a wall once the agent scales, where every change feels risky. That’s where evals earn their keep.

At their core, an eval is simple: give input, apply grading logic, measure success. But agents complicate things because they act over many turns, call tools, and change state as they go. That means failures can cascade, and sometimes models find loopholes in a test that look like a failure on paper but actually help the user (yes, that weird Opus 4.5 example exists).

A few practical takeaways from Anthropic’s work that I keep coming back to:
– Start by deciding what success means. Early evals force clarity, preventing two engineers from shipping different behaviors on edge cases.
– Use a mix of graders, code-based, model-based, and human, depending on the task. For coding agents, deterministic tests that run the code are golden, because passing tests is an honest signal.
– Run two suites, capability and regression, for different goals. Capability suites help hill-climb new behaviors, regression suites protect against backsliding once things are stable.
– Evals compound value over time. They make model upgrades faster, turn product-research conversations into concrete metrics, and let you monitor latency, token use, and errors against fixed tasks.

Teams like Descript and Bolt AI evolved from manual checks to automated grading with periodic human calibration, and that transition changed how fast they could improve. If you’re building agents, don’t treat evals as a tax, treat them as an investment that pays dividends later.

Read the full Anthropic piece here: https://www.anthropic.com/engineering/demystifying-evals-for-ai-agents

Looking ahead, evals will become the backbone for safer, more reliable agents, and once you start, you’ll wonder how you ever shipped without them.