Agents differ from deterministic software

An agent operates through a think, act, and observe loop and connects to memory, retrieval, and external tools. Testing only the final answer is therefore insufficient to establish quality.

Evaluation must examine decision trajectories, tool choice, error recovery, and compliance with boundaries. Staged deployment from sandbox to limited rollout, combined with logging and least privilege, reduces risky behavior.

Engineering agent quality

Agent quality needs several layers of evaluation. Unit tests for tools and retrieval, scenario tests for multi-step trajectories, and human review for sensitive judgment complement one another. Looking only at the final answer can hide poor tool choice or wasteful reasoning.

Context and memory are also risk sources. Excessive retention can threaten confidentiality, while incomplete memory can distort decisions. Teams must define what remains in a session, what enters long-term memory, and how users can correct or remove it.

After release, a sample of real trajectories should be evaluated continuously. A change to the model, tool, data, or instruction can alter behavior. Versioning and rapid rollback allow improvement without losing operational control.

Test the agent when conditions are difficult

A support agent may answer routine requests well, but what happens with an incomplete document, conflicting instruction, or failed tool? An evaluation set should cover these cases and show when the agent answers, asks for clarification, or hands work to a person. Task-completion rate alone is insufficient: a confident wrong action can cost more than a timely stop.

During a limited rollout, cap tool calls and cost per task while recording decision paths. Review failures with product and security teams before expanding: was the wrong source retrieved, the wrong tool selected, or a permission too broad? Fixing those causes lasts longer than adding more prompt instructions.

What must be clear before wider release?

Document success criteria, allowed tools, memory policy, human approval paths, and an emergency stop. A real but bounded pilot exposes the gap between an impressive demo and a dependable system.

This Liyan Knowledge article is an editorial synthesis based on the original source.View original source