Developer Guide Warns AI Agent Evals Are Flawed Without Real Latency Testing

A technical post on DEV Community argues that many AI agent evaluations are misleading because they are run locally, where network latency, timeouts, and transport failures never occur. The author contends that localhost testing cannot reproduce critical failure modes such as retry storms, partial response bodies, or deadline misses that appear in real deployments. To address this, the post recommends capturing detailed per-call telemetry including attempt numbers, monotonic timestamps, timeout budgets, abort flags, and HTTP errors on every tool invocation. A sample Python harness called latency_harness.py is provided to illustrate how implausibly fast round trips can be flagged as suspect during evaluation. The author concludes that a green result from a local eval should be treated only as a rehearsal until the agent is tested against an actual remote environment.