Case studies, methodology deep-dives, release notes, and community contributions on evaluating production AI agents.
Learn how to stress test any AI agent in just 10 lines using a configurable harness for adversarial, multi-turn evaluation and evidence-linked reports. No agent rebuild required.
AI agent evaluation is a multi-layered lifecycle involving pre deployment testing, debugging, regression checks, and production monitoring. This article compares top tools addressing these needs.
A privacy and security agent powered by GPT 5.5 resisted 25 turns of adversarial probing without leaking data. Yet, upstream content filters caused refusal delivery failures.
Claude Opus 4.7 failed a safety-critical tool-call test in healthcare triage. ProofAgent Harness surfaced the gap, showing why adversarial evaluation is essential for deployment.
Why adversarial multi-turn evaluation replaced static benchmarks for production AI agents in 2026. Red teaming, jailbreak patterns, real tool comparison, evidence-based. (158 chars)