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AI agent evaluation misses broken products
At VB Transform 2026, industry leaders discussed the challenge of flawed evaluations in AI agents, leading to a new focus on cohort-based analysis. The shift aims to identify product shortcomings that individual assessments overlook. Harrison Chase from LangChain and other experts emphasized the evolving nature of evaluation criteria as dynamic specifications rather than fixed standards.
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Published 20 Jul 2026, 18:25 UTC5 min read
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Summary
TL;DR
- AI evaluations are moving from individual scoring to cohort comparisons.
- Industry leaders emphasize the challenge of evaluating AI agents effectively.
- Human oversight remains crucial despite advances in automated evaluation.
- Cohort-based analyses reveal flaws not visible in single assessments.
- The evaluation criteria are becoming a living specification.
- Monitoring performance continuously is essential for catching real problems.
Interesting facts
- Many enterprises experience 'eval paralysis', delaying launches.
- Automated judging is still seen as unreliable compared to human review.