Advanced evals: How to find (and fix) hidden AI failures in your product

Founder takeaway

Treat error discovery as a required stage of AI product evaluation: first identify and categorize hidden failure modes, then prioritize fixes based on their impact on users.

Why it matters

AI products can appear effective while still failing in consequential edge cases. A repeatable discovery process helps teams direct scarce engineering effort toward failures that most undermine customer value and trust.

Relevant guides

Put it to work

Review a representative sample of recent AI outputs and ask: What recurring failure categories appear, which users or workflows do they affect, and which single category should we fix first?