Blog
The Verification Burden Your AI Product Ignores
Accuracy is a lagging indicator. A controlled study found AI made expert developers 19% slower, because the work moved into reviewing. Here is the number to optimize instead.
10 Lessons From Production AI Agents
Ten practical lessons from tracing, evals, prompt versioning, routing, and security.
Who Actually Owns Eval Quality
Eval quality improves when domain experts own the examples and rubrics.
Why You Need Offline and Online Evals
Offline evals catch expected regressions. Online evals catch live drift and surprises.
Offline Evals as a CI Gate
Use small golden datasets and CI checks to catch prompt regressions before users do.
The Best Agent Evals Come From Production Failures, Not Design Sessions
Most teams spend weeks designing agent evals from scratch. The ones that build better agents discover them from real traces and real failures. Here is what that actually looks like.
Your Agent Passes Every Test and Still Gets the Date Wrong
Your agent testing strategy is broken. Build retrieval, tool parameter, and end-to-end evals that predict production behavior.
Evaluating AI Agent Skills with Skill Eval
You write CLAUDE.md files and hope the agent follows them. Minko Gechev's Skill Eval framework treats agent skills like code — with unit tests, scoring, and CI integration that catches regressions before they ship.