AI Evals Guide: Generic Metrics Fail, Top Teams Rely on Error Analysis
PawelHuryn · x · 2026-11-16
Paweł Huryn's deep-dive in The Product Compass argues that generic metrics like "hallucination" or "toxicity" miss domain-specific issues, and walks through what the best AI product teams track instead using structured error analysis. He also links a GitHub repo of 45 free agent skills (from idea to paying users) and guidance on embedding agents into products. Full post is paywalled with a 7-day free trial.
More from coding & agent
- 45 agent skills from shipping three live products, open-sourced on GitHub — PawelHuryn · 2026-11-16
- Build a multi-tenant SaaS in 3-4 hours with Claude Code, Clerk, and Supabase — PawelHuryn · 2026-11-16
- PM field guide: building the same CRM in Lovable, AI Studio, and Claude — PawelHuryn · 2026-11-16
- Anthropic's 11 open PM roles pay $305K-$460K — none require a CS degree — PawelHuryn · 2026-11-16
- Formal methods tip: have your coding agent write specs and focus on invariants — blaizedsouza · 2026-11-16
- NVIDIA open-sources Personal AI Router: turn every home PC into one AI cluster — blaizedsouza · 2026-11-16