Agent Evals Are Still a Whack-a-Mole Game
maksym_andr · x · 2026-07-13
The author notes that their current approach to benchmarks and evals feels like a temporary "whack-a-mole" mode: patching things up with a new test or rule every time an issue pops up.
While manageable at current capability levels, they warn this method will fall short as agents grow more powerful, necessitating more systematic evaluation and constraint designs.
More from coding & agent
- Dense instance segmentation via Muse Wonder + SAM 3.1 on Meta's Model API — nikhilaravi · 2026-10-26
- Security tip: use AI agents to build a NIST CSF knowledge base for incident response — prasanna_says · 2026-10-26
- Google Cloud Adds Self-Learning Context Enrichment to Knowledge Catalog for AI Agents — rseroter · 2026-10-26
- Cloudflare Previews Spend Limits for Workers and Durable Objects, Early Access Open — ritakozlov · 2026-10-26
- Shopify design lead on AI-era workflow: designers are becoming full-stack editors — KlausCodes · 2026-10-26
- Nace AI launches Drex for Search, cutting agent steps 62% and tokens 56% — testingcatalog · 2026-10-26