Terminal or filesystem access dramatically boosts a model's image understanding
andpoul · x · 2026-11-14
In a discussion about coding agent evaluation, andpoul argues that even for something as simple as asking a model what's in an image, giving it a terminal or filesystem boosts performance a lot — agents can try things locally to figure problems out, much like in RL environments without internet access.
He also notes that benchmarks without a machine to poke at may be unfair comparisons. Key takeaway: environment access itself is a big capability multiplier, and evals should account for it.
More from coding & agent
- Databricks AI agents take 2nd in Meta kernel challenge with 2.5X speedup over SGLang — Yuchenj_UW · 2026-11-14
- Weaviate Podcast: Lightweight reranking can cut agent token costs despite slower search — CShorten30 · 2026-11-14
- Frontier models win benchmarks, cheap models win the invoice — AIFlow_ML · 2026-11-14
- Store Your Context in a Turso DB Any LLM Can Query, Switch Tools Freely — glcst · 2026-11-14
- Slashvibe launches $189 physical device for managing multiple AI coding agents — Scobleizer · 2026-11-14
- Agents don't chain models by default — concrete goals make them do it on first try — PrateekVJoshi · 2026-11-14