Cleaning Tool Outputs Significantly Boosts Efficiency
thisdudelikesAI · x · 2026-07-16
The post notes that after extensive tool calls, raw outputs become "dead weight" that distracts the model.
Anthropic addresses this by cleaning up these tool results. In their internal agentic search evaluations, combining memory with context editing yielded a 39% improvement. The author emphasizes this isn't just a fine-tuning trick, but an engineering difference that determines whether an agent can actually complete tasks.
Related event: Anthropic shifts agent engineering toward context engineering(5 posts)→
More from coding & agent
- SF 'Code Engineering' event picks up where 1,000-person harness engineering meetup left off — LangChain · 2026-10-27
- Prompt turns Claude Code into an iPhone backup forensics tool exposing 30-day 'deleted' photo copies — alex_verem · 2026-10-27
- Prompt turns Claude Code into a forensics tool finding deleted iPhone photos in backups — alex_verem · 2026-10-27
- Phones won't be mobile IDEs but control planes for agent fleets, argues Yuchen Jin — Yuchenj_UW · 2026-10-27
- FrontierCS 2 launches on Kaggle: 48 tasks make agents beat published CS papers — MeganRisdal · 2026-10-27
- Stop remaking old games with AI: a call for more ambitious agentic software — rschu · 2026-10-27