TokenTrim: LLM Agent Efficiency Engine
Developers face escalating token costs in ReAct agents due to redundant or verbose prompt generation. TokenTrim introduces a lean intent‑classification layer that shortens prompts and responses, slashing token usage by up to 90% while preserving agent performance.
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Raw PostsHow we cut LLM token usage 89% in a ReAct agent using intent classification ΓÇö architecture writeup
How we cut LLM token usage 89% in a ReAct agent using intent classification ΓÇö architecture writeup. How we cut LLM token usage 89% in a ReAct agent using intent classification ΓÇö architecture writeup