How we cut LLM token usage 89% in a ReAct agent using intent classification (opens in new tab)

Deep dive into Schema Weaver's Data Explorer SingleLLM agent architecture — the ReAct conversation loop, intent-classified tool filtering (18K to 2K tokens), parallel tool execution, error recovery, and the ExecutionContext that ties it all together. Part 2 of The Data Explorer Chronicles