I reduced my OpenClaw token usage by 10x (brtkwr.com)

A recent analysis revealed a significant reduction in OpenClaw token usage by over 90%, dropping daily consumption from approximately 2.2 million tokens to just 256,000. The author identified that persistent sessions were failing to compact their message histories, leading to unnecessary repetition of large transcripts during each cron run and group chat reply. Key interventions included implementing a 500 KB compaction trigger, resolving overlaps between concurrent cron jobs, and resetting stale sessions, which collectively streamlined token usage dramatically. The findings are particularly relevant for developers using AI chat systems, highlighting the importance of session management and memory usage in cost control. By addressing overlooked details like session compaction and optimizing cron job routines, the author demonstrated that careful configuration can substantially decrease costs without sacrificing functionality. This serves as a vital lesson for the AI/ML community on the significance of rigorous performance monitoring and proactive session management strategies to optimize resource usage.