Technology Radar
As token costs rise, teams increasingly turn to tools like Headroom, RTK and Tamp to shrink their prompts. However, we advise against naive context compression, which can introduce several subtle problems. First, it often interferes with prompt caching; reducing token counts while missing cache hits can lead to higher actual bills. Second, aggressive compression causes information loss, degrading the performance and accuracy of agentic loops. Third, some tools rely on an LLM to summarize context during compression, adding latency and costs that defeat the purpose.
Before adopting these tools, profile your context usage and rigorously evaluate both net cost and task accuracy; token reduction means nothing if prompt caches break or agent performance degrades. Opt for tools that compress tool outputs while preserving references to the raw data and that prune history only in one shot at task boundaries, to protect cache prefixes.
