Context compression for agents

Agent workflows increasingly benefit from compressing long logs, retrieved documents, and intermediate tool outputs before sending them back into a model. Why it matters: Smaller, cleaner context can reduce cost and latency while making multi-step agents easier to inspect and debug.

Try this: Pick one verbose agent trace or research source, summarize it into a compact structured brief, then compare the next model response against the uncompressed version.