How are people handling the trade-off between context compaction and prompt caching in production agents?

I’ve been thinking about context management for long-running agents. Compaction obviously helps control context growth, but it seems to come with a cost: once you rewrite/summarize the conversation state, you potentially lose a lot of the benefit of prompt caching because the prefix keeps changing. So I’m wondering how people handle this in production. Do you actually compact the main agent context frequently? Or is a better pattern to keep the main context relatively stable and push isolated work into subagents with clean contexts, then only return the relevant outcome/artifact back to the parent? Something like: main agent → spawn focused subagent → subagent does exploration/tool calls → return concise result → main context stays clean That seems like it could give you: better prompt cache utilization less context pollution clearer task boundaries less information loss from repeated summarization Then compaction becomes more of a fallback for genuinely long-lived state rather than something you need every N turns. Curious what people are actually doing in production. How often are you compacting, and when do you prefer compaction vs context isolation/subagents?