
What happened
In one session that ran 13 days and 5,065 requests, a single request late in the session cost about $0.42 against about $0.013 in a fresh session, a 31× gap. Across 6,343 recent requests, 98.2% of billed input was cache_read.
Why it matters
Because each request resends the whole conversation, cost tracks context length multiplied by request count, so cheap per-token cache reads still balloon in total and longer sessions get costlier toward the end.
Summaries like this, every morning.
The post is a practitioner's cost audit rather than a vendor announcement. The author, writing as iguchi of Mukuil, a startup building AI solutions for manufacturing, first assumed that because cache reads are cheaper per token, caching was keeping spend down. Aggregating the usage logs showed the opposite: cheap tokens were being re-read at enormous volume, and that volume was the bill.
The mechanics explain why. Claude Code sends a request to the API on every tool call, and each request carries the whole conversation so far — system prompt, CLAUDE.md, files read, tool output. The arithmetic in the post is that if context grows by a roughly fixed amount per request, total session input scales with the square of the request count, so the back half of a long session is where cost concentrates.
The team's fixes aim at both factors in that multiplication. Session hygiene (/clear, /compact with specified content, restarting past 300K tokens) shortens context, while batching independent tool calls reduces request count; the post estimates moving from an average of 1.17 to 2 calls per message would cut requests by about 41%. One detail suggests the organizational side is the harder part: a subagent defined for large-file reading went unused for 97 sessions and 21,095 requests until CLAUDE.md stated it as a standing instruction, after which it was used 11 times in 27 sessions.
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