Beyond Prompt Caching: Solving the Hidden Costs of Extended LLM Sessions

Long LLM conversations silently escalate costs as conversation history is re-sent to the model repeatedly, with standard prompt caching expiring after five minutes and covering only the prefix. PromptCrunch addresses this by intelligently compressing conversation history, reducing input token costs by up to 75% in extended sessions and shifting billing from turn-count-based to actual work-based charges. For developers building long-running AI applications like Claude Code, this represents a meaningful path toward more predictable and sustainable AI infrastructure costs.