How do teams prevent duplicate LLM API calls and token waste?
I'm curious how teams running LLM-heavy applications handle duplicate or redundant API calls in production.
While experimenting with LLM APIs, I noticed that the same prompt can sometimes be sent repeatedly across different parts of an application, which leads to unnecessary token usage and higher API costs.
For teams using OpenAI, Anthropic, or similar APIs in production: How do you currently detect or prevent duplicate prompts or redundant calls? Do you rely on logging and dashboards, caching layers, internal proxy services, or something else? Or is this generally considered a minor issue that most teams just accept as part of normal usage?
Prompt caching
https://platform.claude.com/docs/en/build-with-claude/prompt...
But in all honesty, for every project I have done with AI embedded (a lot of work around call centers. But a few other projects) we compare the cost of a human doing it and AI doing and we are talking about a difference of at 1000x to 2000x. The cost of inference is irrelevant.
Even if you think about development. I can do projects by myself that would take me and two mid level developers before. Even at enterprise dev comp we are talking about $160K fully loaded x 2 compared to $8000K a year or less for Claude.