Prompt Caching Explained: Stop Overpaying for AI Agents
Prompt caching saves costs by caching inputs, not outputs, in AI agent contexts
“if it's not, then you're going to be paying full price for the whole thing, which is going to be very expensive”
A Hugging Face tutorial clarifies a common misconception: prompt caching saves money by caching input tokens processed by the model, not by storing and replaying outputs. In long agentic conversations with large context windows, a correctly implemented agent harness avoids re-processing repeated context on every turn, potentially cutting costs significantly. The content is practical engineering guidance rather than a new announcement, making it useful for developers building agent systems but not a major industry signal.