An AI assistant built into business software carries a fixed body of background information into every conversation: behavioural instructions, the list of available actions, general facts about the company. Without optimisation, that context is processed from scratch on every single exchange.
What context caching does
Context caching lets you temporarily hold the static part of the context — the part that does not change from one conversation to the next — so that subsequent requests do not pay to process it again, only the genuinely new part of the conversation.
The practical effect on cost
On a system with detailed instructions and many available functions, the static part of the context can account for most of the data processed on every interaction. Reducing the cost of that fixed portion translates into meaningful savings on the overall running cost of the AI service, with no loss of answer quality.
Why it matters to anyone selling software with AI built in
For a company offering an AI assistant to its customers, this technical optimisation is not an invisible detail: it is what makes it sustainable to offer AI generously, rather than having to throttle its use artificially to keep costs down.