OpenAI Prompt Cache Diagnostics: Find the Prefix Drift Making Your AI App Expensive

Last Updated on September 25, 2026 by Editorial Team Author(s): Ethan Mark Originally published on Towards AI. OpenAI Prompt Cache Diagnostics: Find the Prefix Drift Making Your AI App Expensive Your agent did not get smarter overnight. It may simply have gotten more expensive. A long-running AI workflow can look healthy while a tiny change quietly makes every turn reprocess thousands of tokens. A reordered tool, a request ID tucked into instructions, a changed schema, or a fallback model can turn a reusable prefix into fresh work. The response still arrives. Your logs still show success. The bill and first-token latency are the only clues. OpenAI Prompt Cache Diagnostics gives Responses API teams a way to stop guessing. Instead of treating a low cached-token count as a vague cost problem, you can compare one response with a recent baseline and get a classified explanation for the first detected mismatch. This guide shows how to turn that signal into a safe engineering loop: isolate the difference, make one reversible fix, and verify the result on representative traffic. The timing matters. OpenAI’s current API changelog lists the new GPT-6 Sol and GPT-6 Luna models, while Prompt …

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