💡 This is a cross-post from my AI Cost Calc blog . Original has the same content with linked tools — feedback welcome on either platform. Prompt caching is the single most undervalued cost optimization in AI APIs today. Used correctly on a typical RAG workload, you'll cut your OpenAI bill by 40-75% . Used incorrectly — or skipped entirely — you'll pay the headline rate forever. The catch: caching savings are entirely structural . The same product with the same total tokens can save 70% or save 0% depending on how you sequence your prompts. Most teams don't realize they're paying the no-cache price even when caching is technically "enabled." This guide breaks down exactly when OpenAI prompt caching is worth implementing, how much you'll really save, and the four patterns that silently kill your cache hit rate. How OpenAI prompt caching works (60-second refresher) Since late 2024, OpenAI has supported automatic prompt caching on its main reasoning models.…