@krishnachaytanya: Prompt caching is why your LLM bill barely moves, and how to actually fix it. Every API call, the model re-reads your whole prompt from scratch: the system instructions, the docs, the schema, the rules, the examples. That setup never changes. You just pay to process it again, every single call. Prompt caching stores the already-processed setup, so the next call skips it and you only pay for the new question. Same example in the video: 2,000 tokens down to 30. Around 90% cheaper, and it returns faster because the model is not re-reading the same context. The part people get wrong: it caches the PROMPT, not the answer. Your answers are still generated fresh every time. That is why this is not the same thing as response caching or putting Redis in front of your LLM. Works on Anthropic Claude, OpenAI and Gemini. One rule to take away: put the stuff that never changes at the TOP of your prompt. Save this for your next AI build. #trending #systemdesign #llm #ai #backend

KrishnaChaitanya|SystemDesign

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Saturday 12 September 2026 12:59:18 GMT