--- title: Prompt Caching in LLMs! | daily.dev description: Prompt caching is a critical cost-optimization technique for LLM-based agents. Every agent turn resends the full conversation history, causing redundant... canonical: https://daily.dev/posts/prompt-caching-in-llms--yunvudzrh twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Prompt Caching in LLMs! | daily.dev og:description: Prompt caching is a critical cost-optimization technique for LLM-based agents. Every agent turn resends the full conversation history, causing redundant... og:url: https://daily.dev/posts/prompt-caching-in-llms--yunvudzrh og:image: https://api.daily.dev/og/posts/yunvUdZRH.png og:image:alt: Prompt Caching in LLMs! og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Prompt Caching in LLMs! **[Daily Dose of Data Science \| Avi Chawla \| Substack](https://daily.dev/sources/dailydoseofds)** · 9 min read · 1 upvotes · 0 comments ## Summary Prompt caching is a critical cost-optimization technique for LLM-based agents. Every agent turn resends the full conversation history, causing redundant computation. By separating static context (system prompt, tool definitions) from dynamic context (conversation history), the KV cache stores computed Key/Value tensors and serves them at a 90% discount on subsequent reads. Using Claude Code as a case study, a 30-minute coding session achieves a 92% cache hit rate and 81% cost reduction. Key rules: never modify tool definitions mid-session, never switch models, never mutate the static prefix. Prompt structure should place stable content at the top and dynamic content at the bottom. Cache efficiency can be monitored via API response fields. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Prompt Caching Techniques](https://daily.dev/posts/prompt-caching-techniques-rlnexmcrg) · PromptLayer Blog · 1 upvotes · 0 comments - [Why Care About Prompt Caching in LLMs?](https://daily.dev/posts/why-care-about-prompt-caching-in-llms--xsybxgzta) · Towards Data Science · 1 upvotes · 0 comments - [Prompt Caching Explained](https://daily.dev/posts/prompt-caching-explained-mhomvre8o) · DigitalOcean Community · 2 upvotes · 0 comments - [Prompt Caching for Anthropic and OpenAI Models: Building Cost-Efficient AI Systems](https://daily.dev/posts/prompt-caching-for-anthropic-and-openai-models-building-cost-efficient-ai-systems-mjzh92xkq) · DigitalOcean · 2 upvotes · 0 comments --- Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#claude](https://daily.dev/tags/claude), [#llm](https://daily.dev/tags/llm) [View this post on daily.dev](https://daily.dev/posts/prompt-caching-in-llms--yunvudzrh) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Prompt Caching in LLMs!","url":"https://daily.dev/posts/prompt-caching-in-llms--yunvudzrh","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/prompt-caching-in-llms--yunvudzrh"},"datePublished":"2026-03-09T21:25:12.283Z","dateModified":"2026-03-15T06:05:42.525Z","description":"Prompt caching is a critical cost-optimization technique for LLM-based agents. Every agent turn resends the full conversation history, causing redundant...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/d0e3732ede2b7c978a6da6f677d602c3?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/d0e3732ede2b7c978a6da6f677d602c3?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Daily Dose of Data Science | Avi Chawla | Substack","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Daily Dose of Data Science | Avi Chawla | Substack","logo":"https://media.daily.dev/image/upload/s--4IHQgTOw--/f_auto/v1710503712/logos/dailydoseofds","url":"https://daily.dev/sources/dailydoseofds"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/prompt-caching-in-llms--yunvudzrh","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"ai-agents,claude,llm","timeRequired":"PT9M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Daily Dose of Data Science | Avi Chawla | Substack","item":"https://daily.dev/sources/dailydoseofds"},{"@type":"ListItem","position":3,"name":"Prompt Caching in LLMs!"}]} ```