--- title: Getting More Out of Every AI Token | daily.dev description: Engineers at monday.com share three practical strategies for reducing LLM token usage and AI costs in agentic workflows. The Caveman plugin instructs models to... canonical: https://daily.dev/posts/getting-more-out-of-every-ai-token-kyglhjl0z twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Getting More Out of Every AI Token | daily.dev og:description: Engineers at monday.com share three practical strategies for reducing LLM token usage and AI costs in agentic workflows. The Caveman plugin instructs models to... og:url: https://daily.dev/posts/getting-more-out-of-every-ai-token-kyglhjl0z og:image: https://api.daily.dev/og/posts/KyGlHJl0z.png og:image:alt: Getting More Out of Every AI Token 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. # Getting More Out of Every AI Token **[monday Engineering](https://daily.dev/sources/monday)** · 8 min read · 0 upvotes · 0 comments ## Summary Engineers at monday.com share three practical strategies for reducing LLM token usage and AI costs in agentic workflows. The Caveman plugin instructs models to respond tersely, cutting ~65% of output tokens. RTK is a proxy that compresses shell command output (e.g., docker ps) by 60–90% before it reaches the model. Headroom is a broader context optimization layer that compresses tool outputs, logs, files, RAG chunks, and conversation history by 60–95%, with a reversible Compress-Cache-Retrieve mechanism so the agent can fetch full details when needed. The three tools target different boundaries and can be stacked: Headroom wraps the agent, RTK handles shell output underneath, and Caveman steers model verbosity. The post also cautions that over-compression can degrade answer quality, so token graphs and answer quality should both be monitored. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#finops](https://daily.dev/tags/finops), [#context-engineering](https://daily.dev/tags/context-engineering) [View this post on daily.dev](https://daily.dev/posts/getting-more-out-of-every-ai-token-kyglhjl0z) ```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":"Getting More Out of Every AI Token","url":"https://daily.dev/posts/getting-more-out-of-every-ai-token-kyglhjl0z","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/getting-more-out-of-every-ai-token-kyglhjl0z"},"datePublished":"2026-07-16T10:53:29.862Z","dateModified":"2026-07-17T11:11:39.239Z","description":"Engineers at monday.com share three practical strategies for reducing LLM token usage and AI costs in agentic workflows. 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