--- title: Helping AI agents search to get the best results out of... description: MIT CSAIL and Asari AI researchers developed EnCompass, a framework that helps AI agents using large language models backtrack and retry when mistakes occur.... canonical: https://daily.dev/posts/helping-ai-agents-search-to-get-the-best-results-out-of-large-language-models-oepyrxkhw twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Helping AI agents search to get the best results out of large language models | daily.dev og:description: MIT CSAIL and Asari AI researchers developed EnCompass, a framework that helps AI agents using large language models backtrack and retry when mistakes occur.... og:url: https://daily.dev/posts/helping-ai-agents-search-to-get-the-best-results-out-of-large-language-models-oepyrxkhw og:image: https://api.daily.dev/og/posts/oEpYRxkhw.png og:image:alt: Helping AI agents search to get the best results out of large language models 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. # Helping AI agents search to get the best results out of large language models **[MIT News](https://daily.dev/sources/mit)** · 7 min read · 0 upvotes · 0 comments ## Summary MIT CSAIL and Asari AI researchers developed EnCompass, a framework that helps AI agents using large language models backtrack and retry when mistakes occur. The system separates search strategy from workflow logic, allowing programmers to experiment with different approaches like Monte Carlo tree search or beam search without extensive code changes. In testing, EnCompass reduced coding effort by up to 82% and improved accuracy by 15-40% on code translation tasks. The framework enables developers to build more reliable AI agents by automatically handling LLM errors and exploring multiple execution paths to find optimal solutions. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [AI search framework that teaches AI models to think like experts](https://daily.dev/posts/ai-search-framework-that-teaches-ai-models-to-think-like-experts-dehbnog4q) · Cisco · 0 upvotes · 0 comments --- Tags: [#ai](https://daily.dev/tags/ai), [#machine-learning](https://daily.dev/tags/machine-learning), [#python](https://daily.dev/tags/python), [#llm](https://daily.dev/tags/llm), [#mit](https://daily.dev/tags/mit) [View this post on daily.dev](https://daily.dev/posts/helping-ai-agents-search-to-get-the-best-results-out-of-large-language-models-oepyrxkhw) ```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":"Helping AI agents search to get the best results out of large language models","url":"https://daily.dev/posts/helping-ai-agents-search-to-get-the-best-results-out-of-large-language-models-oepyrxkhw","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/helping-ai-agents-search-to-get-the-best-results-out-of-large-language-models-oepyrxkhw"},"datePublished":"2026-02-05T21:40:09.907Z","dateModified":"2026-02-05T21:40:30.367Z","description":"MIT CSAIL and Asari AI researchers developed EnCompass, a framework that helps AI agents using large language models backtrack and retry when mistakes occur....","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/a3aaeaaeb5f29cc72d3399f6fbe6a793?_a=AQAEunF","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/a3aaeaaeb5f29cc72d3399f6fbe6a793?_a=AQAEunF","isAccessibleForFree":true,"articleSection":"MIT News","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":"MIT News","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/881e20a40aa44b12ba4bd27f5c14289d","url":"https://daily.dev/sources/mit"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/helping-ai-agents-search-to-get-the-best-results-out-of-large-language-models-oepyrxkhw","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"ai,machine-learning,python,llm,mit","timeRequired":"PT7M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"MIT News","item":"https://daily.dev/sources/mit"},{"@type":"ListItem","position":3,"name":"Helping AI agents search to get the best results out of large language models"}]} ```