--- title: How do AI teams use RL in production? | daily.dev description: Part 13 of a Reinforcement Learning course series examines how real AI companies apply RL in production through four case studies: Cursor's real-time RL loop... canonical: https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: How do AI teams use RL in production? | daily.dev og:description: Part 13 of a Reinforcement Learning course series examines how real AI companies apply RL in production through four case studies: Cursor's real-time RL loop... og:url: https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl og:image: https://api.daily.dev/og/posts/84y0GgeTL.png og:image:alt: How do AI teams use RL in production? 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. # How do AI teams use RL in production? **[Daily Dose of Data Science \| Avi Chawla \| Substack](https://daily.dev/sources/dailydoseofds)** · 5 min read · 2 upvotes · 1 comments ## Summary Part 13 of a Reinforcement Learning course series examines how real AI companies apply RL in production through four case studies: Cursor's real-time RL loop shipping improved checkpoints every five hours, how frontier labs use verifiable rewards for reasoning and agentic capabilities, Scale AI achieving a 4B model that outperforms GPT-5 on domain-specific tasks, and the emerging market for RL environments as products. The post also covers LLM routing versus Mixture of Agents architectures, explaining how routing selects the best single model per task while MoA combines multiple models to exceed individual performance. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is the difference between LLM routing and Mixture of Agents architectures? LLM routing sends each query to a single best-fit model chosen by an intent classifier and cost ranker weighing latency, price, and capability, leaving other models idle. Mixture of Agents instead has multiple models independently analyze the same query, then hands all their outputs to a single aggregator that writes the final answer. Routing picks one model per task; MoA combines several to exceed any single model's performance. _Comparing model orchestration strategies gets easier with technical explainers like this surfaced on daily.dev._ ### How much better did a Mixture of Agents setup perform compared to a single model on HermesBench? Nous Research reported that a Mixture of Agents preset scored roughly six points higher than either individual model alone, and eight to eleven percent better overall, on HermesBench. No individual model in that setup reached the same result independently, showing that combining multiple models' outputs through an aggregator can exceed what any single model achieves alone. _Developers weighing multi-model architectures can track benchmarks like this through daily.dev._ ### How does Cursor use reinforcement learning to improve its AI coding model in production? Cursor runs a real-time reinforcement learning loop that ships improved model checkpoints every five hours, continuously updating its coding assistant based on ongoing training signals rather than infrequent large releases. This rapid iteration cycle is cited as one example of how AI labs apply RL concepts like reward design and trajectory structure to production coding tools. _Engineers relying on AI coding assistants can follow how tools like Cursor evolve via daily.dev._ ## Community discussion Top comments from developers on daily.dev. **@agustinbarrientos** · 0 upvotes > I wouldn't let those five-hour checkpoints reach users without an automatic rollback gate. ## Similar posts on daily.dev - [Improving Composer through real-time RL · Cursor](https://daily.dev/posts/improving-composer-through-real-time-rl-cursor-kihj0ypyy) · Cursor · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#reinforcement-learning](https://daily.dev/tags/reinforcement-learning) [View this post on daily.dev](https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl) ```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":"How do AI teams use RL in production?","url":"https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl"},"datePublished":"2026-07-20T21:45:33.636Z","dateModified":"2026-09-14T08:29:24.938Z","description":"Part 13 of a Reinforcement Learning course series examines how real AI companies apply RL in production through four case studies: Cursor's real-time RL loop...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/f7d2edac751fb0aa91ac13cffc9872d4?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/f7d2edac751fb0aa91ac13cffc9872d4?_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":1,"discussionUrl":"https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":2},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":1}],"keywords":"machine-learning,llm,ai-agents,reinforcement-learning","timeRequired":"PT5M"} {"@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":"How do AI teams use RL in production?"}]} {"@context":"https://schema.org","@type":"WebPage","@id":"https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl","comment":[{"@type":"Comment","text":"I wouldn’t let those five-hour checkpoints reach users without an automatic rollback gate.","datePublished":"2026-08-02T22:55:46.999Z","url":"https://daily.dev/posts/84y0GgeTL#c-1TalXq9LJ","author":{"@type":"Person","name":"Agustin Barrientos","url":"https://daily.dev/agustinbarrientos","image":"https://media.daily.dev/image/upload/s--5ayxQnqn--/f_auto/v1788281802/avatars/avatar_wQYYVe5Tbj0NJ7C7qPoa8?_a=BAMAMicg0"}}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/how-do-ai-teams-use-rl-in-production--84y0ggetl#faq","mainEntity":[{"@type":"Question","name":"What is the difference between LLM routing and Mixture of Agents architectures?","acceptedAnswer":{"@type":"Answer","text":"LLM routing sends each query to a single best-fit model chosen by an intent classifier and cost ranker weighing latency, price, and capability, leaving other models idle. 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