--- title: Our Early Journey to Transform Instacart’s Discovery... description: Instacart's ML team shares how they rebuilt their Shopping Hub recommendation system using LLMs. The new AI-native platform uses a top-down, cascaded... canonical: https://daily.dev/posts/our-early-journey-to-transform-instacart-s-discovery-recommendations-with-llms-wpv1ryxzx twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Our Early Journey to Transform Instacart’s Discovery Recommendations with LLMs | daily.dev og:description: Instacart's ML team shares how they rebuilt their Shopping Hub recommendation system using LLMs. The new AI-native platform uses a top-down, cascaded... og:url: https://daily.dev/posts/our-early-journey-to-transform-instacart-s-discovery-recommendations-with-llms-wpv1ryxzx og:image: https://api.daily.dev/og/posts/wpV1Ryxzx.png og:image:alt: Our Early Journey to Transform Instacart’s Discovery Recommendations with 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. # Our Early Journey to Transform Instacart’s Discovery Recommendations with LLMs **[Instacart](https://daily.dev/sources/instacart)** · 16 min read · 1 upvotes · 0 comments ## Summary Instacart's ML team shares how they rebuilt their Shopping Hub recommendation system using LLMs. The new AI-native platform uses a top-down, cascaded generation approach: a page design agent generates personalized themes from user context, a fine-tuned student model generates retrieval keywords via RAG, and quality/diversity filtering guards against off-brand or redundant content before passing to existing ranking infrastructure. Key techniques include teacher-student fine-tuning on Llama/Qwen models, RAG-based keyword candidate pruning (reducing generation costs 15-20%), and a fine-tuned DeBERTa cross-encoder for scalable quality filtering (99% cost reduction vs. LLM inference). Early A/B results are promising, with generative placements outperforming static baselines in offline evaluations. Key learnings: keep modeling tasks focused, invest heavily in evals, and add structure to input/output layers. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Building The Intent Engine: How Instacart is Revamping Query Understanding with LLMs](https://daily.dev/posts/building-the-intent-engine-how-instacart-is-revamping-query-understanding-with-llms-7wcfinvhu) · Instacart · 5 upvotes · 0 comments - [Using LLMs to infer grocery preferences from DoorDash restaurant orders](https://daily.dev/posts/using-llms-to-infer-grocery-preferences-from-doordash-restaurant-orders-ig7ur8p29) · Doordash · 1 upvotes · 0 comments - [Why DoorDash, Instacart, and Uber Eats Integrated LLMs Into Search Three Different Ways](https://daily.dev/posts/why-doordash-instacart-and-uber-eats-integrated-llms-into-search-three-different-ways-kabch9gjw) · ByteByteGo · 18 upvotes · 2 comments - [Mind the Gap: Using LLMs to bridge behavioral silos in multi-vertical recommendations](https://daily.dev/posts/mind-the-gap-using-llms-to-bridge-behavioral-silos-in-multi-vertical-recommendations-bywptdoxw) · Doordash · 1 upvotes · 0 comments --- Tags: [#llm](https://daily.dev/tags/llm), [#rag](https://daily.dev/tags/rag), [#recommendation-systems](https://daily.dev/tags/recommendation-systems) [View this post on daily.dev](https://daily.dev/posts/our-early-journey-to-transform-instacart-s-discovery-recommendations-with-llms-wpv1ryxzx) ```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":"Our Early Journey to Transform Instacart’s Discovery Recommendations with LLMs","url":"https://daily.dev/posts/our-early-journey-to-transform-instacart-s-discovery-recommendations-with-llms-wpv1ryxzx","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/our-early-journey-to-transform-instacart-s-discovery-recommendations-with-llms-wpv1ryxzx"},"datePublished":"2026-02-26T19:09:11.606Z","dateModified":"2026-02-26T19:09:38.440Z","description":"Instacart's ML team shares how they rebuilt their Shopping Hub recommendation system using LLMs. The new AI-native platform uses a top-down, cascaded...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/462b696a1048b8c6b24c56ba50be1448?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/462b696a1048b8c6b24c56ba50be1448?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Instacart","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":"Instacart","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/70876f6db0ce42758bec266efc99d9f3","url":"https://daily.dev/sources/instacart"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/our-early-journey-to-transform-instacart-s-discovery-recommendations-with-llms-wpv1ryxzx","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"llm,rag,recommendation-systems","timeRequired":"PT16M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Instacart","item":"https://daily.dev/sources/instacart"},{"@type":"ListItem","position":3,"name":"Our Early Journey to Transform Instacart’s Discovery Recommendations with LLMs"}]} ```