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LLM-Powered Discovery Recommendations

LLM-Powered Discovery Recommendations

1
posts
2026

Instacart is transforming its discovery recommendations by leveraging Large Language Models (LLMs). This initiative moves away from static content libraries and human-driven generation towards an AI-native platform for content generation, evaluation, and retrieval. The system employs a top-down, cascaded approach, starting with page design and theme generation personalized to users, followed by retrieval keyword generation, quality and diversity filtering, and finally, product and pagewise ranking. This aims to deliver more delightful personalization, cohesion across the discovery surface, and adaptability to changing business environments.

2026

Our Early Journey to Transform Instacart’s Discovery Recommendations with LLMs

2/26/2026

This post details the early journey of Instacart in transforming its discovery recommendations using LLMs. It outlines the limitations of traditional recommendation engines, such as difficulty in scaling personalized content and lack of cohesion. The proposed solution involves an AI-native platform with a top-down, cascaded generative approach. Key phases include page design & theme generation, retrieval keyword generation, quality and diversity filtering, and product and pagewise ranking. The methodology emphasizes personalized themes, retrieval-compatible descriptors, and a structured schema for interpretability.