A deep dive into how Instacart rebuilt its Shopping Hub — the discovery page shoppers see right after picking a retailer — around a four-phase generative pipeline instead of a static, manually curated content library. We cover the business problem (personalization that couldn't scale, and a page built by siloed teams that never felt cohesive), the technical approach (an LLM agent that designs page themes top-down, retrieval-augmented keyword generation grounded in the real catalog, layered LLM-judge and embedding-based quality filters, and a cheap distilled classifier that cuts evaluation cost by an estimated 99%), and what the early results show — and don't yet show — about putting a generative model in charge of page structure itself. Source article: "Our Early Journey to Transform Instacart's Discovery Recommendations with LLMs" — Instacart Tech, ...