WHY DOORDASH, INSTACART, AND UBER EATS INTEGRATED LLMS INTO SEARCH THREE DIFFERENT WAYS

Summary from the TLDR Dev newsletter

Food search breaks keyword retrieval every way at once with synonyms, typos, bilingual collisions, a long tail with no conversion data, and hard constraints where “vegan chicken sandwich” scores as similar to something that violates the whole point. Three companies solved it off the same research base and landed at different depths of LLM integration: DoorDash keeps it offline enriching a knowledge graph, Instacart puts it at query understanding with a head/tail split, and Uber Eats makes a fine-tuned Qwen the embedding backbone of two-tower retrieval.