TLDR Tech / Data
Agentic search models
Agentic search models are emerging to orchestrate the full retrieval workflow, replacing today's brittle stack of embeddings, rerankers, query classifiers, and BM25 with thinner backend primitives. Unlike frontier LLMs that handle the “80% case,” models trained specifically for search can encode domain-specific intent and the “last 20%” of retrieval nuances, improving relevance in narrow contexts like e-commerce or job search. Early examples such as SID-1 and Waldo emphasize smaller size and lower latency.
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