Agentic search models

kept by eddie may 13

Smaller, domain-tuned LLMs trained specifically for search orchestration can replace complex monolithic retrieval pipelines by intelligently controlling simpler retrieval primitives.

Can agents replace the search stack?
Using a basic BM25 or e5 retriever with an LLM agent can achieve 0.289→0.453 NDCG on Amazon ESCI by reasoning over queries, but this approach fails on passage retrieval where the embedding model already knows best.
also on SID-1, #search-engine, #ai-agents
Ask HN: How are you doing RAG locally?
Hacker News commenters share diverse local RAG setups including vector databases, SQLite FTS5, BM25, and lightweight tools like Chroma, Qdrant, and AnythingLLM.
also on #rag
Over 30 new plugins join the Cursor Marketplace
Cursor adds over 30 new plugins from partners including Atlassian and Datadog to extend its AI-powered coding agent's capabilities across infrastructure and productivity tools.
also on Glean, #ai-agents
AI's Bundling Moment
As AI model release cadence accelerates to every 42 days, companies like Harvey, Glean, and ElevenLabs are expanding from single workflow tools into broad platforms, reversing the SaaS-era unbundling strategy.
also on Glean