@dair_ai: Great paper discussing agentic search vs. vector search.
Summary
This paper discusses and compares agentic search with vector search approaches.
Similar Articles
@jerryjliu0: There’s an open question on whether grep is all you need for agentic search. This recent paper by @PwCUS (Sen et al.) s…
Recent paper investigates whether grep outperforms vector search for agentic retrieval, finding grep yields higher accuracy in conversational memory tests, but limitations around enterprise document corpora are noted.
Sharing for inspiration: Grep for agentic search was a game changer for us.
Describes improving agentic memory search by incorporating grep-based exact matching alongside vector embeddings, inspired by a paper; achieved significant recall gains in their memory layer.
Agentic search models (5 minute read)
Agentic search models are LLMs trained specifically for orchestrating search tasks, offering smaller, faster, and domain-specific alternatives to general models like GPT-5. They unbundle the traditional monolithic search stack by allowing an intelligent model to manage the entire retrieval process.
@helloiamleonie: Took some inspiration from @vboykis and converted my first ever talk into a blog post. I talk about the role of agentic…
The article by Leonie Monigatti discusses the role of agentic search in context engineering for AI agents, tracing the evolution from fixed RAG pipelines to agentic RAG and context curation. It provides intuition on the strengths and weaknesses of various search tools used in agentic systems.
@dair_ai: New work from Google DeepMind and collaborators. Agentic algorithm discovery keeps getting demonstrated on problems wit…
ArchAgent v2 from Google DeepMind automates multi-level data prefetcher design using agentic algorithm discovery, outperforming hand-designed solutions in the Data Prefetching Championship.