Author's): Abi
Originally published in Towards Artificial Intelligence.
A practical guide to making search a learnable decision layer – with code, architecture, and production trade-offs.
Vector search is perfect for “one query, one answer” workflows. But agentic AI systems download data multiple times as part of the plan – and a small mistake at the beginning becomes a compound error that derails the entire task.
This paper discusses the need for an adaptive search system for agentic AI, highlighting the problems associated with static search in dynamic workflows and illustrating the design of an adaptive search router that improves decision making through feedback loops, thereby eliminating complex errors and increasing the efficiency of search tasks.
Read the entire blog for free on Medium.
Published via Towards AI
Take our 90+ year old Beginner to Advanced LLM Developer Certification: From project selection to implementing a working product, this is the most comprehensive and practical LLM course on the market!
Towards AI has published 'Building an LLM for Manufacturing' – our 470+ page guide to mastering the LLM with practical projects and expert insights!
Discover your dream career in AI with AI Jobs
Towards AI has created a job board tailored specifically to machine learning and data analytics jobs and skills. Our software finds current AI tasks every hour, tags them and categorizes them so they can be easily searched. Explore over 40,000 live job opportunities with Towards AI Jobs today!
Note: The content contains the views of the authors and not Towards AI.
