Solving an ARD problem in AI: Agentic Resource Discovery

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Jun 19, 20262 mins

Microsoft, Google, Cisco and others propose a new way to help AI agents discover the tools they need to perform the tasks they are assigned.

How AI agents work
Credit: Shutterstock/Wanan Wanan

Enterprises implementing agentic AI face a challenge: Which tools should they allow their agents to use, where can they be found, and how can they be used safely? A new protocol, Agentic Resource Discovery, or ARD, aims to let agents answer those questions for themselves. Behind it are Google, Microsoft, Cisco, Nvidia, Salesforce and others.

ARD aims to standardize the way that tools and services are shared across systems within a corporate domain. For example, when investigating a production problem, an agent may want to query engineering documentation and open support tickets, deployment history and observability systems, all of which could be managed by different registries and across different silos. There is no common layer that pulls them together. ARD has been designed to be that layer.

It operates across two levels. Catalogs and Registries. In the first, an organization publishes a catalog setting out its available capabilities. The Registries layer act as a form of search engine, crawling those published catalogs.

The ARD specification is available now. Organizations are invited to publish their own catalogs using the quickstart guide. After this, they are able to join the community and participate in the evolution of ARD.

Maxwell Cooter

Maxwell began writing about technology in 1984, when mainframes ruled the world. Since then he has written for just about every business computing title in the UK, and for a few in the US, covering everything from Artificial intelligence to Zero-day exploits and all points in between. He has also been editor-in-chief of several award-winning titles, including Network Week, Techworld, and Cloud Pro, and a regular contributor to Whatsonstage.com. In his spare time he coaches a junior rugby team.

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