AI agents are multiplying as corporations adopt the technology in record numbers. Smarter underlying models, better tool use, and improved multi-agent collaboration have pushed agents to evolve beyond impressive demos into practical technology that companies marshal in production environments. But the job’s not finished. 

As companies deploy more agents, more often, and against longer tasks, the plumbing that provides their AI ephemera with the required information is buckling.

Here’s the problem: AI agents are sending waves of queries against company data, creating concurrency issues and exposing just how difficult it can be to ensure a company’s AI-legible information is fresh, served only when relevant, and quickly available.

Join the live conversation: On September 24 at 12 p.m. Eastern/9 a.m. Pacific, Whit Walters, Field CTO and Lead Analyst at GigaOm and author of Defeating the Integration Tax report, joins Bonnie Chase, Director of Product Marketing at Vespa.ai, to discuss what happens when retrieval architecture meets that workload.

And crucially, they will explore in this live conversation what changes when a team rebuilds it as a unified layer instead of a fragmented one.

You might be asking yourself: How has this problem not been solved yet? Google famously handles tens of thousands of search queries every second; how difficult can it be to serve agents the information that they need when we’ve solved the human version of the same problem? It’s no small challenge, and it’s why retrieval engineering is a labor category you’ll hear more about in coming quarters.

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