The hidden cost of AI agents is memory
The first generation of enterprise AI projects taught businesses how to retrieve information. A user asks a question, the system finds relevant context, and a model turns it into an answer.
CEO & Co-Founder of SurrealDB.
AI agents change that equation because they retrieve information dynamically and adjust their own state in the process. As tasks evolve they juggle everything from plan development, and outbound tool calls, to updating records, and recording results.
Multiply that activity across hundreds or thousands of agents and the data layer starts behaving very differently - with significant implications for both cost and accuracy. These implications are becoming major considerations when moving agentic AI projects from pilot to production.
Why pilots can hide the real cost
Memory becomes an operational system
Early pilots tend to be narrow by design. Typically, there’s one team working with a limited dataset and relatively simple, short-lived interactions. Take as...
Copyright of this story solely belongs to www.techradar.com. To see the full text click HERE
