We’re, in impact, standing up a second information stack particularly for brokers, then questioning why nobody in safety feels snug letting these brokers close to something vital. We shouldn’t be doing this. In case your brokers are going to carry recollections that have an effect on actual choices, that reminiscence belongs inside the identical governed-data infrastructure that already handles your buyer data, HR information, and financials. Brokers are new. The best way to safe them just isn’t.
Revenge of the incumbents
The trade is slowly waking as much as the truth that “agent reminiscence” is only a rebrand of “persistence.” In the event you squint, what the large cloud suppliers are doing already seems like database design. Amazon’s Bedrock AgentCore, for instance, introduces a “reminiscence useful resource” as a logical container. It explicitly defines retention intervals, safety boundaries, and the way uncooked interactions are remodeled into sturdy insights. That’s database language, even when it comes wrapped in AI branding.
It makes little sense to deal with vector embeddings as some distinct, separate class of knowledge that sits exterior your core database. What’s the purpose in case your core transactional engine can deal with vector search, JSON, and graph queries natively? By converging reminiscence into the database that already holds your buyer data, you inherit a long time of safety hardening without cost. As Brij Pandey notes, databases have been on the heart of utility structure for years, and agentic AI doesn’t change that gravity—it reinforces it.
