04/09/2026
What happens when an AI agent needs to remember the past—but not let the past control its decisions?
In Part 5 of the series, our Vice President of Engineering, Sheba Fernando, explores how agents can manage their own memory within a policy-controlled framework. The challenge isn’t simply giving agents access to historical context—it’s deciding what they should remember, when they should use it, and how that memory should influence future decisions.
By combining agent memory with policy enforcement, organizations can build AI systems that are more consistent, traceable, and accountable—while still allowing new evidence to challenge previous conclusions.
The goal is not to give AI unlimited memory. It’s to give agents the right memory, under the right controls, at the right time.
Read the full blog: https://bit.ly/4qWCyF0