Agent Memory - Building Stateful AI Agents That Remember, Adapt, and Work Across Time (Benjamin Labaschin) (z-library.sk, 1lib.sk, z-lib.sk)

AI agents have quickly become the dominant way large language models interact with users, systems, and workflows, but with their limited context windows users are required to repeat lengthy prompts every session. And as agents move from prototypes into real workflows, the lack of persistent memory becomes one of the most expensive problems teams face. In Agent Memory, Ben Labaschin, head of AI and engineering at Workhelix, shows you what it actually takes to build agents that remember: what they should store, how to retrieve it reliably, and how to design the infrastructure that keeps memory accurate and useful over time. The result is a blueprint for memory systems that can be monitored, governed, repaired, and trusted—not just in demos, but at scale.