AI

A deep dive into how AI agents retain and retrieve information across long tasks and sessions, since the underlying model has no memory of its own. Covers the finite context window problem, short-term versus long-term memory, and the summarization and retrieval techniques that keep an agent coherent without drowning it in irrelevant history. This is part 4 of the AI Agents & Automation track, building on agent loops, tool use, and multi-agent coordination.