AI agents treat every interaction as a new user. A user selects a premium option, and the very next turn the agent suggests the cheapest alternative, it forgot everything. This happens because agent tools return results but never store what they learn. Each tool call is isolated. There is no mechanism to capture preferences from user actions. The root cause: Without explicit state management, agents have no short-term or long-term memory. Research on cognitive memory in LLMs (Shan et al., 2025) identifies three memory layers, sensory, short-term, and long-term, but most agent implementations only have sensory (the current context window). The result: MemoryOS research shows a +49% F1 improvement when agents gain hierarchical memory. I will cover why stateless tools cause preference amnesia (tools return results but never store insights), how agent.state creates within-session memory accessible to all tools, how FileSessionManager persists state across sessions so users return days later with preferences intact, the pattern for tools that learn from actions by capturing implicit preferences at execution time, and research validation from MemoryOS (+49% F1, +46% BLEU-1) and Cognitive Memory in LLMs. You'll walk away with: • agent.state implementation for within-session memory in any agent framework • Cross-session persistence with FileSessionManager or equivalent • Tool design that captures implicit preferences from user actions • The three-layer memory model (sensory, short-term, long-term) applied to your agents • Open-source code you can adapt to any domain Most memory talks focus on RAG or external knowledge bases. This focuses on the simplest, most impactful memory fix: making agents remember what users DO, not what they SAY. The technique applies to any agent domain (e-commerce, support, education, healthcare), not the demo scenario alone.

Outline: • The Memory Decay Problem • Fix: agent.state for Within-Session Memory • Fix: FileSessionManager for Cross-Session • How Memory Works in AI Agents • Production Patterns + Resources