From Context to Execution: How AI Agents Understand, Remember, and Act
- WHO IT IS FOR: AI engineers, product founders, and researchers interested in the intersection of LLMs, memory systems, and agentic workflows.
- WHAT IT IS ABOUT: An exploration of how AI agents leverage context, memory, and real-time data to move from basic reasoning to reliable execution.
- FORMAT: A panel discussion featuring four founders building memory and knowledge infrastructure for AI.
Why do high-reasoning AI agents still make the wrong calls? Often, the bottleneck isn't the model's intelligence, but the quality and timeliness of the context it possesses. From GTM intelligence to private professional relationship memory, the ability for an agent to act reliably depends on how it captures, retrieves, and protects the specific knowledge required for the task at hand.
Join a panel of founders as they dive into the architectural challenges of building memory layers for AI. The discussion will cover diverse applications, including shared memory for native AI teams, merchant-authored knowledge for e-commerce, and private memory for professional networking. Together, they will examine the critical balance between data retrieval and execution risk, answering the fundamental question: What must an agent know before we can trust it to act?