Enterprise AI is shifting from simple chatbots to autonomous agents that execute complex workflows. However, agents often fail because they lack "decision traces": the reasoning, precedents, and exceptions that currently live only in Slack threads or human memory. This talk introduces Context Graphs, a living record of decision-making that turns institutional knowledge into a queryable asset.
We will explore how to move beyond the "State Clock" (what is true now) to the "Event Clock" (why it happened) using AWS infrastructure.
Attendees will learn how to implement a minimal POC using Amazon Bedrock AgentCore and Strands, leveraging semantic and episodic memory to ground AI agents in verifiable precedents.
We’ll conclude with a live use case in financial decisioning, demonstrating how Context Graphs reduce hallucinations and provide built-in explainability for regulated environments.