Your AI agents are only as good as the context they have access to. Every engineer wants to build self-improving AI systems, but your agents can only get smarter if they understand how decisions in your organization are made.

This webinar breaks down how to build a self-improving AI agent for customer support with Airflow: from ingesting and transforming data from multiple sources into AI-ready context, to tracing human and agentic decisions and structuring them into a context graph.

You’ll learn how to:

• Use Airflow to gather raw data from multiple sources and transform it into structured, AI-ready context
• Add Agent-as-Judge and Human-in-the-Loop steps to your pipelines
• Build decision-tracing context graphs that make your agents smarter over time