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Everyone has access to the same foundational models, but the real competitive differentiation is what happens after the API call, in the orchestration layer. Running LLMs in production is where retries cost real money, failures are opaque, and there's no human oversight. Apache Airflow® solved these problems for data pipelines, and the Common AI provider brings that same rigor to LLMs and agents.
In this webinar, we'll show how to build production-ready, agentic AI pipelines on Airflow, using toolsets, durable execution, human-in-the-loop, and more.
You'll learn how to:
- Turn LLM calls and multi-step agents into observable, retryable Airflow tasks with the Common AI decorator suite
- Give agents real capabilities with toolsets, exposing your existing connections and 350+ Airflow hooks as tools
- Understand where Airflow fits alongside agent frameworks, and when to embed agents vs. call external systems
