Build AI Pipelines with Apache Airflow 3

Apache Airflow® has long been the control plane for data pipelines. As AI workflows move into production, teams are discovering the same challenges apply: LLM calls fail, embeddings need regenerating, and agent outputs need human review. The operational discipline that Airflow brings to data pipelines is exactly what AI workflows need too.

Rather than managing data pipelines in Airflow and AI workflows in a separate system, Airflow lets you build both in one observable, reliable control plane. You get scheduling, retries, lineage, versioning, and human-in-the-loop capabilities for your LLM tasks the same way you already have them for your SQL transformations.

In this hands-on workshop, you will build an end-to-end AI pipeline using Airflow’s LLM task decorators, all in your browser, no setup required. The scenario: processing customer reviews for AstroTrips, a fictional interplanetary travel company, with LLM analysis, intelligent routing, vector embeddings, and an AI agent that drafts responses, all with human-in-the-loop approval.