Airflow users should upgrade to the latest version of Airflow, which offers improved features and performance. Familiarizing yourself with core concepts and components, such as DAGs and operators, is crucial for efficient data orchestration. Keeping DAGs light by avoiding top-level API calls and database connections can improve performance. Processing small amounts of data wisely by using the Kubernetes Executor and custom XCom backend can also help. Consistent coding practices, including idempotency, retries, and provider packages, are essential for a smooth Airflow experience. Staying consistent with project structure and standards can democratize your data stack, making it easier for non-engineers to work with data. Finally, leveraging the Astronomer framework can provide instant deployment of the latest Airflow version, optimized infrastructure, and expert support to accelerate your data strategy.