Summary
The post highlights the growing pain of workflow orchestration for data scientists, especially with AI-driven, agentic pipelines that can fail in unpredictable ways. It features Adam Azzam from Prefect explaining their open‑source Python library for orchestrating and monitoring pipelines, along with their Marvin AI engineering framework and ControlFlow agent workflow system. The author presents these tools as practical solutions to bring visibility and reliability to modern, dynamic workflows.
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