To Bin or Not to Bin: A Tutorial on Fast Feedback Loops for AI Capabilities (alexhans.github.io)

A new hands-on tutorial titled "To Bin or Not to Bin" has been released, focusing on enhancing AI capabilities through efficient feedback loops. The tutorial addresses a practical problem—determining which bins need to be taken out for collection—and guides users from initial prompt development for an AI agent to implementing automated checks and eventually executing straightforward code without relying on a model. This step-by-step approach ensures that functionality is verified at each stage, emphasizing rapid iterations without compromising the integrity of the AI system. This initiative is significant for the AI/ML community as it highlights the importance of creating agile environments where AI agents can be modified quickly and reliably. By utilizing tools like Claude Code, Apache Airflow, or cron for scheduling, practitioners can streamline workflows and ensure their AI systems remain effective under changing requirements. This tutorial not only serves as a practical resource for AI developers but also complements the upcoming Airflow Summit 2026 talk, "It Works! Now What?", making it a timely contribution to the ongoing discourse on improving AI deployment processes.