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This conference talk from PyCon US presents a Python-powered Tech Debt Framework designed to help development teams manage technical debt in large legacy codebases with 100,000+ violations. Learn how to implement a systematic approach that tracks progress through visualization of tech debt trends, recognizes developer contributions with leaderboards and automated acknowledgments, and automates fixes for repetitive debt patterns. Discover real-world case studies showing how teams reduced 70,000+ pyright-ignore annotations to increase type-checking coverage from 60% to 99.5% and successfully converted a monolithic synchronous codebase to asynchronous architecture. Gain practical strategies for scaling Python automation, building team buy-in, and systematically reducing technical debt across massive codebases, whether dealing with type errors, legacy dependencies, or async transitions. This 34-minute presentation provides a comprehensive roadmap for creating cleaner, more maintainable code at scale.
