Production Monitoring & Career Portfolio · 45 min · Python · GitHub API · Debt Dashboards

The AI Code Debt Strategy

Track and pay down AI-introduced technical debt. 100k+ surviving issues growing rapidly since early 2025. Issue survival analysis, debt dashboards, and paydown strategies.

Real-world application: Engineers who manage AI-introduced technical debt demonstrate strategic thinking and long-term code quality management.

What you will learn

Track AI-introduced technical debt using issue survival analysis
Build debt dashboards showing surviving issues, age distribution, and resolution rate
Apply paydown strategies: debt sprints, issue triage, and prevention measures
Understand the 100k+ surviving issues trend and its implications for code quality

Introduction

The AI Code Debt Strategy

Objective

Run the debt strategy simulator with 500 AI-introduced issues. Observe the issue survival analysis (total, surviving, fixed, survival rate, age distribution, severity distribution), 4 paydown strategies, 12-week paydown projection, debt sprint plan, and key takeaways.

Track and pay down AI-introduced technical debt. 100k+ surviving issues growing rapidly since early 2025. Issue survival analysis, debt dashboards, and paydown strategies.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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