Module 2 of 3

The Impact on Engineering Teams

Productivity claims examined: what changes about code quality, review, and team knowledge when coding agents are in the loop

The productivity headline numbers are real, but they're averages, and they come with caveats. This module examines the underlying evidence, the error patterns that emerge when coding agents are in the loop, and the harder questions about what happens to code quality and team knowledge over time.

An Intro to Coding Agents
  • ~50 mins
  • 3 lessons
  • professional
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What you'll learn

  • Evaluate productivity claims for coding agents against the available evidence, including what the studies measure and what they don't
  • Describe the new error patterns that emerge with coding agent use: plausible-but-wrong code, novel security issues, and confidently incorrect logic
  • Explain how coding agent use changes code review practices and what new review skills the context requires
  • Articulate the knowledge and ownership risks that emerge when teams rely heavily on AI-generated code

Lessons in the Module

1 What the Research Shows 20–25 mins
2 New Error Patterns, New Review Practices 20–25 mins
3 Knowledge, Ownership, and Technical Debt 20–25 mins
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