Review discipline and measuring quality
On This Lesson 4 topics
This lesson is planned. The outline below lists the topics it will cover. The full lesson has not been published yet.
In this lesson
review AI output rigorously and measure real effects.
Planned topics
- The author is responsible for every line they submit, whoever or whatever wrote it.
- Mark AI-originated changes in the description; keep a prompt log for traceability.
- Check for hallucinated APIs, missing error handling, security issues, and license concerns.
- Measure review time, defect rate, change failure rate, and test quality; not lines produced.
- Compare before and after on a team basis and adjust practice.
Draft outline details
Demonstration
a small dashboard: review time, escaped defects, mutation score, per month.
Check your understanding
Why is "lines generated" a poor measure?
Show answer
Volume says nothing about correctness or value.
Practice
Apply this lesson with the module's lab, exercises and quiz.
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