Measuring AI's effect on engineering
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
measure effect honestly across about 20 teams.
Planned topics
- Take baselines before rollout: lead time, review time, defect rate, change failure rate, survey data.
- Compare adopting and non-adopting teams with caution; note confounders such as team size and work type.
- Track quality counter-metrics: defects, incidents, review load, security findings.
- Report ranges and caveats; avoid claims of a single percentage gain.
Draft outline details
Demonstration
a measurement plan table: metric, baseline, source, comparison group, caveat.
Check your understanding
Why track quality counter-metrics?
Show answer
Faster output can hide more defects or review burden.
Practice
Apply this lesson with the module's lab, exercises and quiz.
Marking a lesson complete is optional and you can undo it any time. Your progress stays in this browser.