Workflow experiments and measurement
A workflow experiment is a small, time-boxed comparison: AI-assisted vs. baseline, with a metric you actually trust. This module teaches how to design one, how to instrument it, and how to call it.
What you will learn
- Design a 2-week experiment for one workflow.
- Pick metrics that can’t be gamed by either side.
- Read results without overfitting to a small sample.
How you’ll learn this module
Built around evidence-informed learning methods. Designed to support retrieval practice, feedback, and spaced review.
Learn brieflyAttemptGet feedbackRetryReview laterApply in a workflow
Topics covered
Experiment shapesSide-by-side, before/after, shadow.
Metric designTime, edits, accuracy, satisfaction.
Sample sizeSmall honest > big sloppy.
Calling itAdopt, iterate, stop.
Suggested learning sequence
01
Design
Sketch one experiment. ~20 min.
02
Run
Run it for 2 weeks alongside normal work.
03
Read
Review evidence and call the result. ~20 min.
Practical exercises
- Design a 2-week experiment for the workflow you most want proof on.
- Choose two metrics — one quantitative, one qualitative — before starting.
Practice with the AI Tutor
Run this module on a real workflow
Bring one piece of work into the tutor. It turns this module’s topics into risk flags, a practice mission, an experiment, and an evidence record.
Open the AI Tutor for this module