Break the brief open.
Turn a training request into a problem brief. What are the assumptions? What don’t you know yet? What do you need to ask stakeholders?
Back to the homepageDesign with AI.
Design with AI.
Think beyond the course.
An eight-week Learning Design Lab pilot for experienced instructional designers. Work on your own project with AI as a strategic partner: from the first brief to what needs to change in practice.
Add me to the waitlistNo commitment. You’re not signing up for the Lab.
AI shouldn’t have the same job throughout a learning project
A lot of AI use in instructional design still starts with the same question: what can it make for me?
That’s useful when you need a first draft, a scenario or something built faster. But making something is only one job AI can do.
Early in the project
AI challenges the diagnosis.
While shaping the solution
AI helps explore or test an option.
During build and review
AI can produce, prototype or look for weak spots.
Early in a project, I might ask AI to argue that the training request is based on the wrong diagnosis. That’s a very different job from asking it to write the storyboard later.
Once the direction is clearer, I can use it to explore another option or test an idea before I commit to it. Later, AI can help with the build or look for weak spots in something that already exists.
Different stage, different job for AI.
You don’t need to become an AI engineer to work this way. You do need to know what you want AI to do, why you’re using it there, and when the choice still needs to be yours.
The Learning Craft Loop
Better learning starts
with a better question.
The Learning Craft Loop is my framework for turning a training request into informed design decisions. You explore what is needed, make it tangible and learn from what happens at work.
AI helps you think and build. You stay responsible for the design decisions.
SenseUnderstand
What is stopping people from doing it well?
Look beyond the training request. Explore the desired behavior and the working environment. Not every problem calls for a course.
AI helps you examine assumptions and possible causes.
What you work toward
A clear problem and a deliberate decision on whether to design a learning solution.
CreateMake
What helps someone when it matters?
Choose the right form: practice, a scenario, a job aid or a learning experience. Make a first version and test it with the people who will use it.
AI helps you explore alternatives and build prototypes faster.
What you work toward
A tangible solution you can test in practice.
LearnRefine
What are people doing differently at work?
Combine observation and feedback with relevant data, for example through xAPI. Explore what works, what does not and which assumption needs to change.
AI helps you find patterns and new questions in the feedback.
What you work toward
Evidence for your next decision: improve, extend or investigate again.
What you learn changes what you see.
That is why Learn leads back to Sense. New insights can change both your solution and your original question.
Practice this approach in the Learning Lab. Refine it through mentoring on your own project. Or have me apply it to your design and development brief.
Your own work is
the learning material.
No made-up company or sample case. You work on a problem you actually need to solve.
Explore real alternatives.
Ask AI to explore different directions and challenge your preferred solution. Training is one option. Sometimes something else fits better.
Capture the why.
Keep a decision ledger: your choice, your reasoning, the assumption behind it and the alternative you deliberately set aside.
Plan for impact early.
Decide what behavior should change and what you will look for after 30, 60 and 90 days. Evaluation starts before the build.
Leave with more
than good ideas.
- A problem brief for your own project.
- A ledger of design decisions and their reasoning.
- A prototype or tested option for your project.
- An impact plan with concrete evaluation questions.
- A way of working with AI you can use again.
For people who know the craft.
And want to look further.
You have experience in instructional design. You’re often handed a solution before the problem is clear. And you want AI to help you think better, rather than just produce more.
You bring a real project and you’re open to critical questions about your own decisions.
Good to know
Is this a course for beginners?
The Lab is for experienced instructional designers. We build on the craft you already know and work on your strategic design decisions.
Is this mainly about AI tools?
AI is part of the whole process. The focus is understanding the problem, weighing alternatives and explaining your choices. A collection of prompts can’t replace that work.
My project is confidential. Can I join?
Discuss what you can share beforehand. You can work with an anonymized version. Always use AI within your organization’s policies.
Are the schedule and price confirmed?
Enrollment opens on October 20, 2026. I’ll share the schedule and price with the waitlist first. No commitment. You’re not signing up for the Lab.
Join the waitlist
Enrollment opens on October 20. The waitlist hears first and gets first access to early bird spots.
You’ll soon be able to join the waitlist here.
No commitment. You’re not signing up for the Lab.
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