Learning to Work with AI
A structured course for discovering, mapping, and testing AI-augmented workflows — built for teams who make things.
Start the CourseFoundations
The conceptual groundwork for the curriculum.
Understanding Your Work
Before you can improve a process, you need to see it clearly. Learn to articulate the invisible steps in your daily work.
4 lessons Cluster 2The AI Primitives
Understand the building blocks of AI tools — models, prompts, projects, and connectors — so you can use them deliberately.
4 lessons Cluster 3Using the Lab
A hands-on walkthrough of the AI Process Lab interface — boards, nodes, connectors, and how to build your first flow.
5 lessonsSpecializations
Applying foundational concepts to specific domains.
Mapping Your First Flow
Put it all together — map a real deliverable from your work as a complete flow, step by step.
4 lessons Cluster 5Experimenting with AI
Design and run experiments to test whether AI actually improves specific steps in your workflow.
5 lessons Cluster 6Measuring What Matters
Learn to track the right metrics so your experiments produce actionable insights, not just interesting outputs.
4 lessons Cluster 7Working with Your Team
Your workflows do not exist in isolation. Learn to collaborate, get reviews, and build on each other's discoveries.
4 lessons Cluster 8Real-World Scenarios
Worked examples showing how different roles can map and test their specific workflows.
5 lessonsThe Approach
This is not a course about AI tools. It is a course about your work — and how to see it clearly enough to know where AI belongs and where it does not.
You will map your own processes step by step, identify where time and quality get lost, design experiments to test whether AI can help, and measure the results honestly. The methodology is grounded in peer-reviewed research from Harvard, MIT Sloan, INSEAD, and IDEO — adapted for practitioners who ship real deliverables every week.
The course requires effort. You will not passively read about AI capabilities. You will articulate your workflows, write your own prompts, run your own experiments, evaluate your own outputs, and document your own decisions. That is the only way to build genuine fluency.