Most teams meet AI as a procurement decision. Someone approves the licences, books a lunch-and-learn, and waits for the productivity to show up. It usually doesn't. The missing piece is fluency. Access to a tool is not the same as knowing how to use it well, and that is what this course is for.
What this means for your team
AI fluency has a plain definition: working with AI in a way that is effective, efficient, ethical and safe. Read that back with your own team in mind. Most of the friction you are seeing is one of those four words going missing, not a tooling problem.
There are three ways your people work with AI:
- Automation. They hand over a defined task and take back the result.
- Augmentation. They think alongside it, back and forth, as a partner.
- Agency. They set something up to run on their behalf.
Most teams live almost entirely in the first one. The value, and the risk, sit in the other two.
The rest of the course is built on four habits, the four D's from Anthropic's framework (the work of Rick Dakan and Joseph Feller):
- Delegation. Deciding what to hand over in the first place.
- Description. Telling the AI clearly what you actually want.
- Discernment. Judging whether what comes back is any good.
- Diligence. Owning what you then do with it.
Build these as capabilities in your people. The course takes one D at a time, with a short video and a note from me on what it means in practice.
Try this
Before the next lesson, ask three of your people what they last used AI for, and what they did with the answer. The ones worth talking about are where someone took the output and ran with it without checking. Bring one of those examples to your next team conversation.
Common questions about AI fluency
Why doesn't buying AI tools improve a team's productivity?
Because access to a tool is not the same as knowing how to use it well. Most teams meet AI as a procurement decision: someone approves the licences, books a lunch-and-learn, and waits for the productivity to show up, and it usually does not. The missing piece is fluency, the habits people build around the tool rather than the tool itself.
What are the three ways people work with AI?
There are three ways to work with AI, and most teams live almost entirely in the first:
- Automation: you hand over a defined task and take back the result.
- Augmentation: you think alongside it, back and forth, as a partner.
- Agency: you set something up to run on your behalf.
The value, and the risk, sit in the second and third, which is where fluency starts to matter.
Do I need to be technical to be AI fluent?
No. AI fluency is about how you and your people work with AI, not about understanding the technology underneath. The habits this course builds carry from one tool to the next, so you are not learning prompts or settings that go out of date. If you can describe what good work looks like, you already have what it builds on.