AI learning is better together

Two team rituals that made learning AI tools actually fun

We live in a working world of endless Slack messages, video meetings, document and design reviews, all while fighting for actual time to design. When we add learning AI tooling amidst its constant evolution, it can feel like there’s never enough time.

Whenever I start to feel a hint of overwhelm, I take a step back and ask, “How do I learn best? How do I make this fun?” I know I learn best with a group of fellow humans that meet regularly, feel safe laughing about what’s new and hard about what we’re doing, and encourage each other to keep trying and sharing new work.

For the past six months, I have been experimenting with how to encourage designing with AI based on this question: how do we create a virtuous cycle of make, learn and share? These are my two favorite approaches.

AI jam time

Six months ago, I repurposed all empty design crit slots into an AI jam and study group and I haven’t looked back. This small group works on personal or work projects, shares progress for feedback, and tries new tools together. I intentionally seeded the group with a few enthusiasts who help onboard teammates and happily explain their approaches. These designers will sometimes lead sessions to try out a new product or feature, like Claude Design. It’s the collective, “Oh cool, I love how you did that, I’m going to try too!” that makes learning fun versus forced.

Lesson: Learning comes when we feel open to explore and try things, not stressed out that we are behind or don’t know as much as the next designer. The biggest gift we can give our teams is focus. We need to give teammates structured time to play together.

AI design show and tell

I also co-lead a bi-weekly AI design show and tell series where two presenters share tools, prototypes and access to their files. Each person has 20 minutes to present their work and cover the following:

The Good

• Describe what this is. Go slower over foundational concepts in the beginning given the audience is at different levels of experience.

• What inspired you to build this prototype or tool?

• Was there a use case that felt like a genuine breakthrough?

• How did it change how you approached your work?

The Reality Check

• How did you create this? Share your approach, workflows, and prompts.

• Where did you get stuck and how did you overcome it?

• What’s one thing that surprised you?

• What would you do differently next time? OR What’s one thing you wish you’d known before starting?

The Practical Stuff

• How much time did you spend learning versus using it?

• How does it integrate well with your existing workflow?

My co-host and I also share these learning mantras at the beginning of every session:

• I’m not behind, I’m learning

• I’m not alone, I can ask my team and AI for help

• If I can dream it, I can make it

As a leader, it’s helpful to be enthusiastic and highlight key behaviors you want to encourage. Sessions are consistently well-attended. I’m grateful our team is so comfortable asking questions and engaging in the work. If these approaches aren’t possible for you, find study buddies at school or outside of work, make things weekly, share your work, and try one small new feature at a time.

Lesson: Building skills come from not just practice time but consistently seeing others pushing the boundaries of AI tooling so they believe they can do it too.

Final thoughts for now

Being a leader today isn’t having all the answers (those answers are stale anyway); it’s to keep going amidst the ambiguity to figure out new ways of working and thinking with your teams. At first, I was uncomfortable no longer leading from experience, but I’ve decided to enjoy leading with curiosity. When you take on that mindset, you realize there is actually no greater time to be a designer like today.