💯 Digest: What 30 mins of AI a day really taught me

30 Days of AI | AI Bootcamps | Past Issues 

👋 Hey, it's Max

We just wrapped the 30 Days of AI Challenge. 30 minutes a day for 30 days. And It’s strange that after five years of teaching people to build online and thirty days of shipping lessons, you think you know what the story is.

I started 30 Days of AI (and 100 School before it) thinking it was about momentum. 30 mins a day to learn the tools, build the thing, stay consistent… But somewhere in between, I realized this was less about AI and more about identity.

The habit was the real product

We didn’t design the challenge to make anyone an AI expert in 30 days but so you’d keep showing up. Thirty minutes is enough to build momentum, but too short to talk yourself out of it. And it worked. Most people didn’t say “I learned X tool” but they said things like:

• “I expected it to be difficult & complex. Every day made it more approachable. I’m less afraid to experiment now.”

• “One thing I didn’t expect to learn was how much AI would change the way I think, not just what I can create.”

That’s the stuff I care about. It’s what I’ve seen again and again since the early 100 Days of No Code days and 100 Days of AI after it. You start for the tools and stay for the mindset shift.

Btw, if you’re still mid-way through your 30 days, keep going! You’re already building the muscle. You can always catch up from wherever you left off (the lessons are still live) or join us for the next round in November.

Learning AI is mostly learning to trust yourself again

Throughout the past month, we asked learners to submit their feedback and reflections at different checkpoints and at the finish line. After reading over 500 submissions, I realised that actually.. nobody’s struggling with AI.

What surprised me most is the word that kept showing up is confidence. To be honest, I expected GPT, automation, or workflow, maybe even productivity. About 80% of those who shared reflections described feeling “more confident” or “less afraid of breaking things.”

Over 80 percent said they’d never built anything before this challenge. By the end, they’d shipped dashboards, chrome extensions, personal assistants, and learned that being non-technical isn’t a fixed trait. And that’s when I realized that we’re not teaching people how to use tools but to trust their ideas again.

If you’ve ever tried to stick with anything for a month straight (journaling, running, learning a language, reading, etc..) you know what it means. So if you just finished the challenge, celebrate that. You earned it.

The messy middle is where growth hides (and the data proves it)

Around week two of the challenge, submissions started to dip. People got busy and energy dropped. But those who stayed (even sporadically) ended up rating the challenge an average of 9.2 out of 10 in the final feedback form.

That has become my favourite insight. You don’t need more content but need a reason and momentum to come back to. And as much as I loved reading what people loved (daily structure, hands-on projects, community), I can’t forget about the ones that mentioned time. Some lessons felt too long and some days they just couldn’t keep up which reminded me that even great learning design needs oxygen.

So as we design the next rounds, we’ll be building in more re-entry points as well as intentional pauses. If you want to be part of that redesign, join the next cohort, we’re shaping it from real feedback.

The hardest thing about teaching AI is remembering we’re teaching humans

When I started teaching no-code, I used to think progress meant cleaner frameworks and better tools. Now, I obsess over feelings. Because if someone feels stupid, or intimidated, or late, they’ll stop learning. And if they feel seen, encouraged, and part of something, they’ll build anything.

As cliché as it sounds, the real lesson from these 30 days is that AI didn’t make this challenge special, people did. People sharing broken prototypes, half-finished ideas, “this doesn’t work but I’m proud of it anyway.”, and even handwritten reflections from their journey. That’s what makes learning sustainable.

And sometimes, that learning doesn’t stay personal. It becomes collective.

Alina from Headway (a company I followed and admired for years) has been sharing with us how her and her team have been experiencing this challenge and what came out of it.

Another moment that stuck with me was hearing from Dan Mowinski who first reached out on August 30th to say he’d be livestreaming his 30 Days of AI experience at 6 a.m. every morning.

Thirty days later, he completed the challenge and created a shared experience around it. His posts became a kind of mirror for what this whole thing is about: accountability, curiosity, and the courage to learn out loud.

I keep coming back to that idea of collective learning. One person starting something that others want to join. Honestly, writing this, I almost feel guilty not mentioning everyone. There were so many examples this round of people who rallied their teams, tagged coworkers, nominated friends, or even started mini spin-off challenges at work. I’ll be highlighting more of those stories in the coming weeks, because each one shows a different shape of what shared learning can look like.

For now, if reading this makes you think of your own team and makes you wish could start experimenting together, I’m offering Free AI Audit for Teams. a 30-minute session where we look at how your company’s already using AI (often more than you realize) and where simple training could multiply that impact.

If you’ve been the one responsible for getting your team to use AI, this is the easiest way to start the conversation. Book your free audit 👇

We just wrapped the 30 Days of AI, but it doesn’t really feel like an ending. It feels like the start of a new rhythm, one where more people are building, teaching, and learning together.

Thanks for building with us! You made this challenge feel alive.

Here’s to whatever you build next 🤞

Max 👋

P.S. Want to make your team & company AI-first? Let us help here.