Most founders hide their prototypes until they’re polished. I let 500 kids and a grad student class break mine in real time. It's not enough.

When I started building MuseKat in January, someone asked me early on if I was going to blog about my experience in building the app. I said, “Absolutely not.” But then, about a week later, I did it anyway, which was a very scary experience for me.

I spent 15 years in tech getting told (either implicitly or explicitly) that there were certain things that would always be out of reach for me if I didn’t know how to code.

And since I’d never before expressed an idea into a piece of software, I was nervous about how it would be received on the other end.

Showing my work publicly made me feel a bit like a kindergartener showing Picasso a crayon drawing of a rainbow. (On paper, it’s a no-contest comparison about who’s the better artist.)

But that’s not how it came across to my network.

In fact, I was surprised by how much support I received even as a non classically trained engineer who "vibe coded" her first app. So I started sharing more, at demo days, meetup groups, and podcasts.

Naturally, at one of my first public demos, one of the first questions I received from an audience member was: 

“If you built this in a weekend, what’s to stop someone else from building this too? Why are you sharing this?”

Of course. This is the canonical question of building in public. Why share if someone else might steal it? Why share your process unless you’re inviting someone else to duplicate it?

It’s true that in this AI age (where ideas are cheap and prototypes are cheap and execution matters more than ever), I’ve noticed a shrinking back of in-public builders. People seem more afraid to share, lest someone else recreates a better version of the very thing they coded the next weekend, or invites indie hackers to intentionally sabotage or break what you built. So people are holding ideas back, retreating into smaller spheres of influence, or hiding out until just the right moment for the big reveal.

As one VC put it on LinkedIn recently: “Your launch becomes another startup’s lunch”

"I’m thinking about my next startup, talking to lots of AI founders and VCs. Here’s what I’m seeing:

This market moves brutally fast. No one has seen anything like this before.

A startup announces a round, ships a product.
Within weeks: five clones.
One is cheaper. One is open source. Another is already running ads.
Your launch becomes their lunch.

Speed isn’t an advantage anymore. It seems like a liability unless you have real lock-in."
- Zain Jeffers

Don’t think for a second that I haven’t panicked about someone with a better business brain and stronger engineering chops recreating what I’ve already built. I’ve worked in this industry long enough to be very clear-eyed about my own strengths and weaknesses.

But in a way, that’s exactly why I had to share it: To find other people who care enough to help me on those weaker spots. 

What I’ve found, five months later, is that the benefits of building in public far outweigh the risks of keeping things private. The slow, consistent external signaling to my network keeps me top of mind for lots of people. It makes people more likely to think of me as the “kid learning app person,” to send a potential product idea or competitor my way, to refer a friend as a beta user. 

Surprisingly, even at this early stage, it’s already attracting other like-minded people who want to build with me. And in a company of one with no one else waiting on me to deliver results, it’s often the only way I can hold myself accountable to keep doing the work. In a way, my network is becoming the moat around my own ideas. I’m essentially banking on the goodwill of my network to support me in my endeavor vs. launch their own rival product.

But it’s not enough. The questions being introduced as we introduce AI into our daily lives at warpspeed are unlike anything we have seen before. There are too many questions we can’t answer on our own.

Things are moving too fast for any of us to keep up alone. It would be irresponsible to build in a vacuum.

When the pace of AI development starts to outstrip our collective understanding, staying silent isn’t just risky: It's borderline unethical.

There's a lot to be worried about in some of the predictions outlined in the AI 2027 research think piece, which outlines two stark global trajectories as we approach the threshold of superintelligent AI. In the end, both possible outcomes paint a chilling picture of what might happen when human input becomes obsolete.

This sounds like scary sci-fi reality. And as a mom raising two young girls at the precipice of this impending prediction, I ask myself this question almost daily: How am I supposed to talk to my kids about AI?

I'm not alone. What hit even harder were the real parents I've spoken to while building MuseKat.

It's like we all know we are raising the AI-native generation but also aren't sure what to do about it. And in a world where only 18% of teachers are using AI in the classroom, a substantial part of this learning will need to happen outside of the classroom. But how?

I started MuseKat because I believe that AI enables us all to embark on learning journeys outside of traditional learning environments. But even something as playful as my app (where a friendly, AI-powered meerkat tells kids stories about the world) raises big, thorny questions:

I can’t solve these on my own; it feels delusional and borderline unethical to presume otherwise.

That’s why, for the first cycle turn of MuseKat, I did the thing that I always said people should do if they are starting an education company: I invited students into the build cycle with me.

Over the past semester, while I’ve been hard at work getting a beta version of MuseKat live in the App Store, I’ve also been actively seeking out active participation from students in classroom spaces all over the city. I've spoken at colleges and elementary career days. I've partnered with high schoolers and young adults, I've interviewed dozens of parents of young kids, and I've really done my best to listen to their stories.

For this series, I wanted to share about four unique student-led activations. I'll share each one as its own case study on this blog this week.

In each case, we have hit on tricky question in real time about AI use – some I’ve been able to answer, others I haven’t. I’ve benefited immensely from the diversity of perspectives, and I’ve been able to introduce things from the front lines of cutting-edge technologists in many classrooms that haven’t yet shaped AI policies of their own.

In this series, I’ll share a bit more about how I set up each of these scenarios and why it’s been so impactful for me as an early-stage startup builder to be so immersed with different facets of the public as I build out this product, hopefully setting the stage for whatever happens next.