Last week, in a room full of 40 nonprofit leaders, I watched three people stand up and run live demos of education mini-apps they built themselves. A program to quickly extract social media-sized content from in-depth research papers. A choose-your-own-adventure guide to deploying a custom hydroponic setup in your own home. An app that turns any project idea into a set of scientific discovery questions for kids to ask at any age.

That not a single person in the room came from an engineering background is notable in itself. That all three of these apps were deployed in under 30 minutes is nothing short of remarkable. 

This event was the first workshop for a pilot program I’m helping launch with Decoded Futures, a new project of the Tech:NYC foundation that helps NYC education and workforce nonprofits enhance their capacity-building with AI. 

In both cases, we used Playlab, an open-source sandbox that helps educators quickly create AI-powered, custom GPTs for their workflows. 

Seeing these nonprofit leaders build apps in real time made me reflect on how AI is reshaping the very idea of who gets to innovate and what it means to be a developer today.

Despite working in tech for the better part of 15 years, I’ve always hesitated to sign up for a live demo at a tech event or meetup. A demo typically means showing off a working prototype of an app that you built yourself—presumably with code. As a non-engineer, this never felt accessible to me.

Many engineers I know spend their weekends or evenings hacking away on quirky prototypes—maybe they train their Hue lights to match the mood of their music, recreate a Web 1.0 app in the Web 3.0 era, or attempt to convert an overflowing inbox into a to-do list for their family. By Monday, they’re showing off their latest hack project back at work, maybe they share a bit more about it on their blog. Sometimes people use it, sometimes no one does. And every once in a while, they’re tempted to show up at a demo day to get real-time feedback from other devs in the room. And so, the cycle of innovation continues.

Over the years, I’ve had plenty of ideas, but I’ve never had the technical autonomy to turn them into real projects. That is, until ChatGPT and other LLMs came along.

These days, I’m signing up for live demos with the best of them. Last week, in a classroom of 20 teachers and administrators, I demoed an app I built with Playlab to help them kickstart lesson plans for a work-based learning curriculum we were designing together. Next week, I’m doing a live demo to 75 students at Columbia to share how anyone can set up a quick custom GPT to dramatically help them improve their interview technique on the job search.

Interestingly, last week, I also attended a more typical Demo Day environment, this one catered to web3 developers building onchain applications with blockchain technology. Like usual, in a room of about 100 people, I was one of about 10 women present. Only one of the 8 presenters was a woman. 

The contrast between that and our real-time Decoded Futures Demo Day environment was striking—nearly 75% of the participants were women, and the cultural diversity in the room was far greater than what I’ve seen in most tech spaces.

It’s moments like these that make me realize just how powerful AI can be in democratizing access to technical innovation. The ability to quickly spin up these micro-apps has leveled the playing field, and I’m excited to see how a new generation of diverse developers will reshape the landscape of innovation.

By the way, you can read more about Decoded Futures and some of the takeaways we had from our first pilot event here.