“Would you like to see me do something in 3 minutes that used to take 4 hours?”
This was one of many incredible moments at last night’s nonprofit showcase, where 10 nonprofit leaders got up on stage at Google’s executive briefing space at St. John’s Terminal to present the results of 10 weeks’ worth of tinkering, building, and well…hacking.
At the celebration, this particular leader proceeded to show how, through a cleverly structured prompt series using Claude, she successfully created a “policy bot” to help her quickly cross-reference complex state policy documentation to answer questions from her constituents in mere minutes (as opposed to hours). Other AI-enabled workflows showcased in yesterday’s presentation included streamlining categorical coding, generating near-instant micro-apps for classroom use, leveraging content generation tools, and improving processes for tracking data in logistically complex systems.
Notably, few if any of the participants in our pilot cohort of Decoded Futures would self-identify as a programmer or software engineer. But, with just a little bit of AI know-how and some structured frameworks to encourage design thinking, by the end of our 10-week, six-session program, everyone successfully deployed an MVP (“minimum viable product”) to augment a part of their nonprofit workflow using AI.
Further proof that in the age of AI, anyone can call themselves a developer.
In Our AI-Native Era
Decoded Futures is a new initiative stewarded by the Tech:NYC Foundation with the support of the Robin Hood Learning + Tech Fund and Google. Over the past six months, I’ve had the privilege of serving as the interim Program Director during the pilot phase, which also included one-off workshops and office hours sessions for nonprofits. Overall, this role has been a fantastic opportunity to deepen my understanding of AI while exploring the nuanced challenges that education and workforce nonprofits face in this era of rapid technological change.
To commemorate the conclusion of our pilot phase of work, Decoded Futures also released yesterday a landmark study on the state of AI adoption among nonprofits in NYC, which you can read here.
One of the best parts of this work was getting the chance to tinker, experiment, and play with AI tools on our own at Decoded Futures. Throughout this entire pilot phase of work, our Decoded Futures team eagerly dove into new AI tools and workflows to try on our own.
To that end, it felt important to us that we also used AI to help deploy and launch research. So, just in case you don't have time to read through a 55-page report, we've got you covered with some alternative options.
1. Listen to a podcast version of this report, created with Notebook LM.
2. Tune into just the key findings with an album of custom songs, generated by Suno.
3. Ask our "research assistant" bot to tell you some of the highlights and key findings.
(Special shout out Bryan Lozano - aka: "No Code Bryan" for this one, which you can access here. We welcome your bug reports on its quality control...)
Where We Go From Here
As our research revealed, the "last mile" of AI implementation is often the hardest hurdle to clear. Our team experienced this firsthand in our own application of AI tools. This challenge underscores the importance of continuing to bridge the gap between the cutting edge of technology and the vital work being done by New York City’s 46,000 nonprofits.
AI is transforming everything about how we learn and work. What makes Decoded Futures so compelling is that we began this journey right at the heart of this transformation, focusing on nonprofits dedicated to education and workforce development.
This unique perspective allowed us to carry trends directly from the forefront of tech innovation into the hands of nonprofit leaders, enabling meaningful collaboration and experimentation. It’s a powerful reminder that we’re building together in the same sandbox. After all, that’s what makes working in tech so exciting—and working in tech in New York City absolutely extraordinary.
Special thanks to Decoded Futures EIR, Jake Porway, as well as Julie Samuels and Bryan Lozano at Tech:NYC, Jackie Moe with Decoded Futures, Amber Oliver with the Robin Hood Learning + Tech Fund and Sarah Henderson with Google, for all of their support in conceptualizing and iterating on this important pilot.
