Rockefeller Reflections: Building the Future of EdTech One Byte at a Time

In this episode of EdTech on the Street, I found myself standing in front of Rockefeller Center with Kiara in the heat of summer to talk about data synchronization and data privacy. Specifically, we discussed how many school districts are still running on outdated infrastructure, and how they can prepare for a future that is already here.

AI is not coming. It is already woven into the fabric of education. What is striking is that most systems are not built to handle what comes next.

What You’re Building Today Won’t Last Five Years

That is the uncomfortable truth.

At ISTE Live 2025, I noticed something different. The largest booths were not selling curriculum or classroom tools. They were selling data platforms and AI software. Everyone is focused on infrastructure now. That is a signal.

As I sat down for my interview, one question echoed in my mind: “How can schools prepare for an AI‑driven future when their systems were built for a textbook era?”

The answer: do not build big. Build smart.

Long gone are the days of massive, monolithic systems. They do not age well. They are expensive to replace. By the time they are implemented, they are often already outdated. Instead, the future lies in microservices: small, purpose‑built programs that can adapt, update, or be swapped out entirely without crashing the whole ecosystem.

Micro‑decisions are the new long‑term strategy.

The Real Challenge Isn’t the Tech, It’s the Translation

Data syncing is not about one system talking to another. It is about speaking the same language, and that is where standards come in.

If districts are serious about real‑time integration across LMSs, VR platforms, adaptive learning tools, and generative AI apps, they need to prioritize systems that align with open standards like Ed‑Fi and OneRoster.

Otherwise, it is like building a city where every neighborhood uses a different power grid. You will never get the lights on everywhere at once.

There is nuance here. Standards are not just about efficiency. They are also about accountability.

Phase One Is Here, Phase Two Is Coming

Right now, generative AI is in what I call Phase One. It is helping teachers write lesson plans, students translate texts, and administrators summarize reports. That is useful, but it is only at the surface level.

Phase Two is deeper and more personal. It is about AI learning how students learn, what motivates them, where they get stuck, and when they thrive. It is personalization at scale, and it relies on one thing: data.

AI Is Here: Stop Resisting, Start Designing

My favorite moment in the conversation was near the end, when we were not talking about systems or security. We were talking about students: what kind of thinkers, citizens, and people we want them to become.

That is the real endgame here.

AI is a tool, one that is evolving faster than any generation of technology before it. But it does not define us; we define how it is used. If we are thoughtful, ethical, and brave enough, we can design an education system that empowers learners, protects their privacy, and adapts as fast as they do.

Filmed live at Rockefeller Center, NYC. Part of the “EdTech on the Street – Real Talk in the City That Never Sleeps” video series by Magic EdTech.