This article was originally published on Forbes.com as part of the Forbes Communications Council, featuring insights from Cade Collister, Chief Creative Officer at Metova.
I spend my days helping teams ship humane, useful products—and my nights answering tough questions from my kids about AI, robots and “what job will I have when everything is automated?” Lately, one idea keeps peeking around the corner: microschools. These tiny, nimble learning communities look a lot like cross-functional product teams. Could they be the best place to teach the habits of UX, the literacy of AI and the creative grit tomorrow’s tech roles demand?
First, a quick reality check. Microschools aren’t a monolith. They range from one-room learning pods to networked academies, often fewer than two dozen learners, built around flexible schedules and project-based work. A 2024 sector analysis from the National Microschooling Center (NMC) pegs the median size at 16 students and finds project-based learning as the most common instructional approach. That same report cites earlier EdChoice estimates suggesting 1.1 million to 2.1 million learners in microschool settings, while more recent commentary puts the count at roughly 95,000 microschools serving about 1.5 million students. The truth: This space is growing fast and is still under-measured.
UX, AI And The Classroom
From a UX lens, this format is intriguing. Good designers master discovery, prototyping and iteration. Good engineers learn to reason with systems. And good AI practitioners cultivate literacy in data, ethics and model limits. Microschools can hard-code those habits into daily routines because they aren’t locked to bell schedules or pacing guides. They can ship learning in sprints, hold retro meetings on projects and let students test their work with real users (neighbors, parents, local businesses) in ways that feel authentic—not performative. That’s not just romanticism: Meta-analyses show project-based learning can meaningfully boost achievement and thinking skills when done well.
If we want kids job-ready for AI-infused tech roles, we must also teach AI with the same UX humility we bring to any unproven feature. Classroom AI tutors, for instance, are ascendant—but still maturing. Khan Academy’s Khanmigo has seen wide district adoption, yet leaders there note they haven’t run a randomized control trial to establish efficacy (they plan to). That’s a perfect teachable moment: Students can learn to interrogate the tool’s strengths and limits, not just treat it as a magic answer box.
What content belongs in a UX-and-AI-forward microschool? We can anchor to widely cited policy guidance rather than hype. UNESCO urges human-centered, responsible use of generative AI in education; the OECD’s “AI and the Future of Skills” work explores how curricula might shift as machines take on more language and reasoning tasks. The implication for kids isn’t “learn to prompt”; it’s “learn to frame problems, question data and design with ethics.”
We also need a design spine. The K12 Lab at Stanford’s d.school maintains practical tools for design thinking in classrooms, and the Design Thinking in Schools directory shows how widely the approach has spread. In a micro setting, you can make design the operating system, not just a once-a-semester unit. Think studio critiques, field research interviews, wireframes and service blueprints pinned to the walls—plus apprenticeships with local companies when projects need real constraints.
And yes, there’s a career case. The U.S. Bureau of Labor Statistics projects web developers and digital designers (a category that commonly includes UX roles) to grow 7% from 2023 to 2033—faster than average—while graphic-design-only roles grow much more slowly. Translation: Hybrid skills that blend design, code and product thinking remain durable, especially as AI reshapes workflows.
The Promise And The Pitfalls
So, could microschools be the answer? Maybe. They are exceptionally well-suited to cultivate the dispositions that modern tech work rewards: curiosity, collaboration, critique and continuous improvement. But there are sharp edges. Accountability and equity matter. As public funds and vouchers touch more microschools, policymakers and operators will need transparent outcomes and safeguards so innovation doesn’t widen gaps. Families deserve clarity about costs, quality and pathways back into public systems if needs change.
Here’s what a lean, UX-centric micro program might ship in its first year:
Weekly design sprints (research → prototype → test → iterate) tied to community problems,
AI literacy labs that compare human versus model performance and discuss bias,
Portfolio-grade projects in product design, front-end dev, and data storytelling,
Studio crits with local designers,
Ethics workshops using UNESCO and OECD frameworks, and
Apprenticeships with startups for authentic scope and deadlines.
Do we need microschools to do this? Not exclusively. A great public school with an empowered principal can run the same playbook. But microschools lower the coordination cost. They’re fast, personal and permission-light—closer to a product lab than an institution. Acton Academies, for example, have shown how learner-driven, project-heavy environments can normalize apprenticeships and real-world deliverables—ideas any district could borrow.
Designing The Future Of Learning
If we treat this as design work, the path forward is clear. Start small. Co-create with learners. Test AI tools with rigor. Publish outcomes. And keep the doors open—literally—to your community. Whether you build a microschool or graft these practicces into a traditional campus, the goal is the same: Graduate kids who can frame problems, design with empathy and collaborate with machines without surrendering judgment.
I can’t promise microschools are the answer. But as a UXer watching AI accelerate, I’m convinced they’re a promising prototype. And like any good prototype, what matters isn’t that it’s perfect. It’s that it’s honest, learnable and built to iterate.
