Experiential learning isn't a trend - it's overdue

This week, I've been having the same conversation over and over with college administrators, college professors, and parents. Everyone's talking about experiential learning for college students.

"How do we give students real experience?" "What does hands-on AI education actually look like?" "How do we prepare people for jobs that don't exist yet?"

It's validating, but also a bit surreal. We've been asking ourselves these exact questions at Flintolabs.

Then I came across an article from the World Economic Forum, and it completely reframed how I think about what we're teaching. The author argues that AI has made the liberal arts crisis worse, because the traditional way of teaching them (reading texts, writing papers) doesn't work anymore when AI can do both.

But here's the insight that made me sit up: experience is the new model for developing human skills. Actual doing! Building ventures, solving real problems, iterating on ideas that matter. The article points to entrepreneurship education programs around the world that teach critical thinking, creativity, and resilience not through lectures but through the hard work of making something real.

When students build AI applications, they're not just learning to code. They're learning to break down ambiguous problems, evaluate their own work critically, and persist when the first version doesn't work. They're developing the judgment to know when AI helps and when it doesn't.

What really gets me is this: colleges are now racing to create these experiential opportunities because they finally realize it matters. But most students won't get access to them until sophomore or junior year of college, if at all. By then, the students who started building in high school are already years ahead.

The workforce is changing faster than education systems can adapt. And the gap between those who know how to do things and those who just know about things is widening every day.

Maybe that's what keeps us going. We're not waiting for permission to give students the experience they need. We're giving it to them now, when it matters most.

-Janani

Submission Deadline: March 13, 2026

What: ISTE+ASCD's AI Innovator Challenge invites students to design AI-powered solutions that solve real problems in their communities. Teams work through a structured curriculum to build AI literacy while creating projects that demonstrate innovation, creativity, and positive impact.

Who: K-12 students worldwide working individually or in teams. Open to classrooms, clubs, and independent projects.

Format: The challenge provides 15 free lesson plans through the AI Innovator Studio, covering everything from AI fundamentals to prototyping and pitching. Students receive support through webinars and resources as they develop their projects. Winners present at ISTELive 26 on the global stage.

Prizes:

What Makes It Special: Unlike typical competitions, this challenge provides comprehensive learning materials and ongoing support throughout the process. Students don't just build an AI project—they develop a complete understanding of how to use AI as a tool for positive change while earning recognition on an international stage.

Perfect for: Students who want hands-on AI experience with structured guidance, or anyone ready to tackle community problems with technology. No prior AI experience required—the curriculum is designed to build skills from the ground up.

The World Economic Forum's Youth Pulse 2026 surveyed nearly 4,600 young people across 100+ countries. Their message? Youth aren't asking for a seat at the table out of entitlement—they're demanding it because they have unique insights adults can't see.

With over half the global population under 30, young people represent the largest, most AI-literate generation in history. Yet they're also the least supported. They face a brutal contradiction: 57% identify employment as their top priority, but 70% remain stuck in informal or low-wage work. Two-thirds fear AI will eliminate their entry-level opportunities within three years.

But here's what makes this generation different: they're not waiting for permission. Youth-led climate projects are already delivering results at scale across 120+ initiatives globally. Students are building businesses, launching apps, and creating solutions to problems only they can see because they're living them.

The survey reveals that young people don't trust education systems to prepare them for work—46% see education as critical, but they're demanding practical, modular learning with direct pathways into real careers. They want skills that work now, not theories that might matter later.

World leaders gathering at Davos should pay attention. The question isn't whether young people are ready to contribute—they already are. The question is whether those in power are ready to listen and provide the tools youth need to turn their insights into impact.

Read the full World Economic Forum article

Moltbook went viral last week as a "social network for AI agents." Its creator proudly announced he "didn't write a single line of code", AI built the entire platform. Within 3 minutes of looking at the site, security researchers at Wiz found a catastrophic flaw: 1.5 million API keys, 35,000 email addresses, and thousands of private messages completely exposed.

The problem wasn't sophisticated hacking, it was a missing checkbox. The platform used Supabase but failed to enable Row Level Security, a basic protection that prevents unauthorized database access. Anyone who opened their browser's developer console could see the API key in the JavaScript and gain full read-write access to everything.

This is the dark side of "vibe coding", using AI to rapidly build applications without understanding what's actually being created. Speed became the selling point while security was an afterthought. The exposed data included OpenAI API keys shared in "private" messages, meaning one platform's misconfiguration leaked credentials for entirely different services.

For students learning to code with AI tools, this incident reveals a crucial truth: AI can help you build faster, but it can't think about security for you. Knowing how to clone a repo isn't enough, you need to understand what makes code secure, where credentials should live, and why certain configurations matter.

The researchers who discovered this flaw weren't experts with advanced tools. They simply knew what to look for because they understood the fundamentals. As AI lowers the barrier to building software, the gap between those who understand security basics and those who don't will only widen. The students who learn the right way from the start, who know why you don't hardcode API keys, why authentication matters, and how to configure databases properly—won't just avoid these mistakes. They'll be the ones who can actually build products people can trust.

Read the Wiz Security analysis

Learning GitHub: The professional skill most engineers learn on the job

This week, our students learned version control with GitHub, a fundamental skill that software engineers typically don't encounter until their first job, yet it's essential for any serious coding work.

Using GitHub Desktop, students learned to clone repositories, make changes to code, and commit their work. These aren't just technical steps—they're the foundation of how professional developers collaborate, track changes, and build upon each other's work.

What makes this particularly valuable? Most coding courses skip version control entirely, leaving students to figure it out later when stakes are higher. By learning GitHub now, our students can expand what they build beyond single-file projects. They can work with existing codebases, contribute to open-source projects, and showcase their work in ways that matter for internships and college applications.

The best part? Once you understand Git workflows, you unlock access to millions of projects on GitHub, and can use multiple AI tools without being limited. Students can clone any public repository, experiment with real-world code, and learn by studying how experienced developers structure their applications.

This is the kind of practical skill that separates students who've only completed tutorials from those ready to build actual software. It's not glamorous, but it's exactly what you need when coding stops being an exercise and starts being real work.

Our February cohort is filling fast. Spend just one hour per weekend over 6 months learning to build actual AI applications—not just use tools, but create solutions to problems you care about. Earn 3 college credits from University of Colorado Denver while developing skills that separate you from the AI anxiety everyone else is feeling.

Classes start this Saturday February 7!

Enroll now with code NEWYEAR50 →

Follow our LinkedIn page for free Q&A sessions where you can ask anything about our program, how you can earn credits, typical lessons students learn and really anything you have in mind before enrolling! Our next session is this Thursday, February 6 at 5pm PST/8pm ET.

Register for Thursday's Q&A →

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