Nye's Digital Lab is a weekly scribble on creativity at the intersection of AI & Distributed Networks.

This week I'm thinking about making more projects, and using them to teach building things that matter.

My grandmother was a prolific knitter. She made all sorts of things for her four children and then all of her many grand kids.

When people asked her how to start knitting, she never said "make a practice square" or "start with a scarf." Instead, she'd tell them to pick what they actually wanted to make. You want to make a sweater for your boyfriend? Then, knit a sweater.

The desire to create something specific, something needed, would teach them far better than any abstract exercise. She understood that purpose is the best teacher we could have.

I think artificial intelligence will transform how we work and learn. The careful curriculum sequences we've built in education may remain valuable, but they're being supplemented by a practical approach. When AI can generate code and solve equations in seconds, we will likely need to embrace additional ways to engage learners.

My grandmother's knitting points toward an answer:

the drive to make something that matters,

for people who matter to you,

creates a unique form of learning.

Traditional education has relied on a structured approach. Arithmetic before calculus, grammar before essays. These foundations have mattered for a long time.

But there's always been another "thread" running through human learning. It's the project that pulls you forward. I have students who learned programming to mod their favorite game, or friends who mastered woodworking to build their child a tree-house. The project becomes the teacher, and the skills support the project.

Apprenticeships worked this way for centuries. The Bauhaus movement understood it. Silicon Valley garage startups embody it when college dropouts build companies. The motivation of a real outcome has always been a powerful educational force.

What's changing is that AI makes this approach essential.

When technical skills can be augmented or automated, what remains distinctly human is the ability to identify what needs building and why. My grandmother didn't just teach knitting techniques;

she taught people to see a grandchild who needed warm booties and feel compelled to provide them.

I think that recognition of what is needed can't be programmed.

The passion behind purpose-driven learning creates resilience that skill-building alone rarely achieves. When you're learning abstract skills, every obstacle feels like evidence you're "not cut out for this." But if you're building something you care about, obstacles become puzzles to solve.

The motivation is intrinsic and sustainable because the outcome matters to you personally.

Real projects have different DNA than educational exercises.

Here are a few that I believe are critical.

Time

Start with time pressure, not arbitrary deadlines. I love game jams and hackathons because they showcase this perfectly: 48 hours to build something functional. This pressure forces you past perfectionism into creation. You learn what you need, when you need it, with the urgency of someone who has something to deliver.

Team

You need diverse skills to build projects. Someone who understands users, someone who can build, someone who keeps everyone on track, someone who remembers to order pizza during late-night work sessions! These aren't assigned roles but genuine needs that emerge organically. Working together on something real teaches the complex art of creation with others.

Rapid Prototype

Keep it rough! It's all throw away! The prototype mindset is best for projects with purpose. Instead of aiming for perfection, you build something quick to test your assumptions. This iterative approach mirrors how creation actually works in the world. Each failure teaches something specific and immediately applicable to the next iteration.

Communication

When building with others, you must explain ideas, negotiate between visions, and sometimes admit you were wrong. (Not me of course, but everyone else. ) You develop what the pedagogy experts call emotional or soft skills, but they're really the hard skills of making things happen with other humans. No AI can replicate the ability to inspire a team through a difficult debugging session or mediate between competing design philosophies.

Ship

What makes project-based learning memorable is the satisfaction of completion. Pointing to something and saying "we made that" creates a sense of pride. The thing exists in the world and people can use it, experience it, benefit from it. This tangible outcome validates the struggle in ways that abstract assessment never could.

Finally, here's the big one. I believe the transformation deepens when projects connect to genuine community need.

This isn't about adding a service component to traditional learning but recognizing that the most powerful education happens when you're building something your community actually requires. Purpose-driven projects ask...

not "what skills should we practice?"

but "what does our neighborhood need?"

When a community garden needs irrigation, the learning becomes engineering and ecology. The curriculum emerges from real needs rather than abstract standards. This doesn't replace foundational learning but it provides a compelling context for why those foundations matter.

This approach directly addresses what AI changes about work and learning.

If machines handle technical execution, what's left for humans isn't just creativity but caring. It's the ability to see what matters to specific people in specific places. AI might write code efficiently, but it takes humans to recognize that non-English speaking families need better translation services at the local clinic, or that youth programs need safe spaces to gather.

My hope is that purpose will create natural resilience against automation anxiety.

When your focus is serving community needs, AI becomes a powerful tool rather than a threat. The value isn't in performing technical tasks but in understanding context, building relationships, and navigating the social dynamics around meaningful change. These are human territories.

I suspect that the projects that will matter in an AI-enhanced future are those that require deep local knowledge and genuine connection. They're about seeing patterns in your community that no algorithm could detect because they require lived experience to recognize. They're about building trust with people who need help but might be suspicious of institutions.

They're about translating between technical possibilities and human needs.

Classroom education plus Purpose Driven Projects. The future likely holds both approaches working together. As AI accelerates, so too, do the projects.

Students will still need foundational knowledge, but they'll increasingly apply it through projects that matter to their communities. The classroom becomes one node in a network that might include things like maker-spaces, community centers, and anywhere that purposeful creation can happen. Time pressure from real needs, collaboration with diverse teams, and iteration based on actual use become core educational experiences.

Educational institutions don't need to abandon what works but rather expand their vision. Traditional teaching provides the foundation; projects with purpose provide the application and motivation.

My grandmother passed down more than knitting techniques. She taught that making things for people you care about is both the means and the end of real learning. When machines can knit perfect scarves, the question isn't whether humans should still learn to knit.

It's whether we're knitting something someone actually needs, with people we want to work alongside, for a community we're part of.

The projects that matter will be those that emerge from genuine need, built through real collaboration, creating something that couldn't exist without human recognition of what communities require.

That's not just education or even work. That's the human contribution that can not be replaced.

Thanks for reading. I do this every week. If you vibe to the ideas I express, please consider subscribing or sharing with friends. We'll see you next time.

Nye Warburton is an educator from Savannah, Georgia, who growing up, seemingly got sweaters every year from his grandmother. This essay was crafted through improvisational sessions using Otter.ai, it was edited and refined using Claude Sonnet 4.0 and old-fashioned human labor.

For more information visit: https://nyewarburton.com

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