AI is supposed to make things easier.

This time...it didn't.

It started with an idea for Jim's office. He has regular pegboard covering the walls, and we wanted custom wooden organizers that could attach to it.

The plan sounded simple enough: 3D print the clips, laser cut the wooden boxes, and use AI to help create the SVG files.

Except AI kept getting it wrong.

Measurements were off. Pieces didn't fit. Corrections created new problems. Maurie argued with AI, typed in ALL CAPS, threatened to switch to Claude, actually switched to Claude...and eventually came back with a completely different way of approaching the problem.

Instead of continuing to explain what was wrong, she started showing it.

She marked the physical pieces, drew corrections, took pictures, isolated individual problems and kept testing.

Eventually, it worked.

In this episode of Beyond Yet, Maurie and Jim talk about AI, 3D printing, laser cutting, prototyping, frustration, critical thinking and why using AI doesn't mean handing over the thinking.

Sometimes the most valuable thing AI does isn't getting the answer right.

It's helping you get far enough to figure out what you need to do next.

If you can think it, you can create it.

What is your next yet?

What happens when you need something that doesn't exist?

You could keep shopping. You could compromise. You could settle.

Or... you could draw it.

In this episode of Beyond Yet, Maurie needed an organizer made for one very specific space and one very specific collection of makeup. After searching for something that would work, she finally grabbed a piece of paper, drew exactly what she wanted, added measurements, took a picture, and gave it to AI.

The result was an STL file she could send to a 3D printer.

It wasn't perfect. The first version was too tall. The next version got finger notches. There are already ideas for version three.

And that's where this story gets much bigger than a makeup organizer.

Maurie and Jim talk about AI, CAD, 3D printing, prototyping, learning, ZPD, and something they've seen repeatedly with students: sometimes being able to see what's possible first creates the motivation to go back and learn the skills underneath it.

AI doesn't have to replace learning. It can change where learning begins.

And sometimes it means you don't have to settle for the closest thing someone else decided to mass produce.

If you can think it, you can create it.

What is your next yet?

We had 206 panic buttons, a Velcro problem, some very determined adhesive…and absolutely no desire to relearn CAD.

What started as a pretty mundane problem at our school district turned into a perfect example of why we created Beyond Yet.

We needed a permanent holder for a panic button. We couldn't find one to buy. We knew a 3D printer could probably make one.

We just didn't know how to design it.

So Jim asked a question:

What if AI could do the part we didn't know how to do?

It could.

In this episode, we tell the whole story, including the bad tape, painted-over Velcro, our first prototype, the STL file AI generated, what we got wrong, what we learned about manufacturing time, and the little 3D-printed holder that is now changing how we're thinking about what we can create.

Because the interesting part isn't the panic button holder.

It's what happened afterward.

Once you've made something you previously couldn't make, you start looking around and wondering:

What else could I do that I don't know how to do…yet?

That's Beyond Yet.

If you can think it, you can create it.

After four years of talking about artificial intelligence, we're changing the conversation. Beyond Yet isn't about AI news, prompt lists, or another collection of how-to tutorials. It's about what happens when something you've always wanted to learn, build, try, or create suddenly isn't as far out of reach as you thought.

Maurie and Jim introduce Beyond Yet, explain why they're making the change, get distracted by a moth, argue about pre-boiled eggs, and ask the question that may define the whole show: What do you want to get your PhD in?

Artificial intelligence needs data centers, but what happens when one wants to build in your community?

In this final episode of our three-part series, Maurie and Jim Beasley shift the conversation from fear to preparation. Instead of asking whether data centers should come to town, they explore how communities can negotiate smarter agreements that protect residents while creating long-term benefits.

They discuss:

• Why your town has more leverage than you think
• Protecting water before construction begins
• Infrastructure improvements that should stay with the community
• Roads, utilities, emergency services and broadband
• Heat reuse, workforce development and long-term planning
• Why a handshake isn't enough

If a company wants something your community has, make sure your community receives something valuable in return.

The goal isn't to stop progress.

It's to make sure progress works for everyone.

AI in Action is hosted by Maurie and Jim Beasley of AI Education Professionals.

#AI #DataCenters #ArtificialIntelligence #Infrastructure #CommunityPlanning #Texas #Technology #EconomicDevelopment #Water #Broadband

Part two of our three-part AI data center series explores the legal realities behind these massive projects.

From zoning laws and environmental regulations to power grids, water usage, developer lawsuits, and state authority, we explain why many communities struggle to stop projects once they begin—and what local leaders should understand before it's too late.

AI doesn't live in the cloud.

It lives in physical buildings that require enormous amounts of electricity, cooling, land, and infrastructure.

In Part 1 of this three-part series, Jim and Maurie Beasley explain what AI data centers are, why they're expanding so rapidly, who builds them, and why communities across America are beginning to face difficult decisions about bringing them into their neighborhoods.

If you've heard about billion-dollar AI projects but aren't sure what they actually mean, this episode provides the foundation you'll need before the conversation reaches your town.

AI data centers are expanding rapidly across America, and many rural communities aren't prepared for what comes next.

In the first episode of this special series, we share the story of our own community's successful fiber infrastructure project and explain why those lessons matter as cities begin negotiating with large technology companies.

This conversation sets the stage for upcoming episodes covering data centers, legal considerations, and practical strategies that can help communities negotiate from a position of knowledge rather than reaction.

Artificial intelligence doesn't live in the cloud... it lives in real buildings that require land, electricity, water, and infrastructure.

This week on AI in Action, Maurie and Jim explore one of the biggest conversations happening behind the scenes in AI... data centers.

Who benefits? Who bears the cost? What happens to rural communities when massive AI infrastructure moves in? Is there a better way to balance technological progress with local property rights, environmental stewardship, and community partnerships?

The discussion covers power grids, water usage, jobs, profit sharing, eminent domain, and why being a good neighbor may be just as important as building the next generation of AI.

Whether you live in a large city or a small town, the decisions being made today will shape the future of artificial intelligence for decades to come.

Are we watching history repeat itself?

Maurie and Jim explore the recent restrictions placed on advanced AI models and compare them to the famous Crypto Wars of the 1990s. From encryption battles to modern AI export controls, the same questions remain: How much control should governments have over emerging technologies, and what happens when innovation collides with national security?