Last December, I was doing a live demo for a college senior named Jacob and his dad.
Jacob had one semester left. He was interning at a home builder in the area. And his dad had specifically reached out to me because of something the company told Jacob: if you can help us with AI implementation, you jump to the top of the candidate list.
Not a software company. Not a startup. A home builder.
That conversation stuck with me because I hear versions of it constantly now. The job market is shifting in real time, and most people are still treating AI as optional.
It's not optional anymore.
What the Home Builder Story Actually Shows
Jacob's situation is interesting because it flips the usual narrative. We talk a lot about AI taking jobs. But here's a company in a physical, blue-collar-adjacent industry actively rewarding the employee who can bring AI skills.
Why? Because the home builder had real problems, AI could solve. Proposal tracking. Project status reports. Communication between site teams and office staff. These aren't exotic problems. They're just problems no one had the time to fix.
Jacob's dad made a decision I respect. He didn't want to hire someone to build AI tools for Jacob's employer. He wanted Jacob to learn how to build them himself.
His exact reasoning: “If he learns this, he can be valuable to people.”
That's the right call. And it's something I've been saying in my workshops for two years.
The Difference Between Using AI and Building with AI
There are three levels of how people work with AI. I call them the AI Fluency Levels.
The first level is AI Assisted – you're having conversations with ChatGPT, getting writing help, maybe using it for research. Good start. Most people are here or haven't started at all.
The second level is AI Workflows – you've connected tools together. Emails go to a folder, get summarized by AI, and you review a digest. You've automated something.
The third level is Building Agents – you've created something that runs without you. A system that handles a specific task end-to-end while you focus on something else.
Jacob's employer isn't looking for someone who can chat with GPT-4. They want someone who can get to level two or three. Someone who can look at a 15-page project status report and say: I can build an agent that converts this to a one-page visual every Friday.
That's what creates real value. And that's what moves you to the top of the list.
I've Seen This Story More Than Once
Around the same time I was working with Jacob, I was coaching another student. He'd been trying to get hired at a construction company for six months. No luck.
After five weeks of working with me… about an hour a week… he built a web app from scratch. He went to the job site, asked the workers what slowed them down, and built a project tracking tool that calculated whether timelines were on schedule.
When he reapplied with the app in hand, management reconsidered him.
Not because he had more experience. Because he showed up with a solution to their actual problem.
That's the shift happening right now.
Why Most People Miss This Window
Here's the thing that frustrates me.
If you're on Twitter or LinkedIn, you think everyone is building AI agents and the window is closing. But I talk to actual business owners every week. Small companies, service businesses, construction firms, clinics. Most of their staff barely knows how to write a prompt. The average employee is nowhere close to building an agent.
The window is still wide open.
I ran my first AI workshop in Austin in early 2025. Sold out immediately. My second one: five repeat attendees from the first workshop, just trying to stay current. The hunger for practical AI skills is real, and the supply of people who can actually teach it in a hands-on way… not seminars, not YouTube videos, but real hands-on workshops… is still tiny.
What to Actually Do
If you're early-career or trying to differentiate yourself, here's the simplest frame.
Start with one thing. Not five tools, not an entire automation stack. One problem at work that eats 30 minutes a week. Build something small that solves it. Document before and after.
That single project is now something you can put in front of an employer.
The One Tweak a Week approach works here. Add one more AI capability to your toolkit each week. In three months, you've built 12 small things. Some won't work. Some will. The ones that work become your portfolio.
Jacob's dad was right. Learning to build is different from having it built for you. The skill compounds. Every project teaches you something the next one needs.
Home builders are asking for this. Construction companies are asking for this. Clinics, real estate firms, law offices – they all have the same problems. And they're all starting to notice who walks in the door with real solutions.
That person doesn't have to be a programmer. They just have to be curious enough to start.
Thanh Pham runs AI workshops in Austin and works with companies across industries to implement practical AI systems. If you want to learn hands-on AI skills for your career or business, check out the Productivity Academy or reach out directly.
