There's a specific kind of frustration that comes from knowing something is important and not knowing how to touch it.
For the past two years I'd watched AI go from "interesting trend" to "fundamental shift in how work gets done." I was advising organizations on digital transformation. I was in rooms where AI strategy was being set. And yet every time the conversation turned technical — every time someone asked "what does this actually look like in practice?" — I was one step removed from a confident answer.
I talked about AI. I didn't build with it.
The Decision
Vanderbilt's Generative AI Software Engineering Specialization on Coursera was on my radar for a while before I enrolled. What pushed me over the edge wasn't the curriculum — it was the word engineering in the title.
I'd done strategy courses. I'd read frameworks. What I hadn't done was sit down with a blank repo and try to ship something real using AI tools. The Vanderbilt program was explicitly about building: writing code, using AI assistants, understanding how these tools actually work under the hood.
My goal wasn't to become a full-stack engineer. My goal was to never again be the person in the room who can only speak to AI from 30,000 feet.
What I Expected vs. What Happened
I expected it to be hard. I expected to spend a lot of time stuck on syntax errors and configuration issues, frustrated at tools that assumed I already knew things I didn't.
Some of that happened. But something else happened too: I discovered Claude Code.
The course introduced me to AI-assisted development as a workflow — not just "use ChatGPT to explain code" but an actual paired-programming approach where the AI is in the loop at every step. Scaffolding, debugging, explaining decisions as it made them.
That changed the shape of what was possible for me.
The Shift
The frustration I described at the start — knowing something matters but not being able to touch it — that started to dissolve in the first few weeks of the course.
Not because AI made everything easy. It didn't. There were still moments of genuine confusion, still walls I had to work through. But the walls were lower, and more importantly, I could see over them.
I enrolled to understand AI better. What I got was a hands-on proof that the gap between "person who talks about AI" and "person who builds with AI" is smaller than I thought — and crossable with the right tools and enough stubbornness.
The first project was an expense tracker. That's the next entry.
This is entry 1 in my build-in-public journal. I'm documenting the journey from Digital Transformation practitioner to AI-fluent builder — one project at a time.