LeadershipFebruary 1, 20268 min read
I built this website in an afternoon. Not by hiring a developer. Not by learning to code over months of tutorials. I did it by having a conversation with Claude Code—an AI assistant that translated my vision into reality while I focused on what I actually wanted to communicate.
A year ago, this would have required a developer, a designer, and weeks of back-and-forth. Today, it required curiosity and a willingness to learn a new way of working.
This isn't a story about websites. It's about a fundamental shift in what's possible for non-technical leaders—and why getting invested in these tools now isn't optional.
The Widening Gap
Every week I talk to executives who fall into one of two camps.
The first group is experimenting. They're using AI to draft communications, analyze data, prototype ideas, and automate the tedious parts of their work. They're not experts—they're learners. But they're building an intuition for what's possible.
The second group is waiting. Waiting for IT to roll out an "approved" solution. Waiting for the technology to "mature." Waiting for someone to tell them it's safe.
Here's what the second group doesn't realize: the gap between these two camps is compounding daily. The executives who are experimenting aren't just saving time—they're developing a fundamentally different mental model of what's possible. They're asking different questions. Seeing different opportunities. Making different decisions.
By the time the "approved" solutions arrive, the first group will be operating on an entirely different level.
Why This Moment Is Different
We've been through technology shifts before. The internet. Mobile. Cloud. Social. Each one required executives to adapt. But this shift is different in a crucial way.
Previous technology waves required you to understand what the technology could do and then direct others to build it. You needed technical literacy, not technical capability.
AI tools like Claude Code collapse that gap. For the first time, non-technical leaders can directly create, prototype, and build—not by becoming programmers, but by becoming effective collaborators with AI systems.
The skill isn't coding. The skill is:
Clear communication: Knowing how to articulate what you want
Iterative thinking: Building in small steps, testing, and refining
Creative direction: Recognizing when output matches your vision
These are skills most executives already have. They just need to apply them in a new context.
What Getting Invested Actually Looks Like
I'm not suggesting every COO needs to build their own website. But I am suggesting that every executive needs hands-on experience with these tools. Not a demo. Not a presentation from a vendor. Actual, hands-on experience.
Here's why: you cannot evaluate opportunities you don't understand. You cannot ask the right questions about AI strategy if you've never felt the difference between a well-crafted prompt and a poor one. You cannot lead an organization through this transition if you're relying entirely on others to interpret what's possible.
Start Small, But Start
Pick something real but low-stakes:
Use Claude to analyze a quarterly report and surface insights you might have missed
Have an AI tool help you draft a difficult communication, then refine it together
Prototype a simple tool or workflow that would make your team more efficient
Build something tangible—even if it's just for yourself
The goal isn't to become technical. The goal is to develop intuition.
Embrace the Learning Curve
The first time you use these tools, you'll probably be underwhelmed. Your prompts will be vague. The outputs will be generic. You'll wonder what all the hype is about.
This is exactly what happened with previous technology shifts. Remember the first time you tried to find something on the early internet? Or sent your first email? The tools felt clunky and limited—until you developed fluency.
The executives who push through that initial friction are the ones who discover the real potential.
Build Organizational Muscle
Once you've developed personal fluency, the next step is building it across your organization. This doesn't mean mandating AI usage or rolling out enterprise tools. It means:
Creating psychological safety: for experimentation
Sharing learnings: from your own experiments
Celebrating creative applications: wherever they emerge
Asking better questions: about how AI could help with specific challenges
The organizations that will win aren't the ones with the best AI strategy decks. They're the ones where dozens of people are running small experiments, sharing what works, and building collective intelligence about how to leverage these tools.
The Cost of Waiting
Let me be direct about what's at stake.
In every previous technology transition, there was a reasonable window to wait and see. You could let early adopters work out the kinks, then fast-follow with mature solutions.
That window is closing faster than any previous transition. The capabilities of these tools are improving monthly, not yearly. The executives who are experimenting now are building advantages that will compound.
Worse, the cost of waiting isn't just falling behind—it's losing the ability to catch up. Once your competitors have developed AI-native workflows, AI-enhanced decision-making, and AI-accelerated execution, the gap becomes structural.
This Isn't About Technology
The deepest reason to get invested in AI tools isn't about technology at all. It's about leadership.
Your teams are watching how you respond to this shift. Are you curious or defensive? Engaged or delegating? Learning or waiting?
The executives who will thrive aren't the ones with the best technical understanding. They're the ones who model the mindset that will define the next decade: relentless curiosity, willingness to be a beginner, and the courage to engage with change rather than manage it from a distance.
The tools are ready. The question is whether you are.
Where to Start
If you've read this far and you're convinced but unsure where to begin, here's my suggestion:
Pick one thing you've been meaning to do but haven't had time for. Something that would normally require help from a technical team. Maybe it's building a simple dashboard, creating a prototype, drafting a proposal, or analyzing a complex dataset.
Then spend an hour with Claude Code or a similar tool trying to make progress on it. Don't worry about doing it "right." Just experiment.
You'll learn more about what's possible—and what you need to learn—in that hour than in any presentation or strategy session.
The AI revolution isn't coming. It's here. The only question is whether you'll be leading it or following it.