What six months of curiosity, AI, and a willingness to try something new have taught me.
If you had told me six months ago that I would be writing code, building interactive dashboards, and troubleshooting Google Apps Script, I probably would have laughed. Then, when no one was looking, I would have quietly looked up what Google Apps Script actually was.
I'm not a software developer. I'm an educator and leader who loves helping people grow, trying new approaches, and making a meaningful impact. I've also never been particularly good at leaving something alone once I start wondering whether there's a better way.
That curiosity typically leads to a productive conversation. This time, it also led to several thousand lines of code.
We were spending valuable time creating weekly communications. The information mattered, yet finding updates later was difficult, and keeping everything organized took more effort than it should have.
I wondered what it would look like if leaders could find what they needed without digging through old communications. I could picture it. I just had absolutely no idea how to build it.
So I started talking to AI. No sophisticated prompt or technical plan, just something along the lines of, "Here's what I'm trying to do. Is this even possible?"
One question led to another, followed by a little code, a test, a quick visit to our IT department to make sure I wasn't about to break anything important, and more conversations with AI. With feedback from colleagues and plenty of trial and error, that idea became a searchable communication hub that made information easier to find and saved hours of repetitive work.
I was thrilled. And perhaps a little dangerous, because suddenly every spreadsheet and process looked like something that might need attention.
Our eLearning team had been collecting valuable course feedback for more than a year. We had the data. What we didn't have was an easy way to use it to make decisions. Which courses were making the greatest impact? Where were learners finding value? Which needed revisions? What should we develop next?
Those questions led to another conversation with AI and eventually an eLearning Course Insights dashboard. Now we can see what's working, where courses might need attention, and what the feedback tells us about future development. From there, we started looking at how AI might help with action planning, continuous improvement, and information scattered across multiple systems.
What surprised me most wasn't that AI could help write code or build dashboards. It was how much I learned through the conversations. I'd describe what I was trying to accomplish, question a suggestion, explain why something wasn't quite right, and keep working through it. Sometimes AI helped me see an option I hadn't considered. Other times, I realized I needed to rethink the question I was asking.
I wasn't simply getting answers. I was learning through the process.
I wish I could say it was as simple as describing an idea to AI and watching a finished solution appear. It hasn't been quite that easy.
There have been errors. Lots of errors. Something might work beautifully one day, only for me to wake up with new ideas for making it better. I've asked AI to fix one small thing, only to discover something else had stopped working. There have definitely been moments when I wondered whether I was saving time or creating an entirely new hobby.
I've also learned that AI can be very convincing, even when it's wrong. Sometimes I have to push back, explain what's missing, or remind it what we're actually trying to accomplish. And sometimes I have to stop myself and ask whether the latest idea would make anything better for the person using it.
Just because something can be built doesn't mean it should be.
One unexpected part of this experience has been getting comfortable being a beginner again. That's not always easy when you're accustomed to leading, making decisions, and helping others navigate challenges.
Sometimes I don't understand the code or why something isn't working. My most useful contribution might simply be explaining what the experience should be for the person using the tool.
What I've discovered is that I don't have to know how to do everything to begin figuring out how to make something better. And neither do you.
AI can suggest solutions and help work through problems. What it can't do on its own is understand our people, our priorities, or why a particular outcome matters. I have to bring that context, recognize when a suggestion misses the mark, and decide what is actually worth pursuing.
Some of my most valuable conversations with AI haven't involved code at all. They have helped me sort through questions I probably should have been asking from the beginning. What does someone actually need to know? What decision are they trying to make? Are we measuring something because it matters, or simply because we can?
I have found myself carrying those questions into other parts of my work, too. And I think they've made me a better leader.
I am sharing this story not because I think everyone should start building dashboards or learning Google Apps Script. Please don't. I suspect we already have enough dashboards competing for space in our bookmarks.
What I hope is that someone reading this recognizes an idea they've been putting aside, perhaps because they've thought, "I wouldn't even know where to start."
I know that feeling. And I've learned that the first step can simply be a conversation.
Here's my challenge to you: Think of something you've been wanting to improve, create, or better understand.
It doesn't have to be a big idea. Just something you've been thinking about and haven't quite figured out how to approach.
Pick one. Open an AI tool and start a conversation. You might try:
"I'm trying to [describe what you want to improve, create, or understand]. Here's what I've been doing or thinking so far: [share a little context]. I'm not sure where to start. Can you help me explore a few possibilities, ask questions to clarify my thinking, and suggest one simple step I could try?"
Describe your idea in everyday language, keeping confidential information private. No detailed technical explanation or spreadsheet required.
Then see where the conversation goes. Question suggestions that don't seem quite right. Ask AI to explain something differently. Try a small idea and see what happens. You may end up with a solution, a better question, or a completely different way of looking at the problem.
And remember, you're still the one making the decisions. You know the people involved, what you're trying to accomplish, and whether a suggestion would actually help. AI gives you someone to work through the thinking with.
Six months ago, I didn't set out to learn code. I set out to solve a problem.
I'm still solving problems, still learning, and occasionally staring at my screen wondering what on earth I just broke. Something has changed, though. Instead of assuming an idea is beyond my technical ability, I'm more likely to ask, "I wonder if we could..."
That doesn't mean every idea works out. It just means I'm more willing to find out.
Now it's your turn. What's one idea, challenge, or possibility you've been putting aside because you're not quite sure where to begin?
Give yourself permission to explore it. Start a conversation with AI and see where it takes you. If you discover something useful, I'd love to hear about it.
Fair warning, though. One good idea has a funny way of turning into a dozen more.