This is another good title for this post…
Not About the Tools: A Year of Needs, Problems, and Meaningful Solutions
I keep a five-year daily journal. Every day gets just a sentence or two, but those short entries turn into a time machine. A few days ago, it reminded me that exactly a year ago, I gave a lightning talk to Improvers about how I was using AI tools to be a more productive developer and consultant.
Back then, I had one tool in my belt: ChatGPT.
And even with that, I was blown away.
I was copy-pasting code back and forth between my IDE and ChatGPT, getting unstuck on implementation details, and researching domain questions that I didn’t yet have the language for. It was clunky—manual, linear, slow by today’s standards—and still I thought, “If this alone is possible, what does this mean for the way I work?”
Fast forward twelve months.
Now I’m using a whole ecosystem of AI tools.
Not because they’re shiny. Not because they make for cool demos. And definitely not because I want to become the person with the biggest toolbox.
Each tool I’ve added had to earn its way in. Every single one solves a particular need:
- removing the friction that kept old projects stuck in the backlog,
- accelerating ideas that used to sit dormant for years,
- making tedious or logistical steps disappear,
- turning “I wish I had time for this” into “I can do this today.”
That’s been the most surprising part of this year: projects I shelved for years because they were too time-consuming, too dull, or too logistically annoying suddenly became possible again. Week after week, I’ve been revisiting ideas I had long assumed were dead. Some of them shipped. Others are moving faster than I could have imagined. And a few I’ve pushed aside again—not because I can’t do them, but because I now have clarity that it’s still not their time.
What made the difference wasn’t the explosion of AI tools.
It was a matter of how I think.
I don’t look at tools as solutions in search of a problem. Instead, I lean into a simple playbook:
Need → Problem → Solution.
What’s the need?
What problem is getting in the way?
What solution could remove that friction?
A year ago, AI tools were evolving fast.
Today, they’re evolving even faster.
I still can’t predict what my toolset will look like twelve months from now. I can’t predict what new capabilities will show up, how they’ll reshape the way I work, or what new projects will suddenly become possible.
But I do know my anchor.
No matter how fast the tools move, I’m not hopping onto every fast-moving ship. I’m staying grounded in the same simple loop that has guided me through this year:
Need → Problem → Solution.
And that’s what has made the last twelve months so transformative.
Not the tools.
But the clarity they help bring to mind.
As technology accelerates, the most important thing is knowing what you actually need and what’s finally possible because of it.
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