The Technology Changed. The Need to Keep Learning Didn't.
In Part 1, I talked about starting my career as a carpenter building houses in the Washington, D.C. area while going to school and trying to find my way into technology.
Eventually, I got my opportunity as a Web Developer during the dot-com boom and Y2K era.
That was more than 27 years ago.
A lot has changed since then.
I've watched technologies that were once considered cutting-edge become obsolete. I've watched development languages and frameworks come and go. I've watched infrastructure move from physical servers to virtualization and the cloud. I've watched software evolve into SaaS platforms, mobile become part of everyday life, automation change business processes, and now artificial intelligence begin changing how we work again.
Every one of those changes required learning something new.
And I'm still learning today.
I use AI regularly. I'm interested in what it can do, where it can improve productivity, and how it can change the way we develop products and solve business problems.
But experience has also taught me not to confuse new with better.
That's an important distinction.
After enough years in technology, you start recognizing patterns.
I've seen organizations automate bad processes instead of asking whether the process itself should exist.
I've seen teams repeatedly fix symptoms because nobody had the time, authority, or inclination to find the root cause.
I've seen technical shortcuts that saved a few days eventually cost months.
I've seen organizations choose technology first and then try to figure out what business problem it was supposed to solve.
The names of the technologies change, but many of the underlying problems don't.
That's where I believe experience becomes particularly valuable.
Experience doesn't mean walking into a room already knowing the answer.
If anything, experience has taught me to be more comfortable saying, "I don't know. Let's figure it out."
But it has also taught me which questions we should probably ask before we start looking for the answer.
What problem are we actually trying to solve?
Why are we doing this?
Who does it help?
Are we fixing the root cause or another symptom?
Are we making something better, or simply making it newer?
And increasingly today: Are we using AI because it genuinely improves the outcome, or because AI happens to be the technology everyone is talking about?
Those questions aren't anti-technology.
They're exactly the opposite.
Technology is incredibly powerful when we apply it to the right problems.
I've spent more than 27 years watching the tools change, and I expect they'll continue changing faster than ever.
I'm not an expert in every new programming language, platform, framework, or AI tool that appears.
I don't need to pretend that I am.
What I do need to do is remain curious enough to learn, experienced enough to ask questions, and humble enough to surround myself with people who know things I don't.
Because after all these years, one lesson has remained remarkably consistent:
The best technology professionals aren't the people who already know everything. They're the people who never stop learning.
In Part 3, I'll talk about another change that happened along the way.
At some point, my career became less about the things I could personally build and more about the people I could help build them.
Thanks,
Michael Cronin
Website: https://www.michaelcronin.info
LinkedIn: https://www.linkedin.com/in/michaeltcronin/details/experience/
