I started building websites in 1996.

Back then, getting information online required tools with names like HotDog and HoTMetaL. Those gave way to Dreamweaver, then WordPress, and eventually platforms like Wix that bring website design, hosting, e-commerce, and marketing together in ways we couldn't have imagined when we were writing HTML nearly 30 years ago.

I've watched the same transformation happen across almost everything I do.

Desktop publishing evolved from PageMaker and QuarkXPress to increasingly accessible platforms like Canva. Professional photography went digital. Cell phones became cameras. Cameras became computers. And now artificial intelligence can enhance an image, remove unwanted elements, generate backgrounds, and alter what we're able to create from the original photograph.

The tools have constantly changed.

I've learned that the answer isn't to abandon everything you know every time something new arrives. It's to take the experience you've accumulated and combine it with the best of what's available today.

That's essentially how I've built my workflow.

I still use professional tools I've relied on for years, but I'm constantly experimenting with what's next. Adobe Creative Cloud remains part of my workflow. So do newer platforms for graphics, websites, photography, video, and social media.

And now there's AI.

AI avatars. Digital twins. AI-generated voices. Image generation. Video generation. Writing assistance. Automated editing. The list seems to grow almost daily.

It's exciting, but there's another side to this technological revolution that doesn't get discussed nearly as much.

Keeping up with technology is becoming expensive.

There is rarely one application that does everything you need. Instead, you build a technology stack.

You subscribe to one application for professional editing, another for stock photography and video, another for graphics, another for AI voices, another for avatars, another for digital twins, and perhaps several more for the specialized tasks that make up your particular workflow.

Then comes the newest wrinkle: credits.

AI companies have tremendous computing costs. Generating an AI video or avatar isn't the same as opening a traditional piece of software on your computer. You're using someone else's servers and computing power, and increasingly you're paying for that usage through credits.

That means I'm constantly experimenting not only with what works best, but with what makes financial sense.

Maybe an AI avatar platform is the right tool for one project. For another, a digital twin created through a different application might produce what I need without burning through expensive credits.

Knowing the difference becomes part of the skill.

That's something I think gets overlooked in all the discussion about AI replacing jobs. Having access to artificial intelligence isn't the same as knowing how to use it effectively.

You still have to learn.

You still have to experiment.

You still have to make decisions.

And increasingly, you have to understand the economics.

For years, I personally absorbed many of these technology costs while producing work for companies. Eventually, I established my own business, which allowed me to treat these tools for what they really are: investments required to do the work I do.

That changed my thinking.

I no longer ask only, "What can this technology do?"

I ask:

Does it make my work better?

Does it make me faster?

Does it allow me to create something I couldn't reasonably create before?

And is the return worth what I'm spending?

Interestingly, Wall Street is beginning to ask many of the same questions about the AI industry itself.

The excitement surrounding artificial intelligence is enormous, but eventually companies have to demonstrate that their technology can generate sustainable returns. The AI companies that attract investment over the long term may not simply be those with the most impressive technology. They'll need business models that make economic sense.

As users, we're going through our own version of that process.

We're experimenting.

We're subscribing.

We're canceling.

We're comparing.

We're figuring out which technologies deserve a permanent place in our stack and which ones are simply interesting experiments.

And I think that's where experience still matters.

After nearly 30 years of digital work, I've seen enough revolutionary technologies come and go to understand that today's essential tool can become tomorrow's forgotten software.

The challenge isn't predicting exactly which applications will still be here five or ten years from now.

The challenge is staying curious enough to keep learning.

At 65, that's exactly what I intend to do.

As long as I have my wits about me and I'm physically capable, I'll continue experimenting with these systems and learning how they work. I'll keep figuring out which technologies help me communicate better, create better content, work more efficiently, and deliver greater value to the companies I work with.

I started doing this in 1996 because I was fascinated by what technology made possible.

Nearly 30 years later, I still am.

The technology is dramatically different.

The curiosity that keeps me learning it isn't.