Why I’m Glad I Never Learned Flash—and How That Shapes What I Choose to Learn About AI

Back in the early 2000s, everyone told me I should learn Flash. It was the thing—the language of slick websites, cool animations, and interactive experiences. I thought about it, but something held me back. Eventually, Flash disappeared, swept away by HTML5, mobile devices, and changing tech standards. And I’ve never regretted not sinking hours (or years) into mastering it.

That lesson has stuck with me: not every technology is worth learning. The tricky part is figuring out which ones are.

Fast-forward to today, and the same question hovers over artificial intelligence. AI feels massive, like the internet did in the ‘90s—too big to ignore. But it’s also moving so fast that it’s easy to wonder: am I learning something that will still matter in two years? Or am I about to sink time into the next Flash?

How I Decide What to Learn in AI

Here’s the framework I’ve been using:

1. Focus on Foundations, Not Tools
   Tools come and go. Flash went. So did Vine. Even ChatGPT will evolve into something else. But the foundation of AI—how models are trained, how prompts shape outputs, how to evaluate trust and bias—those skills translate across platforms. I’d rather learn the concepts than the “hot” app of the moment.

2. Solve Problems I Already Have
   I don’t chase AI for AI’s sake. I ask: what’s something I’m already doing that feels repetitive, time-consuming, or expensive? That’s where I test AI first. If it helps, it sticks. If it doesn’t, I move on.

3. Look for Skills That Compound
   Some learning creates leverage across everything else I do. For me, that means prompt design, data literacy, and understanding how to evaluate outputs. These compound like learning Excel once did—you can apply them everywhere.

4. Keep the Experimental Mindset
   I don’t need to “bet everything” on a single tool. Instead, I run experiments: small, low-stakes tests that show me what’s useful. I treat AI learning less like a college degree and more like a running lab notebook.

The Big Difference from Flash

The difference between Flash and AI is scale. Flash was niche—powerful, but limited. AI isn’t going away. The question isn’t if you should learn it, but how you’ll decide what to learn first.

For me, the lesson is clear: don’t obsess over the shiny tools that might vanish. Invest in understanding the principles, and use them to solve real problems today. That way, even if a tool disappears tomorrow, the time I spent learning won’t.