Chasing Hype
I get it. The pace of this field is genuinely remarkable. Something significant happens almost every week. A new model, a new capability, a new framework, a viral demo. And there’s real social pressure layered on top: if you’re not current, you’re behind. If you’re behind, you’re irrelevant. So people run. They read every release. They watch every demo. They try every major new tool within days of launch.
I fall into this trap more than I’d like to admit. And I can tell you from experience: it doesn’t compound. You end up with a wide, shallow familiarity with a lot of things, but you don’t build depth in anything. And depth is what actually creates value. Depth is what lets you serve someone at a level that matters. Wide and shallow gets you invited to conversations. Deep and focused gets you paid.
The reason the rat race is so hard to escape isn’t weakness of character. It’s the absence of a philosophy that has genuine longevity. If you have a clear sense of where you’re going, a clear understanding of what you’re building toward and who you serve, then a new model release becomes a question with a clean answer: does this change anything material for my specific work? If yes, worth attention. If no, file it away and move on. But without that anchor, every new thing is equally urgent, because you have no framework for what matters to your particular mission.
The antidote isn’t ignorance. You don’t need to stop paying attention. You need a filter. Write down your mission, your thesis, your actual goals. Then every time something new drops, run it through the filter first. Most things will not pass. The ones that do will genuinely advance your work. That’s a much better ratio of attention-to-value than the alternative, and it leaves you with enough space to actually think.
Two images from a SXSW panel in March 2026 stuck with me. The first was a meme someone referenced: a bar of soap with a raw pump glued on top of it, captioned “businesses randomly adding AI.” The image is perfect. Adding AI to a business without understanding where it actually helps is like gluing a pump onto a bar of soap. It looks modern. It adds complexity. It does not improve anything. The underlying business problem has to be identified first, and if the problem does not exist, the solution is not AI. The second image was a metaphor from one of the panelists: Michael Jordan on the baseball field is not the same as Michael Jordan on the basketball court. You do not have to be good at everything. The hype cycle pressures people into thinking they need to master every new tool, every new framework, every new model. That is a recipe for mediocrity across the board instead of excellence in one lane. Find what you are genuinely good at, build teams around the gaps, and let the hype pass through your filter instead of setting your agenda.
Key Takeaway
Staying current on every AI development is a distraction without a long-term philosophy to filter what actually matters to your specific mission.