How I Learned to Stop Worrying and Love AI

This morning I felt a slight tightening in my chest. Coincidentally, it was about right after I saw the announcement of Mythos's release and if I’m being honest, it wasn't even about all of the software potentially being hacked by this supreme being of a model. It's just KNOWING that there will be five more models to take for a spin in the next couple of weeks and SO MANY posts announcing it like this is something new.

For the past couple of years, being in tech has felt less like a stable job that pays your mortgage and more like running a sprint on a treadmill that someone keeps speeding up. New releases, public announcements, six-month exit cycles. Freaking madhouse. Nowadays I find myself checking tech news the way I check the weather in the summer: “Oh it’s 38°C? Just another sweaty day in hell I guess,” I say to myself, shrugging it off, like it’s just normal to live like this.

The Oatmeal Forecast

The discourse itself doesn’t help. Acknowledging the speed does little to ease the fatigue, mostly because we are constantly sold two extreme, binary futures.

Option A is a sci-fi utopia where nobody works and we all paint landscapes while the machines handle the planet. I want to, but I know I don’t buy it. Option B is the one that causes the dread but feels more aligned with my view of the world: we become completely redundant, sitting in a grey cubicle, living off a tiny UBI check and eating cold oatmeal.

And as I spend many of my days building infrastructure and deploying solutions that make others quietly less employable, this isn’t an abstract philosophical question. It makes me wonder if what I’m doing right now will even be a viable profession in five years.

The Relief of Exhaustion

But lately, something shifted. I reached a state of acceptance.

It didn’t come from some sudden burst of optimism or a corporate keynote about "human-AI partnership." It came from pure, pragmatic exhaustion. You can only stare at an exponential curve for so long before your eyes glaze over and you have to go back to work.

The turning point was looking closely at the actual reality of implementation. Strip away the marketing hype and the doomsday tweets, and you find that enterprise tech is still incredibly messy. The data is still dirty. The infrastructure is still fragile. These models are powerful, but they are not magic. They require hard, grounded engineering to actually do anything useful.

Riding the Curve

Acceptance means realizing that outrunning the velocity is impossible. I can’t predict where we will be in five years, and honestly, neither can the people building the models.

So I stopped worrying about the cold oatmeal. The bomb is already mid-flight. Instead of panicking about the destination, I’m focusing on the engineering problems right in front of me today.

True acceptance comes from understanding a basic truth: for as long as human thinking is relevant, having a good, functioning reasoning brain means I will be fine. If the world changes completely, we will adapt then.

For now, there is work to do.