I gave up coffee because I started losing my sight. I was getting visual migraines, auras that would creep in until I stopped seeing out of one eye for several minutes. It was terrifying the first time, and not much better the tenth.
It turned out coffee wasn’t really the cause. The stress from a past job was. But I was only drinking a single cup a day, so quitting felt like the one thing I could actually control.
That single cup was harder to give up than I expected. The week I stopped was the hardest of my life. Nothing dramatic happened, nothing to point at, just a flat grey feeling that sat on everything. It felt like being depressed. Over one cup of coffee.
I ended up staying off it for almost four years.
Now I’m back, and I only drink pour over, V60 and batch, weighed and made properly like a real expat. Not out of caution, I just like it more this way. The auras are gone, the job is behind me, and the two minutes at the counter watching it bloom are the calmest part of my day.
I didn’t expect The Bear to make me uncomfortable.
Not because of the kitchen chaos or the screaming, and there’s plenty of both. Because of how much the characters care. Carmen beating himself over a dish. Richie discovering, after years of drifting, that he’s actually good at something when he finally commits. Every one of them giving more than they have, suffering for it, and doing it anyway.
Watching that made me aware of something I usually don’t look at directly: I don’t do that. I hold back.
At university, I did the bare minimum to get by. At work, I reach for the easiest path. I’ve told myself this is a kind of intelligence, as a way to simplify, automate, avoid unnecessary effort. And some of it is. But some of it is just avoidance dressed up as efficiency.
Not going all-in is a way to avoid completely failing. It’s also a way to avoid feeling fully realized.
I’m not sure I know how to fix that. But The Bear made it harder to pretend I hadn’t noticed.
I used to roll my eyes at people who started a new sport and immediately bought all the gear. Day one of running and they’re already showing up with top-of-the-line shoes, a smartwatch, wireless earbuds, and the most aerodynamic outfit money could buy. What a waste, I’d think. They haven’t even proven they like this yet.
I’ve changed my mind.
Buying the gear is a statement. Not to others, to yourself. It’s how some people say: I believe I can do this, and I’m going to.
That belief is the thing. The shoes are just a way of making it happening.
Most people don’t fail at new habits because they lack discipline. They fail because they never really believed they’d follow through. Buying the gear, keeping the journal, signing up for the race… these are ways of saying: I’m a runner now. Not someday. Now.
Act like what you want to be, and you start becoming it.
These days I’ve found myself reading about hardware shortage and how RAM, disk, and NAND manufacturers have all their production for 2026 already sold to AI/Data center companies.
It had me thinking about the strange position compute finds itself in right now.
GPUs weren’t designed for AI. They were designed for graphics as in pushing pixels, rendering triangles. It turned out that the math for doing that at scale overlaps just enough with neural network math. The entire current AI boom runs on repurposed hardware.
AI compute today looks like early computing in some ways (expensive, power-hungry, room-sized) but with a key difference: the general-purpose phase is already behind us. GPUs served that role for over a decade, but now the industry is moving fast toward specialized silicon: Google’s TPUs, Meta’s MTIA, Amazon’s Trainium, Microsoft’s Maia. Even OpenAI is building its own chips. Every hyperscaler has concluded that off-the-shelf isn’t good enough anymore.
And then there are bets and promises. Wafer-scale chips that fit an entire compute cluster on a single piece of silicon. Designs that try to mimic how brains actually work. Optical computing, replacing electrons with light. And the long promised quantum computing. These aren’t products yet, they’re hypotheses about what comes next.
The pattern in computing history is clear: when you hit a physical wall something different emerges. We’re hitting those walls now. Current GPU scaling is running into the limits of what silicon can physically do and we’re solving it by just throwing more hardware and building bigger computing centers. Vacuum tubes hit the same kind of wall. Too hot, too big, too power-hungry, and the answer wasn’t more tubes. It was the transistor, which made everything that followed possible.
Yet almost nobody is talking about it. The conversation is all AI and agents, as if the hardware underneath were a solved problem. It isn’t.
Currently I’m between jobs. Nothing special, a lot of people go between jobs.
After working for several years on a fast-paced startup, you might be tempted to jump back to your next role. You could feel it or not, but you’re likely tired, even close to burnout.
Taking a break between jobs is not just about resting. It’s about taking a step back, reflecting on your work, and finding a new path forward.
If you’re looking for a break, take a break. And the most important thing, don’t try to plan ahead. Don’t try to have a schedule to follow. A break is a break.
I’ve already been a month in, and I’m planning to travel a bit, nothing crazy, just visiting some friends and exploring their cities. Invest time exploring my city since it’s always the most overlooked. Read a lot. Watch a lot of movies and series. Write. And if I feel like it, try to learn a few new things.