I recently ran a values exercise with a team of engineers in 1-1s. Each had to select three sticky-notes from a predefined set of values. Every single one of them chose Cooperation.

When we asked what cooperation meant, I got five completely different answers:

As a teenager, I was all ideas and no follow-through. Every week brought a new concept, a new scheme, a new startup in my head. I wore my imagination like a badge. But over time, I had to confront something uncomfortable: ideas weren't rare. They were a ten a penny, a kind of noise that kept me from actually doing the hard work.

Each of these Ps need to be in place, in order, or you're doomed.

I've been doing a lot of vibe coding, and my particular tools of choice include v0.dev (as a Vercel fanboy). By default, v0 will use tailwind for styling. This means I've been using Tailwind for the first time, and... I hate it.

In a recent piece, I made the case that we should stop trying to build "perfect" AI. That imperfection is not a failure mode — it's intrinsic to how these systems work. Here, I want to go one step further: not just to excuse AI's flaws, but to explore how we can use them. How we can design with imperfection in mind.

In software engineering, complexity often masquerades as sophistication. Nowhere is this clearer than in frontend code that relies on inferential logic: the practice of deducing user intent or state based on limited information, rather than explicitly guiding the user experience.

We seem to have stumbled into a strange contradiction: we demand perfection from our machines, while tolerating imperfection from ourselves. The same people who chuckle at human error in the workplace will denounce AI systems for the slightest misstep. "It hallucinated a fact!" Yes. And you never have?

A week ago I tried switching my web browser's default search engine from Google to Perplexity.

I've deleted my Facebook, Twitter, and Instagram accounts.