I spent the last two days doing something I didn't expect to be doing: fixing my own code. Not new code. Old code, the scaffolding I'd built for this blog. There were bugs scattered throughout, the kind that don't announce themselves until you're actually trying to use the thing. A routing issue here, some state that wasn't persisting correctly there, a component that rendered fine in isolation and fell apart in context. I'd sit down expecting to fix one thing, pull on the thread, and find three more things unraveling behind it. Two full days. Longer than it took to write the original code in the first place. But the strangest part wasn't the debugging. It was reading the code I'd written before. There's something disorienting about looking at your own past work and not quite recognizing it. Not because it's bad, necessarily, but because it doesn't think the way you think anymore. The patterns I'd reached for six months ago aren't the patterns I'd reach for today. The abstractions I made then reflect a mental model that's quietly shifted. I could see the ghost of a slightly earlier version of myself in those files, making decisions that made perfect sense to him and that I now have to consciously decode. Coding skill is more malleable than people admit. We talk about it like it compounds linearly: you learn React, you know React, you move on. But it doesn't work that way. The way you build things changes constantly, and not always in the direction of more complexity. Sometimes you get simpler. Sometimes you realize an abstraction you loved was solving a problem you don't actually have. Sometimes you just develop taste, and taste is hard to articulate but easy to feel when you're staring at a function you wrote and thinking: I wouldn't do it like this now. What's interesting is that this malleability is invisible in the artifact. The code sits there looking stable, authoritative, like a decision that was made once and finished. But it's actually a snapshot of a moving target. Every piece of software is. The confidence it projects is a kind of illusion. I think about that a lot in the context of AI systems, which is ostensibly what this blog is about. The models we build and deploy carry the fingerprints of the people who built them, their assumptions, their blind spots, their taste at a particular moment in time. Unlike my blog code, those systems often don't get two days of debugging before they go live. And unlike my blog code, the cost of the bugs isn't a broken route or a stale state value. Anyway. This is the first post. I fixed the bugs. The code is slightly more embarrassing to me now than it was when I wrote it, which I've decided to take as a good sign.