In my last post I argued that the way to modernise a large, tangled system is not a full rewrite but the strangler fig, carving off one piece at a time. Which leaves the real question: which piece first? A seam is simply a place you can change one side of a line without disturbing the other. In a tightly coupled system those lines are faint, but rarely absent. Here is the order I look in.
In my last post I wrote about Knowledge Debt, what happens when we stop understanding the systems we ship. The obvious follow-up: what do we do about it, especially in the large, long-lived codebases where it has compounded the longest?
AI coding demonstrations rarely resemble those systems. They start from an empty folder, which has no history to misunderstand. We work in the opposite conditions: decades of accumulated behaviour, outdated documentation, and critical rules living only in the memory of people who may have long since left.
We talk a lot about tech debt. We're about to learn that Knowledge Debt is the harder problem.
There's a growing debate in our industry, on one side, the "vibe coders" who greenfield entire applications with AI agents without a second thought. On the other, experienced engineers like Zoran Horvat who warn, with good reason, that we're sleepwalking into a profession we no longer understand.
Both sides have a point. But I think we're missing something in the middle.