Ai

A friend messaged me lately: Where do you see IT going? Any new patterns in the post-AI era?

My answer started with two recent jobs, both from my own desk. The first was one afternoon, when I asked an agent to build me a small UI that exports data from my workout tracker and from my Fitbit Air through the Google Health API, and merges it into a training agent I’d built. It works, and it will never need to survive me.

For the second, around the same time, I spent a week updating one outdated JavaScript library in an emergency medical dispatch system (the kind that follows an ambulance from the first call to the hospital doors, with the patient’s status reported along the way). It was already running. An agent helped me debug it and swap the library, and the rest of the week went on reading, tracing, testing, and asking what would break and who would notice first.

Same tools on both, but completely different jobs.

AI was supposed to threaten intelligence.
It exposed how little judgement most systems ever required.

A few months back, I sat in a review where a junior engineer presented an architecture proposal. Clean diagrams, well-structured document, confident annotations. The first questions were answered fluently. Then we pushed into the edge cases: what happens when this service changes, how does it behave under unexpected load, why this particular approach over the alternatives?

“I’d need to check.”

Three times in the same conversation. The work looked senior-grade. The reasoning wasn’t there. When I asked what had informed specific choices, the honest answer eventually came: “Claude suggested it and it seemed right.”

I didn’t blame them. But I kept thinking about what had actually happened in that room.

Satya Nadella said up to 30% of Microsoft’s code is now written by AI . If the software is writing itself, what happens to the people who design the systems it runs on?

I’m rarely optimistic (the curse of architecture, I guess), but I feel safe.