Gergely Orosz writes an unusually personal piece: he is coming to terms with AI writing most of his shipped production code — faster, with similar results, and better than him in less-familiar languages. The essay is honest about what that costs, not just what it saves. It is drawn from his longer analysis “When AI writes almost all code, what happens to software engineering?”
- The craft is the loss: years of learning C, decoding complex codebases, debugging — all validated by the simple fact of writing code that works. AI devalues that validation
- The zone was identity: some of his best memories of building software are being locked in, compiling, running, and seeing “YES, it worked”
- It was never pure joy: the focus demands were real, including time-estimate conflicts — time passes differently when you’re deep in a hard problem
- The open question: does satisfaction migrate up the stack, to thinking about higher-level problems while instructing more complex code to be written?
The piece refuses both lazy framings — “AI makes engineers obsolete” and “AI is just a better tool.” It treats the emotional accounting seriously and ends without a tidy resolution: “Yes, AI is convenient, but there’s also a loss.”