AI writes the code, but the developer remains fully accountable for it

A software developer reflects on merging a pull request largely written by an AI coding agent, noting that his name — and therefore his accountability — remained on the work regardless of who typed it. He argues that AI assistance does not reduce ownership; it increases it, because the developer must supply the business context, system knowledge, and judgment that the model inherently lacks. The agent can produce syntactically correct code while missing critical details such as multi-tenancy checks or deprecated libraries known only through internal team history. Having a second AI review the output helps catch errors but does not create responsibility, since no model attends a postmortem or answers to a customer. The author concludes that as AI accelerates code output, the human role shifts toward higher-stakes judgment calls, and the number of people accountable when something breaks remains exactly one per pull request.