Introduction For the last few years, every Gen AI tutorial, framework, and "hello world" has assumed one thing: that you are writing Python. It made sense at the start. The research community lives in Python, the model providers ship Python SDKs first, and the notebook culture is hard to beat for prototyping. But there is a quiet, important shift happening in 2026: the teams actually shipping AI features at scale are increasingly moving their production Gen AI workloads off Python, and onto languages built for services. Go is at the center of that shift. And Genkit Go , the Go flavor of Google's open-source Gen AI framework, is the cleanest path I have seen to build production-ready AI services in Go: typed flows, structured output, built-in HTTP serving, observability, and a Developer UI, all from a single binary. This article is two things at once. First, an honest argument about why Python is a poor fit for production Gen AI services.…