For the longest time, the state of the art for software development environments targeting Azure has been DevOps. This adds the engineering principles of extreme programming and agile to systems administration and the managing of infrastructure, builds and deployments. GitOps layers on top of DevOps so that the infrastructure itself has a build and test and deployment pipeline. For AI tools to automate changes to software systems, absolutely everything has to be automated. This includes the infrastructure of the system, which is comprised of a number of various applications. The structure of this system has to be completely automated in order to get the advantages from AI. Demo heavy. (Uses Azure for all infrastructure)