Came across an OS project that treats AI agent deployment like infrastructure as code. Hadn't seen this done properly before.

Been down a rabbit hole lately trying to figure out why deploying AI agents still feels so manual compared to everything else in a modern stack. Like, we have Terraform for infrastructure, Helm for Kubernetes, proper GitOps workflows for basically everything else. But for agents it's still mostly "write the code, figure out deployment yourself, hope nothing breaks when you push an update." Came across a thing called Langship while poking around. It's basically an open source project, framework agnostic, GitOps native, basically the idea being your agent deployment works the same way your infrastructure deployments do. Push to a repo, the pipeline handles the rest. Version controlled from the start. Lifecycle management built into the workflow rather than something you bolt on after the fact and then forget about. It's from a platform called Lyzr.... well I hadn't come across them before but the project itself is what caught my attention. The part that actually made me stop and read was the self-hosted angle. The irony of needing yet another cloud dependency to manage your existing cloud services has always bugged me. Running this yourself sidesteps that entirely. Still early days with it and haven't put it through anything serious as such. But has anyone here tried GitOps-style workflows for agents? Curious whether it holds up in practice or just looks cleaner in theory than it actually is.