v0.3.1 has some larger architectural changes and let me rethink the approach. I had to rebuilt the engine. The old build-and-deploy model (build a container image with Buildah, hand it to Knative) is gone, replaced by an architecture designed around a single goal: get an AI-generated app to a live URL in seconds, with hardware-grade isolation, and never build a container on the deploy path.

AI is taking its place — in work, in private life, and everywhere in between. With this comes a couple of challenges: many are already in sight, others we can't yet imagine.

For corporates and businesses, an AI-enabled employee gains the capability to create artifacts like websites, apps, and more. Right now, these creations are either running within the context of the provider tool (a desktop app, a browser tab) or are clumsy to deploy — requiring support from an IT expert who understands containers, Kubernetes, and CI/CD pipelines.

vibeD enters the stage.

The idea of vibeD is to provide an endpoint for any GenAI tool to deploy artifacts under your own conditions, in a controllable environment. No deployment competencies needed for your non-IT personnel. Extensible, secure, and built on standards.

We're excited to announce the first public release of vibeD — the workload orchestrator purpose-built for GenAI-generated artifacts.