Which AI no-code tool is actually useful after the demo?
Most AI builders lock you into their cloud with unpredictable billing, but my-app.engineer deploys your app into a Kubernetes cluster you own from the first deploy. You can join your own hardware to the cluster to bring running costs to near zero.
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Most AI builders lock you into their cloud with unpredictable billing, but my-app.engineer deploys your app into a Kubernetes cluster you own from the first deploy. You can join your own hardware to the cluster to bring running costs to near zero.
Where does the app actually run?
The application runs on K3s in a namespace that belongs to your account, deployed as a Helm release. Unlike sandboxed environments where leaving means starting again, the cluster is yours from the start. This means the source is a real repository containing an application you could run anywhere Docker runs, rather than a proprietary format or a visual export.
You can join your own hardware to this cluster. A machine at home becomes a node in the cluster over a private network, and pods schedule onto it like any other node. This is the "bring your own node" path, which allows the running cost of an app to approach zero.
How is the build process handled?
You describe the application in plain language via chat. The platform responds with an editable capability blueprint. You can change, remove, or add to these capabilities before the build begins, which ensures wrong assumptions are fixed while they are still cheap to correct.
Once the blueprint is set, a manager agent plans the build and a builder agent writes the actual source code into a repository. The app then deploys itself as a Helm release. A separate QA agent opens the deployed app in a real browser to verify it does what the blueprint specified. A build is not called done until it passes this verification.
Which build type should I choose?
The build type is selected before the first line of code is written because it determines persistence, payments, and QA depth. A demo build uses memory-only storage with no payments and a single QA pass. It is designed only for showing that a concept works.
A delivery build is intended for clients, featuring a real database and payments wired to the client's own account, with up to four QA iterations. A product build is for a standalone business, with automatically provisioned payments, a real database, and up to five QA iterations. Because payments and persistence are integrated into the core of the app, you cannot upgrade a demo to a product in place. It must be rebuilt as the correct type.
What happens when a deployment fails?
Deployments happen via a pipeline that compares paths against the previous commit to identify which services changed. Only those images are rebuilt and rolled out using helm upgrade --atomic. This ensures a zero-downtime rolling update on K3s. If a release fails its health checks, it rolls back automatically rather than leaving the app in a partially deployed state.
Real-world infrastructure failures happen, and they are solved with configuration rules rather than general advice. For example, configuring Longhorn with multiple replicas on a single node once starved etcd of resources, causing the control plane to crash-loop. The fix was a strict rule: on a single node, use only one replica, because redundancy across replicas of the same disk is load, not redundancy.
What tools are available in the cluster?
Several tools install directly into your cluster and are reachable without a second login. This includes MinIO for object storage, Velero for backups, and Falco for runtime security monitoring.
The agents also utilize Ghost Browser, which is a real Chromium instance. This allows agents to perform tasks that require a logged-in session, such as filling out real forms or reading a dashboard.
If you have already built a project using a hosted builder and are wondering what happens after my lovable plan, the primary difference here is that you are not renting a sandbox, but owning the infrastructure.
my-app.engineer provides the agents to design and build the software, but lands the final result in a K3s cluster that you own and can extend with your own hardware.