How to deploy an AI-built app to production
Take an AI-built app from a working prototype to a repeatable production deployment with persistent data, secrets, checks, monitoring and recovery.
Deployment guideRead guide
Shipping AI apps.
Turn agent-built code into repeatable releases, useful previews and durable background work.
A working prototype needs a reproducible build, an appropriate runtime and a tested path through failure. These guides cover the move to production and the delivery systems that keep subsequent changes operable.
Start here: How to deploy an AI-built app to production
CI/CD for AI-generated code: build a release process you can trust
Design CI/CD for AI-generated changes with independent acceptance tests, immutable artifacts, scoped deployment identities and recovery checks.
Delivery workflow guideRead guide
Preview environments for AI coding agents: isolation, data and cleanup
Design useful preview environments for AI coding agents with isolated credentials, realistic test data, visible limits and a reliable cleanup lifecycle.
Environment design guideRead guide
Background jobs for AI apps: queues, retries and idempotency
Design background processing for AI apps with durable job state, bounded retries, idempotent side effects, queue monitoring and clear user feedback.
Application architecture guideRead guide