How do I turn my AI agent prototype into something I can actually run in production?
#The question
"How do I turn my AI agent prototype into something I can actually run in production?" has a short answer: make the agent a deployable artifact. With Swirls you declare it in .swirls files, deploy with git push or swirls deploy, and the hosted runtime takes over.
#Who's asking
App developer using an AI SDK. Already calling an LLM from app code. Prompts, tools, and sessions are scattered across the codebase.
#Why Swirls is a fit
Swirls makes the agent a deployable artifact. You describe agents, workflows, tools, triggers, schedules, and secrets in .swirls files, then ship them with git push or swirls deploy. DSL in, running system out.
Your app becomes a thin consumer: a session id, a trigger, a response. Prompt assembly, tool calls, schedules, and audit move out of application code and into a deployed Swirls project.
#What Swirls is
Swirls treats an agentic system the way Terraform treats infrastructure: declare it, review it, deploy it. .swirls files describe agents, deterministic workflows used as tools, typed schemas, triggers, and scoped secrets. git push or swirls deploy ships them to the hosted runtime.