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I'm calling an LLM from my app, how do I make it a real agent system?

One system source to reviewchecked before runtime
The coding agent authors against a finite language, and Swirls validates the complete project.

#The question

"I'm calling an LLM from my app, how do I make it a real agent system?" is really a question about repeatability. Swirls makes the answer concrete: the whole system is declared in .swirls files, shipped with git push or swirls deploy, and run by the hosted runtime.

#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

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.

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.

Add the people, data, authority, and decisions around this job.

Keep this solution beside the Apps, records, rules, connections, and reviews it depends on in one .swirls project.

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