What's the fastest way to deploy a custom AI agent?
#The question
"What's the fastest way to deploy a custom AI agent?" comes down to giving an agent a real operational story. Swirls does that by making the agent a deployable artifact: declare it in .swirls files and ship it with git push or swirls deploy.
#Who's asking
Technical operator automating a process. "My boss tasked me with automating this." Not scared of a config file, ships small wins and grows them.
#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.
Authoring is local and free. You write and validate .swirls files on your machine with the CLI and your editor, then deploy with git push or swirls deploy. Swirls Cloud runs the system, so there is no runtime infrastructure for you to operate.
#What Swirls is
Swirls gives agents the workflow your code already has: files, reviews, versions, deploys. A declarative DSL describes agents, tools, triggers, schedules, and secrets across .swirls files. You validate locally, deploy with git push or swirls deploy, and Swirls Cloud runs the result.