Workflow

If you have used swamp.club at all, you probably think of it as an infrastructure automation tool. The ecosystem gravitates that way. The most-pulled extension is @john/k8s with 15 model types wrapping the Kubernetes API. The examples in the docs show pod health checks and deployment workflows. The leaderboard is full of people automating infrastructure tasks. That framing is incomplete. What swamp actually provides is a typed, versioned, schema-validated data layer for AI agents. The primitives are: models with Zod schemas, immutable versioned data, method execution, and composable workflow DAGs. Those primitives do not care whether the data flowing through them is pod status or prose rules. ...

A collision is coming that most teams have not noticed yet. On one side you have the workflow your team actually uses. If you run a platform or operations team, it probably looks something like Kanban: pull-based flow, WIP limits, design sessions before implementation, a small number of states that everyone understands. The workflow exists to serve the people. You have spent years tuning it. It works. On the other side you have the lifecycle your AI agent needs. If you are using an agentic framework — Swamp, or something like it — the agent operates through a state machine with enforced transitions, upfront planning, adversarial review gates, and checks that physically prevent skipping steps. The lifecycle exists to constrain the agent. It works. ...