Phrony is an open specification and open-source runtime for declaring, deploying, and running AI agents — the way teams already treat services and infrastructure.
The paradigm
Every agent starts small: a prompt, a few tools, some glue inside an app. That's the right shape for a helper inside a feature. But the agents teams ship now have grown up — many tools, real budgets, escalation paths, humans in the loop, and constant change. The thing you care about is no longer a function. It's an entity. Code is the wrong place to keep it.
How it works
Phrony treats an agent as a first-class primitive — the way you already treat services and infrastructure.
01Declared
02Deployed
03Run
Its purpose, tools, policies, limits, and human checkpoints live in one versioned manifest, not scattered across application code.
Technically, this gives you one place where agent behavior is decided. For governance, it means every action passes through a single enforcement and evidence point — by construction, not by convention.
Phrony is offered as a methodology and a runtime you can run yourself. The spec is the standard; the open-source project is the reference implementation.
Open specification
The manifest schema, policy model, runtime contract, and trace format are open. Anyone can implement a conformant runtime. Manifests are portable.
Open-source runtime
The reference implementation is on GitHub. Run it locally with Docker, validate manifests, deploy agents, and drive sessions with the operator CLI.
What the runtime handles
Session lifecycle, the model loop, tool dispatch, policy enforcement, limits, human-in-the-loop pauses, and structured traces — so you do not rebuild that stack in every service.
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