What it is
Agents follow a process badly. The harness makes them follow it.
One workflow.yaml describes the business process as a state machine and enforces it on every step.
The agent sees the current state's instructions, tools and transitions, and that is its whole view of the graph.
A human state parks the session for a decision.
A sub-workflow runs as a child with a typed contract at the boundary.
Cases with rubrics grade whether the agent did the task.
It is a thin layer over LangChain Deep Agents and LangGraph, written in TypeScript, MIT licensed, published as @archmax-ai/harness.
My part
The harness is an archmax-ai project. I contribute to it and am listed as a maintainer of the npm package.
My largest piece is the audit trail. Every state traversal, human decision and error route is recorded in a checkpointed trail, so a test case can assert on the path the agent actually took. Beyond that I worked on the governance kernel and on delegation between workflows, set up the CI, the secret scanning and the npm release pipeline, and worked through the documentation for clarity.
Most of that predates the public repository, which starts in September 2026. The docs cover the workflow machine, sessions, triggers, skills, sub-workflows and testing.