00 - Vision
Agent Orchestrator is a Harness Engineering control plane for agent-first software delivery.
OpenAI recently used the term Harness Engineering to describe an engineering style where humans focus less on hand-writing code and more on designing environments, specifying intent, and building feedback loops that let agents do reliable work. This project adopts that framing directly.
What We Are Building
- A local-first control plane that abstracts Claude Code, Codex, OpenCode, Gemini CLI, and other shell-based tools behind one resource model
- A declarative harness where workflows, agents, triggers, secrets, policies, and observability live as versioned repository assets
- A long-running execution runtime that can keep plan -> implement -> test -> review -> fix loops alive for hours or days
Why a Control Plane?
A serious engineering harness does more than invoke an agent once. It decides:
- which agent should run
- in which workspace
- on which workflow step
- with which guardrails and secrets
- under which retry, pause, or recovery policy
- and how results are turned into auditable state, logs, and downstream actions
That is the role of this project.
Core Beliefs
- Humans steer, agents execute: people set goals, acceptance criteria, and constraints; the system coordinates execution.
- The repository is the system of record: manifests, docs, skills, QA artifacts, and policies should be versioned and discoverable in-repo.
- Guardrails matter more than heroic prompting: workflows, invariants, triggers, and recovery paths compound more than one-off prompts.
- Any shell-based agent should be portable: the control plane should outlive any single model or vendor.
- Long-running software delivery loops must be observable: durable state, logs, events, and traces are first-class requirements.
What This Is Not
- Not a chat wrapper around one model
- Not just a workflow DSL
- Not a generic CI/CD replacement for every enterprise use case
The ambition is narrower and more opinionated: become the control plane for agent-native engineering systems.
Product Direction
- Turn ad hoc agent usage into reusable workflow assets
- Let teams institutionalize QA, fix, review, governance, migration, and self-bootstrap loops
- Provide a stable harness layer above rapidly changing models and coding shells