Coding agent orchestration

Orchestrate AI Coding Agents Through One Governed Control Plane

What is AI coding agent orchestration?

AI coding agent orchestration coordinates which software task each agent may perform, against which code state, under which evidence and review gates. Nexus adds software-delivery governance: durable authority, fenced ownership, independent exact-SHA review and controlled canonical integration around model workers.

Prompt chaining is not orchestration

Prompt chaining passes one model response into another. It can structure a conversation, but it does not establish authoritative ownership, repository identity, recovery rules or permission to integrate code.

Agent orchestration adds scheduling, state transitions and dependency management. Software-delivery governance goes further by defining which outputs may alter the canonical product and which evidence must exist first.

Prompt chain: message sequence
Orchestration: work and dependency coordination
Governance: authority, evidence and release rules

The control plane surrounds the agents

Nexus stores project and execution state in PostgreSQL so models do not become the source of truth. The scheduler allocates fenced work; workers produce candidate commits and evidence; independent review evaluates the exact candidate; integration remains a separate authority.

This architecture can route work to different hosted or self-hosted models where appropriate. Changing a model does not require replacing the governance layer.

Database-backed authority
Model-independent workers
Exact code identity
Canonical repository control

Coordination is measured by safe progress

More simultaneous agents do not automatically mean more delivery. Dependencies, review capacity and integration conflicts can turn raw concurrency into rework.

Nexus therefore treats verified, integrable progress as the useful output. Capacity controls and evidence gates favour reliable autonomous software development over the largest possible swarm.

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