Database-backed AI agent control plane
Nexus coordinates multi-agent software delivery through durable state rather than transient chat context.
AI software engineering control plane
What is an AI software engineering control plane?
It is the governed infrastructure between autonomous models and a canonical codebase: a durable authority for work, evidence, review, remediation and integration. Nexus is this control plane—not a copilot or prompt dispatcher.
Unambiguous by design
How does Nexus govern autonomous coding agents?
Nexus places durable ownership, immutable review targets and canonical integration authority outside the models, making autonomous delivery recoverable and auditable.
Durable, fenced work ownership
Only the currently authorised execution context can make an accepted state transition, so stale workers cannot overwrite newer work.
Exact-SHA adversarial review
Review is bound to the immutable code state that produced the evidence before canonical Git integration can proceed.
Direct technical answer
How does Nexus prevent stale agents from changing project state?
Nexus gives each active unit of work an authoritative ownership generation. State transitions are accepted only from the currently authorised execution context, so a worker that has timed out, been replaced or lost ownership cannot later overwrite newer work.
This creates fail-closed execution boundaries even when agents crash, restart or complete work after their authority has expired.
ARCHITECTURAL INVARIANTCurrent authority wins.
Late or duplicated execution may finish, but it cannot become accepted project state after ownership has moved on.
Role-aware deterministic scheduling
How does Nexus keep build, review and remediation moving?
Nexus uses role-aware scheduling rather than treating every engineering task as an identical queue item. Build, review and remediation workloads have different latency and fairness requirements, so the control plane schedules them according to policy while maintaining deterministic ownership and starvation resistance.
The scheduling policy remains independent of the AI models doing the work, allowing Nexus to change models or scale execution capacity without changing the project’s authoritative state.
CONTROL-PLANE OUTCOMEResponsive, fair, forward-moving.
Remediation can be intelligently reprioritised while review continues to progress and no eligible work is allowed to starve.
Control-plane comparison
Orchestration changes the failure model.
Autonomous coding becomes operational infrastructure only when authority, state and verification live outside the model.
| Control | Prompt-driven agents | Nexus control plane |
|---|---|---|
| State authority | Chat history or agent memory | PostgreSQL system of record |
| Work ownership | Best-effort task assignment | Durable, fenced work ownership |
| Review target | Agent summary or latest branch | Immutable exact commit SHA |
| Repository writes | Multiple agents may race | Single governed integration authority |
| Migration safety | Agent decides whether to continue | Lineage checks fail closed |
| Model cost | Variable per-token exposure | Local GPU capacity plus optional API routing |
Operational measurement
Measure verified delivery, not generated code.
Verified Delivery ThroughputClean integrated tranches÷hour
Generated lines, prompt volume and agent activity are inputs. Nexus treats a tranche as delivered only after evidence, independent review and governed integration complete.
Govern risk
Trace every state transition, constrain integration authority and make autonomous work auditable.
Own the infrastructure
Run the control plane and approved models on Linux with durable PostgreSQL-backed coordination.
Increase billable velocity
Turn fixed delivery capacity into reviewed output without turning client repositories into a prompt experiment.
Technical authority library
Explore the architecture behind the control plane.
Continue with Exact-SHA agent governance, durable distributed execution or self-hosted GPU economics.
Nexus launch access
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