We design Claude workflows with deterministic control, auditability, and human authority.
We help technical organizations deploy governed Claude systems — auditable, bounded, and built on the same constitutional architecture we already ship in safety-critical aviation.
Governance defines what the agent may do, what it may never touch, what requires human escalation, how evidence is recorded, and how decisions are replayed and audited. It is not a behavioral prompt. It is a structural constraint — enforced before execution, not after.
Every engagement starts with the governance architecture. We build Claude systems that can be audited, bounded, and trusted — then hand them off with documentation your team can maintain.
You have a Claude use case. You need to know what the agent may do autonomously, what it may never touch, and what requires human escalation.
A working governed Claude workflow. Governance established before AI is added — so what ships earns trust, not supervision.
Claude's capabilities evolve. Your governance layer needs to evolve with them. Monthly architectural review and escalation judgment.
Four composable Laws. Language-specific enforcement kernels. Domain jurisdictions that apply the Laws to specific operational contexts.
Constitutional framework. Four foundational Laws, the reducer pattern, evidence chain structure, and composability rules for jurisdiction design.
Read the Codex →SwiftVector · TSVector · RustVector. Each kernel compiles Laws into language-specific guarantees — actor isolation, pure functions, ARC memory management.
Kernel specs — coming soonObservation, Resource, Spatial, Authority — domain-agnostic primitives that compose differently per jurisdiction while remaining architecturally identical.
Law reference — coming soonThe governance layer is not an afterthought bolted onto an existing AI system. It is the foundation on which the AI system is built. Policy is defined before the first agent call. Every action is evaluated before execution. The constitutional architecture means the system can demonstrate compliance on demand — not merely claim it.
The constitutional architecture composes differently across aviation, desktop agents, and narrative AI. Same SwiftVector kernel. Replayable evidence in every jurisdiction.
AI can propose. Flightworks Sentinel decides. The record proves it. Sits between your AI layer and your autopilot — governing what AI is permitted to propose, issuing typed verdicts, and preserving replayable evidence of every decision.
Pre-commit governance gate for agents with shell and browser access. Allow / deny / escalate with signed decision artifacts.
Human authorship protected as a formal governance constraint. AI may draft prose; it cannot decide fate.
The governance architecture described on this site is grounded in published writing. These are the primary sources.
The foundational essay. Why autonomous AI agents need constitutional governance — and why behavioral oversight fails at scale.
Home lab build documentation. Six-node K3s cluster on M4 Pro Mac mini. Real infrastructure running governed AI workloads.
The constitutional specification. Eleven Laws in four groups, three enforcement kernels, and the nine criteria by which any valid implementation can be evaluated.
Governed autonomy is the conclusion of a career that started with network infrastructure, moved through iOS development, and arrived at AI governance on Apple Silicon. The through-line is a consistent focus on deterministic systems, verifiable behavior, and human authority over machine action.
MacSweeney LLC is applying to the Claude Partner Network as a specialist AI architecture and governance practice. We don't sell AI adoption — we build the governance layer that makes AI adoption trustworthy.