Magenta Canon is a runnable evaluation context for autonomous AI agents: it models a proposal model (agents propose, they do not execute), capability ceilings (no actor exceeds granted authority), cryptographic authority topology, behavioral drift detection via precedent memory, and epoch-bound permission grants. It does not solve AI alignment and does not govern model architecture, training, inference quality, or output correctness.
- Proposal model: autonomous agents submit proposals, humans authorize before execution
- Capability ceilings: no agent may exceed or delegate beyond its granted authority level
- Corrigibility: agents propose and humans authorize; a fully-wired production human-override channel is a roadmap goal
JURISDICTION
Autonomous Systems
The accountability gateway applied to AI agents. Proposal physics, capability ceilings, and human override channels.
How to Read This Proof Room
Four states, kept apart.
- Runnable / proven control pattern — executes today against the gate: delegated actions are allowed, withheld actions are blocked before downstream, both are recorded, and the evidence verifies independently.
- Reference / mock integration — the downstream tool in these examples is an audited mock, not a live provider. It proves the control pattern and the downstream absence of a blocked call, and nothing about a real provider's behavior.
- Future provider integration — connecting a real provider is design-partner work that has not been built. No live provider connection exists, and none is implied by a workflow appearing on this page.
- Not claimed — no compliance certification, no professional advice, no real-world side effects, and no assertion that a customer's own policies are correct.
Enforcement is scoped to the MCP tools/call method class; other MCP methods pass through the gateway ungated. The refund ceiling is the one numeric threshold the gate enforces today — other boundaries are expressed as tool-scoped allowlists under default-deny.
What Magenta Governs
The boundary stated plainly: Magenta governs what an autonomous agent is allowed to do through external tool calls, and records the decision. It is an action-control and evidence layer, not a model-cognition, alignment, or broad AI-safety solution.
- Capability ceilings — an agent cannot exceed the authority an operator delegated, and cannot grant itself more (runnable)
- Default-deny over the MCP tools/call method class — undelegated tool calls are refused before downstream (runnable)
- Evidence — signed, hash-chained receipts for allow and block alike, independently verifiable (runnable)
- Corrigibility — ratified doctrine plus a documented fail-closed intervention path; a fully wired production human-override channel is roadmap and is not claimed as in place
- Authority topology and precedent memory — separate architecture and reference material; they are not what the gateway consults on a tools/call
- Not model alignment, not prompt-injection prevention, and not a guarantee of safe outcomes
What Magenta Does Not Govern
Magenta Canon is an accountability gateway for AI-agent tool calls, not an AI safety or model quality system. The following fall outside the scope of the gateway.
- Model architecture or training
- Inference quality
- Output correctness
- Agent intelligence
Related Governance Jurisdictions
Autonomous systems often operate across regulated domains. The Magenta Canon accountability gateway also applies in legal, financial, and healthcare contexts — see the full jurisdictions overview.
Safety Clarification: Default-deny enforcement expresses policy discipline, not safety guarantees. Magenta Canon does not ensure safe outcomes, prevent harm, or guarantee correct behavior.