Maturity Assessment

Runtime Governance Maturity

Assess your organization's AI governance posture. Identify gaps. Deploy containment. Certify your capability to govern agentic systems deterministically.

The 5-Level Maturity Model

Most engineering organizations are at Level 1 or 2. The infrastructure on this platform enables immediate elevation to Level 4.

Level 1

Ad Hoc

No governance infrastructure. Agents run unrestricted. Failures discovered after damage.

No system prompts or policiesNo cost limitsNo file access restrictionsNo audit trail
Assessment: Zero governance. All 15 failure modes are uncontained.
Level 2

Reactive

System prompts exist but are text-based suggestions. Bypassed under context pressure.

CLAUDE.md / .cursorrules deployedManual code reviewNo automated enforcementBasic retry awareness
Assessment: Text-based governance only. 12+ failure modes uncontained.
Level 3

Structured

YAML policies and some middleware. Automated enforcement exists but is not comprehensive.

Policy-as-code (YAML)Some automated gatesBasic cost limitsPartial audit trail
Assessment: Partial governance. 6-8 failure modes contained.
Level 4

Governed

Full 4-layer runtime governance. Deterministic enforcement with telemetry across Identity, Skill, Tool, and Environment.

4-layer governance deployedAutomated enforcement on all layersFinancial circuit breakersFull audit trail with rollback
Assessment: Comprehensive governance. All 15 failure modes contained.
Level 5

Institutional

Self-healing governance with adaptive thresholds, automatic remediation, cross-team telemetry, and organizational learning.

Adaptive threshold tuningAutomatic remediation policiesCross-team governance telemetryGovernance evolution pipeline
Assessment: Institutional governance. Self-improving containment infrastructure.

Certification Tracks

Institutional credentials that map directly to the runtime governance ontology. Each track requires demonstrated deployment and configuration competency.

Level 3

Runtime Governance Practitioner

Deploy and configure governance skills across all 4 architectural layers.

Prerequisites
  • Deploy 3+ governance modules
  • Configure policy.yaml
  • Pass YAML policy audit
Level 4

Runtime Governance Architect

Design complete governance architectures for multi-agent environments.

Prerequisites
  • Deploy all 15 governance modules
  • Configure middleware.ts
  • Design custom policies
  • Pass architecture review
Specialist

MCP Governance Certified

Secure MCP deployments with capability manifests, file guards, and supply chain verification.

Prerequisites
  • Deploy MCP Governance module
  • Configure capability manifests
  • Implement file guards
  • Pass security review
Specialist

Bounded Cognition Certified

Manage agent context windows, prevent context rot, and optimize token economics.

Prerequisites
  • Deploy context governance stack
  • Configure checkpoint rotation
  • Implement cost monitoring
  • Pass economics audit

Quick Self-Assessment

Answer these 5 questions to estimate your current governance maturity level.

1. Do your AI agents have written operational policies (CLAUDE.md, policy.yaml)?

No → Level 1Yes → Level 2+

2. Are those policies enforced by middleware (not just text)?

Text only → Level 2Middleware → Level 3+

3. Do you have automated cost caps, retry limits, and file guards?

No → Level 2Yes → Level 3+

4. Is governance deployed across all 4 layers (Identity, Skill, Tool, Environment)?

Partial → Level 3Complete → Level 4

5. Does your governance infrastructure self-adapt and improve?

Manual → Level 4Adaptive → Level 5
Executive

Board-Ready Briefing →

Intelligence

Runtime Failure Index →

Metrics

Governance Telemetry →

Start Building Governance Maturity

Each governance module moves you one level up the maturity model. Deploy any module. Measure the delta. Build toward institutional governance.

View All 15 Runtime Modules →
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Richard Ewing — AI Economist & Capital Auditor