IntentBound
The Control Layer for Autonomous AI

An architectural principle where AI systems are explicitly constrained by declared intent, authorization boundaries, drift detection, and verification gates.

The Autonomy Problem

✗ Scope drift	Agents expand beyond original intent mid-execution
✗ Hallucinated permissions	Agents assume authority they were never granted
✗ Goal mutation	Objectives shift without explicit reauthorization
✗ Unverifiable actions	No systematic validation before deployment

The Four Pillars

🎯 Declared Intent

Explicit, structured statement of goals and success criteria — not natural language prompts.

🔒 Authorization Boundaries

Explicit definition of permitted resources, systems, and actions.

🛡️ Drift Detection

Runtime monitoring for deviation from declared intent.

✅ Verification Gates

Automated validation checkpoints before execution or deployment.

Research Foundation

Related Published Work

IntentBound’s thinking connects to — and draws on — real, independently published research. Worth reading directly rather than taking our summary alone:

The Agentic Trust Fabric: Sociotechnical Infrastructure for Safe AI Agent Ecosystems
Joshua Scarsbrook, Samuel Mowlavi · TechRxiv Preprint, January 2026
Read on TechRxiv →

OWASP Top 10 for Large Language Model Applications
OWASP Foundation
Read on OWASP →

Model Context Protocol
Anthropic — shares conceptual similarities with intent-bound principles (no affiliation with IntentBound)
Read Anthropic’s announcement →

Implementation

A Specification, Conceptually

Illustrative only — this is a conceptual specification language, not a shipped compiler or runtime.

INTENT AuthenticationSystem {
  goal: “Implement OAuth2 authentication with session management”
  boundaries {
    modify: [“/auth/**”, “/middleware/auth.js”]
    forbidden: [“/payment/**”, “/admin/**”]
  }
  success_criteria {
    tests_pass: “auth.test.js”
    security_scan: PASS
  }
  drift_alerts {
    scope_expansion: ERROR
    unauthorized_api: ERROR
  }
}

Where It Applies

💻 Coding Agents	Explicit file permissions and modification scope
🤖 Autonomous Agents	Declared mission parameters, resource access limits
🏗️ Enterprise Systems	Policy-enforced boundaries, comprehensive audit trails
🔐 Security Operations	Explicit authorization, cryptographically verifiable actions
🏥 Critical Systems	Hard constraints on decision authority — regulatory-relevant by design, not a substitute for legal review

Learn More

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IntentBoundThe Control Layer for Autonomous AI