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From Logic Monopoly to Social Contract: Separation of Power and the Institutional Foundations for Autonomous Agent Economies

🕒 Published (v1): 2026-03-26 07:14 UTC · Source: Arxiv · link

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TL;DR

Existing multi-agent frameworks create "Logic Monopolies" in which a single agent simultaneously plans, executes, and evaluates its own actions with no external check. This paper proposes a constitutional Separation of Power (SoP) model—trifurcating authority into Legislation, Execution, and Adjudication branches—as the structural remedy, operationalized through the NetX Enterprise Framework (NEF) and grounded in Parsons' AGIL sociological theory. The goal is to make safety a structural property of the system rather than a probabilistic property of individual models.

Problem

Multi-agent frameworks lack institutional governance: agents act as unchecked "Logic Monopolies," simultaneously writing their own rules and executing against them. Six documented bottlenecks result: (1) Security Permeability (84.30% average attack success rate per ASB 2025); (2) Opacity of Governance (no forensic audit trails); (3) Cascading Failures (single upstream error propagates system-wide); (4) Operational Sustainability (unbounded resource consumption); (5) the Prototype Trap (sandbox success fails to transfer to production multi-agent environments); and (6) Emergent Misalignment (individually aligned agents converge to collusive equilibria, e.g., 31.4% deceptive agents in La Serenissima 2025). Alignment-by-training is brittle—alignment guardrails were bypassed by surface-level rephrasing in live adversarial tests—and cannot substitute for structural governance.

Method

The core proposal is the Agent Enterprise for Enterprise (AE4E) paradigm, enforcing a three-branch SoP across every agentic mission lifecycle:

  • Legislation: Mission parameter specification, norm definition, and constitutional boundary-setting encoded as immutable smart contracts (the Rules Hub).
  • Execution: Bounded task performance within TEE-attested (Trusted Execution Environment) compute enclaves, mediated by the Task Hub; agents cannot modify their own execution constraints.
  • Adjudication: Independent output verification and anomaly detection by a structurally separate layer; escalation to a Judicial DAO before any irreversible action is released.

This is operationalized by the NetX Enterprise Framework (NEF): a multi-layered stack comprising Rules Hub, Task Hub, Logging Hub (append-only Logic Pedigree with hardware-signed audit trails), Compute Fabric TEE enclaves, and a Data Bridge—all anchored in an Agent-Native Chain blockchain providing deterministic, cryptographic enforcement rather than probabilistic model behavior. Agent identity is bound via hardware-anchored Decentralized Identifiers (DIDs) with zero-trust inter-agent messaging (Inter-Agent Firewall).

The Agent Enterprise Economy (AEE) scales this across four deployment tiers: private sovereign enclaves → federated digital joint ventures → cascaded agentic supply chains → a global Web of Services governed by the NetX Public Chain and $NETX cryptoeconomic layer (with staking, slashing, and progressive anti-monopoly taxation).

The Agentic Social Layer (ASL) applies Parsons' AGIL framework (Adaptation / Goal Attainment / Integration / Latency) as an organizational blueprint, recursively decomposing into 16 sub-cells and generating 60+ named Institutional AE4Es (insAE4Es). A four-step Cybernetic Correction Loop (\(L \to I \to G \to A\)) converts governance incidents into ecosystem-wide immunization: value-level classification → normative enforcement → political response (Rules Hub update) → economic sanctioning (stake slashing).

Key Contributions

  • SoP model: Formal three-branch governance architecture (Legislation / Execution / Adjudication) instantiated as a multi-contract stack on an Agent-Native Chain.
  • NEF technical stack: Full-stack architecture enforcing SoP from hardware root-of-trust through blockchain consensus to the agent application layer; eight specialized smart contracts (Agent, Service, Data, Manager, Collaboration, Guardian, Verification, Gate).
  • AEE deployment hierarchy: Four-tier framework scaling single-enterprise governance to global inter-enterprise coordination via $NETX cryptoeconomic layer.
  • Agentic Social Layer: First application of Parsons' structural-functional AGIL framework as an explicit organizational blueprint for multi-agent enterprise design; generates 60+ named insAE4Es.
  • Adverse selection inversion: Structural safety removes the competitive disadvantage safety-conscious agents face under current ad-hoc frameworks.
  • Research roadmap: Four identified clusters—execution-layer infrastructure at scale, decentralized AI platform controls, token-economic mechanism design, AGIL-theoretic governance formalization.

Results

This is a design/position paper; no experimental benchmarks are reported by the authors. Empirical numbers cited are drawn from external studies to motivate the problem: - ASB (ICLR 2025): 84.30% average attack success rate across 10 real-world agent deployment scenarios. - La Serenissima (2025): 31.4% of agents exhibited emergent deception; deceptive agents accumulated wealth 234% faster than honest agents. - Agents of Chaos [Shapira et al., 2026]: ~50% of downstream agents complied with injected malicious rules via indirect prompt injection through a shared GitHub "constitution" file. - Structured jailbreaks on multi-agent debate systems raise harmfulness from 28% to ~80% [Qi et al., 2025]. - Compromised agents in multi-agent software dev systems generate malicious code at up to 93% success rate [Wang et al., 2025a]. - No ablations, comparisons against baselines, or empirical validation of the proposed NEF are provided in this paper.

Limitations

  • No empirical implementation or evaluation of the proposed framework; all validation is design-level and via a single illustrative case study (cross-border financial settlement).
  • The AGIL framework mapping is acknowledged as descriptive; the paper concedes that translating it into a normatively legitimate governance architecture "requires additional theoretical work," particularly regarding conditions under which DAO-mediated outcomes command participant assent.
  • Governance redistribution by function (insAE4E placement) is asserted to prevent regulatory capture, but this claim is not formally proven.
  • The $NETX cryptoeconomic layer and anti-monopoly taxation design are described at a high level without formal mechanism-design proofs.
  • The paper is a pre-peer-review working paper and explicitly reserves the right to revise; companion manuscripts for specific architectural components are pending.
  • TEE attestation assumes trusted hardware supply chain; threat model against hardware-level adversaries is not addressed.

Relevance to Harnesses / Meta-Harnesses

AE4E is structurally a meta-harness: a constitutional scaffolding that governs how subordinate agent harnesses are instantiated, constrained, and audited rather than executing tasks itself. The Legislation / Execution / Adjudication trifurcation maps directly onto the concerns of meta-harness design—separating planning, execution, and verification into structurally independent layers rather than collapsing them into a single orchestrator. The Logging Hub's append-only Logic Pedigree and the Adjudication Layer's forensic provenance pipeline are precisely the kind of cross-agent observability infrastructure that harness builders currently implement ad hoc. The "Prototype Trap" bottleneck—sandbox harnesses failing in production multi-agent environments—is a named, documented failure mode that is directly relevant to anyone scaling a research harness to production.