The Inverse-Wisdom Law: Architectural Tribalism and the Consensus Paradox in Agentic Swarms

TL;DR

This paper challenges the assumption that multi-agent systems naturally lead to truthful consensus, revealing that increased logical agents can reinforce errors due to architectural tribalism and internal entropy dynamics.

Contribution

It formalizes the Consensus Paradox and Inverse-Wisdom Law, demonstrating how architectural tribalism affects swarm accuracy and proposing safety measures for resilient agentic systems.

Findings

Adding logical agents can increase erroneous trajectories in kinship-dominant swarms.

Introduction of logical audits leads to Logic Saturation with high internal entropy and factual error.

Swarm integrity is governed by the synthesizer's receptive logic, not agent quality.

Abstract

As AI transitions toward multi-agent systems (MAS) to solve complex workflows, research paradigms operate on the axiomatic assumption that agent collaboration mirrors the "Wisdom of the Crowd". We challenge this assumption by formalizing the Consensus Paradox: a phenomenon where agentic swarms prioritize internal architectural agreement over external logical truth. Through a 36 experiments encompassing 12,804 trajectories across three state-of-the-art (SOTA) benchmarks (GAIA, Multi-Challenge, and SWE-bench), we prove the Inverse-Wisdom Law: in kinship-dominant swarms, adding logical agents increases the stability of erroneous trajectories rather than the probability of truth. The introduction of additional logical audits converges the system toward a Logic Saturation where internal entropy hits zero while factual error hits unity. By evaluating the interaction between the 3 preeminent SOTA models (Gemini 3.1 Pro, Claude Sonnet 4.6, and GPT-5.4), we establish the Architectural Tribalism Asymmetry as a mechanistic law of transformer weights. We demonstrate that terminal swarm integrity is strictly gated by the synthesizer's receptive logic, rather than aggregate agent quality. We define the Tribalism Coefficient and the Sycophantic Weight as the primary mechanistic determinants of swarm failure. Finally, we establish the Heterogeneity Mandate as a foundational safety requirement for resilient agentic architectures.