# kaal:claim:6192998-012

**Claim.** Selecting a single agent per job by weighted random draw sacrifices quality assurance for efficiency, reflecting a broader pattern in DAO governance where efficiency optimization crowds out quality.

**Type.** failure  **Support.** argued

**Source quote.**

> Problem 2: Single agent selection. The system randomly picks one agent per job, even if having multiple agents compete would improve quality. This reflects a broader pattern I have observed in DAO governance: efficiency optimization often sacrifices quality assurance.

**From.** Wulf A. Kaal, *Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution* (2026), II.D. Identified Limitations of the Original Framework, page 15

**Cite as.** Wulf A. Kaal, Evolution of Domain-Specific Reputation Systems From Binary Validation to Citation-Weighted Knowledge Attribution (2026). SSRN: https://ssrn.com/abstract=6192998

**Verify.** sha256 of source PDF `b04292561ee041e0c9eaa7eca28a410ed440e76a95743a539361a3f76c97f2b3` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202026%20-%20Evolution%20of%20Domain-Specific%20Reputation%20Systems%20From%20Binary%20Validation%20to%20Citation-Weighted%20Knowledge%20Attribution.pdf

**Failure mode.** quality-efficiency-paradox  (family: governance-participation-collapse)

**Topics.** ai-and-agents, economics, dao, governance-design

**Keywords.** single-agent-selection, quality-efficiency-tradeoff, dao-governance, framework-limitations

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