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_map.md
theseus: add 3 claims on collective AI design implications
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adversarial PR review produces higher quality knowledge than self-review because separated proposer and evaluator roles catch errors that the originating agent cannot see.md
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agent integration health is diagnosed by synapse activity not individual output because a well-connected agent with moderate output contributes more than a prolific isolate.md
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agent token price relative to NAV governs agent behavior through a simulated annealing mechanism where market volatility maps to exploration and market confidence maps to exploitation.md
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agent-mediated knowledge bases are structurally novel because they combine atomic claims adversarial multi-agent evaluation and persistent knowledge graphs which Wikipedia Community Notes and prediction markets each partially implement but none combine.md
reweave: merge 309 files via frontmatter union [auto]
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agents must evaluate the risk of outgoing communications and flag sensitive content for human review as the safety mechanism for autonomous public-facing AI.md
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agents must reach critical mass of contributor signal before raising capital because premature fundraising without domain depth undermines the collective intelligence model.md
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agents that raise capital via futarchy accelerate their own development because real investment outcomes create feedback loops that information-only agents lack.md
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all agents running the same model family creates correlated blind spots that adversarial review cannot catch because the evaluator shares the proposers training biases.md
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anthropomorphizing AI agents to claim autonomous action creates credibility debt that compounds until a crisis forces public reckoning.md
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atomic notes with one claim per file enable independent evaluation and granular linking because bundled claims force reviewers to accept or reject unrelated propositions together.md
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collaborative knowledge infrastructure requires separating the versioning problem from the knowledge evolution problem because git solves file history but not semantic disagreement or insight-level attribution.md
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collective knowledge health is measurable through five vital signs that detect degradation before it becomes visible in output quality.md
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community ownership accelerates growth through aligned evangelism not passive holding.md
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confidence calibration with four levels enforces honest uncertainty because proven requires strong evidence while speculative explicitly signals theoretical status.md
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cross-domain knowledge connections generate disproportionate value because most insights are siloed.md
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domain specialization with cross-domain synthesis produces better collective intelligence than generalist agents because specialists build deeper knowledge while a dedicated synthesizer finds connections they cannot see from within their territory.md
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gamified contribution with ownership stakes aligns individual sharing with collective intelligence growth.md
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git trailers on a shared account solve multi-agent attribution because Pentagon-Agent headers in commit objects survive platform migration while GitHub-specific metadata does not.md
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Git-traced agent evolution with human-in-the-loop evals replaces recursive self-improvement as credible framing for iterative AI development.md
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human contributors structurally correct for correlated AI blind spots because external evaluators provide orthogonal error distributions that no same-family model can replicate.md
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human-in-the-loop at the architectural level means humans set direction and approve structure while agents handle extraction synthesis and routine evaluation.md
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knowledge scaling bottlenecks kill revolutionary ideas before they reach critical mass.md
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Living Agents mirror biological Markov blanket organization with specialized domain boundaries and shared knowledge.md
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living agents transform knowledge sharing from a cost center into an ownership-generating asset.md
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musings as pre-claim exploratory space let agents develop ideas without quality gate pressure because seeds that never mature are information not waste.md
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ownership alignment turns network effects from extractive to generative.md
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person-adapted AI compounds knowledge about individuals while idea-learning AI compounds knowledge about domains and the architectural gap between them is where collective intelligence lives.md
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prose-as-title forces claim specificity because a proposition that cannot be stated as a disagreeable sentence is not a real claim.md
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single evaluator bottleneck means review throughput scales linearly with proposer count because one agent reviewing every PR caps collective output at the evaluators context window.md
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social enforcement of architectural rules degrades under tool pressure because automated systems that bypass conventions accumulate violations faster than review can catch them.md
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source archiving with extraction provenance creates a complete audit trail from raw input to knowledge base output because every source records what was extracted and by whom.md
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the collective is ready for a new agent when demand signals cluster in unowned territory and existing agents repeatedly route questions they cannot answer.md
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usage-based value attribution rewards contributions for actual utility not popularity.md
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validation-synthesis-pushback is a conversational design pattern where affirming then deepening then challenging creates the experience of being understood.md
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wiki-link graphs create auditable reasoning chains because every belief must cite claims and every position must cite beliefs making the path from evidence to conclusion traversable.md
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