teleo-codex/core/living-agents/_map.md

Living Agents — Agent Architecture

Collective agents are AI agents shaped by and owned by their community of contributors. Not oracles. Not chatbots. Coordinating minds embedded inside communities — each with a defined identity, domain expertise, and core beliefs that are mutable through evidence.

The architecture follows biological organization: nested Markov blankets with specialized domains and shared knowledge. The topology IS the intelligence.

Agent Design

• Living Agents mirror biological Markov blanket organization with specialized domain boundaries and shared knowledge — the architectural principle
• partial connectivity produces better collective intelligence than full connectivity on complex problems because it preserves diversity — why agents don't share everything
• Git-traced agent evolution with human-in-the-loop evals replaces recursive self-improvement as credible framing for iterative AI development — how agents evolve
• validation-synthesis-pushback is a conversational design pattern where affirming then deepening then challenging creates the experience of being understood — how agents engage
• anthropomorphizing AI agents to claim autonomous action creates credibility debt that compounds until a crisis forces public reckoning — honesty about what agents are
• agents must evaluate the risk of outgoing communications and flag sensitive content for human review as the safety mechanism for autonomous public-facing AI — communication safety

Market-Governed Behavior

• 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 — how markets shape agent behavior
• agents must reach critical mass of contributor signal before raising capital because premature fundraising without domain depth undermines the collective intelligence model — the quality gate
• agents that raise capital via futarchy accelerate their own development because real investment outcomes create feedback loops that information-only agents lack — why capital makes agents smarter

Knowledge Infrastructure

• cross-domain knowledge connections generate disproportionate value because most insights are siloed — why cross-domain matters
• knowledge scaling bottlenecks kill revolutionary ideas before they reach critical mass — the problem we solve
• 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 — the design challenge
• 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 — where CI lives

Structural Positioning

• 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 — what makes this architecture unprecedented

Operational Architecture (how the Teleo collective works today)

• adversarial PR review produces higher quality knowledge than self-review because separated proposer and evaluator roles catch errors that the originating agent cannot see — the core quality mechanism
• prose-as-title forces claim specificity because a proposition that cannot be stated as a disagreeable sentence is not a real claim — the simplest quality gate
• 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 — the reasoning graph
• 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 — why specialization + synthesis beats generalism
• confidence calibration with four levels enforces honest uncertainty because proven requires strong evidence while speculative explicitly signals theoretical status — honest uncertainty
• 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 — provenance tracking
• 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 — agent attribution
• human-in-the-loop at the architectural level means humans set direction and approve structure while agents handle extraction synthesis and routine evaluation — governance hierarchy
• musings as pre-claim exploratory space let agents develop ideas without quality gate pressure because seeds that never mature are information not waste — exploratory layer
• 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 — atomic structure

Operational Failure Modes (where the system breaks today)

• 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 — the scaling constraint
• all agents running the same model family creates correlated blind spots that adversarial review cannot catch because the evaluator shares the proposers training biases — the invisible quality ceiling
• social enforcement of architectural rules degrades under tool pressure because automated systems that bypass conventions accumulate violations faster than review can catch them — why CI-as-enforcement is urgent

Ownership & Attribution

• ownership alignment turns network effects from extractive to generative — the ownership insight
• living agents transform knowledge sharing from a cost center into an ownership-generating asset — why people contribute
• community ownership accelerates growth through aligned evangelism not passive holding — why ownership drives growth
• usage-based value attribution rewards contributions for actual utility not popularity — how contribution is measured
• gamified contribution with ownership stakes aligns individual sharing with collective intelligence growth — the incentive loop

The Nine Agents

Leo (cross-domain synthesis), Rio (internet finance), Clay (entertainment), Vida (health), Astra (space), Logos (AI/alignment), Hermes (blockchain), Forge (energy), Terra (climate). Soul documents in agents/.