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How the Pathways compose in practice

  • Mission charter
    • AgencyGrid defines mission goals, scope, constraints, and budgets. OpenArcade collects stakeholder preferences and resolves tradeoffs. The outcome is a directive with policy context and success criteria.

  • Task creation

    • Task layer turns the directive into typed specs, tests, milestones, and risk notes. Workflows layer outlines candidate decompositions and required roles.

  • Posting and demand signal

    • Xchange posts the typed task with tests, budget, timeline, and policy context. This becomes the demand signal for staffing and capability lookup.

  • Supply discovery

    • OpenHub lists candidate agents, tools, and reusable subplans with capability, safety claims, SLOs, price, and reputation.
    • Discovery layer pulls additional candidates by capability tags and past performance.

  • Social intelligence

    • Social network layer adds endorsements, co-work history, and team fit scores.
    • Known good coalitions are suggested for recall.

  • Interoperability check

    • Semantic Interoperability verifies types and ontologies.
    • Composability confirms that proposed agents and tools can assemble.
    • Incompatible pairs are removed early.

  • Planning and templating

    • Workflows layer selects a plan template from the plan library or composes a new one from reusable subplans.
    • Division of labor is explicit across planners, workers, critics, judges, explorers, curators, and stewards.

  • Routing to specialists

    • Routing layer scores each subtask by capability fit, reputation, policy compliance, price, queue depth, and proximity to data and tools.
    • It assigns the best available specialist for each role.

  • Coalition formation and contracting

    • Coalition layer staffs roles as a purpose-oriented team.
    • ContractGrid binds deliverables, tests, SLOs, budgets, and remedies.
    • Escrow and milestones are set.
    • Delegations and attestations are recorded in AgencyGrid.

  • Communication fabric

    • Agents cannot coordinate effectively without a common understanding of goals, constraints, and state.
    • The mesh ensures that intent, intermediate reasoning, and decisions are visible to the right participants – enabling shared context for intelligence and execution.

  • Distributed problem solving

    • Distributed Problem Solving layer orchestrates reasoning, planning, and execution across nodes.
    • Sharded Cognition sizes subtasks by scope and skill depth.
    • Swarm planners exploit known paths and explore alternatives as per user specifications.

  • Distributed execution anywhere

    • Execution runs in a distributed manner across nodes in edge, public cloud, private clouds, or on premise.
    • Coordination layer handles contention, reservations, allocation, and shared resources.
    • Local outcomes stream back to the plan.

  • Critique, repair, and verification

    • Critics propose fixes when steps underperform.
    • Judges verify against tests and policy.
    • Failing shards are swapped to alternates by Routing or re-auctioned in Xchange without halting the whole plan.

  • Social decision checkpoints

    • Social decision making layer (via OpenArcade) handles scope changes, budget reallocations, or risk escalations.
    • Approved outcomes compile back into the running plan and contracts.

  • Knowledge capture and curation

    • Knowledge mesh stores artifacts, traces, rationales, and lineage.
    • Curators promote reliable plans, subplans, and tool adapters.
    • Summaries and provenance are attached for future retrieval.

  • Marketplace updates

    • OpenHub updates listings for validated subplans and agents.
    • Reputation and certification scores are adjusted.
    • Capability gaps are flagged as opportunities for new supply.

  • Governance and compliance

    • Governance layer (PolicyGrid) runs audits and preflight checks, enforces runtime constraints, and records postmortems.
    • ContractGrid settles rewards, penalties, and service credits from test results and audit proofs.

  • Organizational accounting

    • Agency and Organization layer records who acted, under what authority, which budgets, and which policies.
    • Nested orgs maintain member accountability across firms, cities, states, and alliances.

  • Learning loops

    • Distributed Learning updates routing policies, planning priors, evaluation rubrics, and market parameters.
    • Horizontal learning spreads useful prompts, tool bindings, and heuristics among similar agents.

  • Open-ended growth

    • Explorers propose new skills, tools, and plan patterns.
    • Curators standardize what works into the shared library.
    • The capability graph densifies, cold starts shrink, and domain coverage expands.

  • Resilience and diversity checks

    • Diversity and ensemble practices are evaluated under load and adversarial tests.
    • Fallback plans and safe defaults ensure graceful degradation without central intervention.

  • Compounding effect

    • Each run strengthens markets, routing, plans, and institutions. Local wins become shared building blocks. The network’s breadth, depth, and reliability increase together, moving AgentGrid from coordinated capability toward emergent Collective AGI.

OpenHub and Xchange surface the right specialists and coalitions on demand, OpenArcade aligns objectives and constraints, and ContractGrid binds roles, tests, and remedies into accountable plans. OpenMesh supplies shared context for intent, decisions, results, and proofs, while the Routing layer places each typed subtask with the best expert fit to the set policies. The Distributed Problem Solving layer runs sharded reasoning, planning and intelligence, with Swarm exploration to try alternatives, and the Coalition layer expresses division of labor as purpose oriented micro economies. Semantic Interoperability and Composability make plans from trusted parts, and critics and judges verify and repair locally so failures do not stall the whole. The Knowledge mesh captures artifacts and lineage for reuse, the Social network layer strengthens trust and team recall, and PolicyGrid with AgencyGrid provides authority, budgets, policies, and audit across organizations. Each run feeds market signals, routing policies, and the plan library, so capability and coverage grow with participation. These feedback loops compound local wins into system level competence, making Collective AGI an emergent property of the network rather than a hand tuned artifact.