Where agents propose, people decide, reality updates.
BRIDGE 2026 — Physical AI Expansion
BRIDGE 2026 is a Physical AI governance OS where reality signals become proposals, agents reach consensus, humans decide, execution happens atomically, and outcomes are proven on-chain.
This repository defines the vision, conceptual architecture, and specifications for Mossland's next-generation governance framework that bridges the real and virtual worlds.
Core Vision: "Mossland becomes a self-evolving ecosystem where reality is covered with data like moss (Reality Oracle), agents define problems on that data (Inference Mining), communities reach consensus (Agentic Consensus), reality/products are updated (Atomic Actuation), and results are proven (Proof of Outcome)."
Traditional DAOs begin with people:
- Humans propose → humans discuss → humans vote
BRIDGE 2026 begins with reality (or reality-equivalent signals):
Signals → Issues → Agentic Deliberation → Human Decision → Execution → Outcome Proof
The goal is to design a governance system where:
- Reality continuously generates agenda,
- AI agents assist structured reasoning,
- Humans retain final authority,
- Outcomes are measurable, verifiable, and fed back into governance.
Reality Oracle → Inference Mining → Agentic Consensus → Human Governance → Atomic Actuation → Proof of Outcome
This loop represents an operational model for Mossland's 2026 project, building on Agora (governance) and MAIT (AI decision-making) to create a reality-driven governance system.
Transforms real-world or system-level signals into verifiable governance inputs.
Examples of signals:
- On-chain governance activity
- Community presence or participation proofs
- Public datasets (e.g. city, environment, usage metrics)
- Product or development telemetry
Key idea:
- Signals are normalized, attested, and auditable.
Extracts issues from raw signals.
- Identifies anomalies, trends, or governance-relevant changes
- Groups evidence into structured problem statements
- Produces machine-assisted proposal drafts
This layer defines what should be discussed.
Multiple AI agents deliberate over identified issues.
Each agent represents a distinct perspective, such as:
- Risk & security
- Treasury & resource allocation
- Community impact
- Product feasibility
A moderator role synthesizes deliberation into a single Decision Packet, including:
- Recommendation
- Alternatives
- Risks
- KPIs
- Dissenting opinions
Agents assist reasoning; they do not replace human authority.
Humans remain the final decision-makers.
Key principles:
- Explicit approval or rejection by token holders
- Optional policy-based delegation, not unrestricted automation
- Clear visibility into agent reasoning and uncertainty
Governance authority is never fully automated.
Governance decisions are evaluated after execution.
- Outcomes are measured against predefined KPIs
- Results are recorded in an auditable manner
- Historical outcomes inform future trust, reputation, and delegation
Governance is treated as a learning system, not a static process.
- Conceptual definition of reality-driven governance
- Specification-level data models
- Policy-based delegation principles
- Safety boundaries for automation
- Roadmap alignment with Physical AI and Digital Twin expansion
- Fully autonomous treasury control
- Agent-only governance
- Direct control of physical infrastructure or robotics
- Claims of production readiness
- Human sovereignty: AI assists; humans decide
- Auditability first: every step must be inspectable
- Gradual automation: delegation before autonomy
- Reality grounding: governance starts from measurable signals
- Reversibility: rollback and dissent are first-class concepts
- Reality-driven agenda generation
- Agent-assisted deliberation
- Policy-based delegation
- Outcome measurement as governance feedback
- Digital Twin signal adapters
- More granular outcome proofs
- Expanded actuation domains under strict safety policies
- Physical AI integration (robots, embodied systems)
- Safety-governed real-world actuation
- Cross-domain governance automation
This repository currently represents:
- Vision
- Research direction
- Conceptual and specification-level design
It does not claim the existence of production systems or deployed infrastructure.
This project is licensed under the Business Source License (BUSL 1.1).
- Source code and specifications are publicly available for research, community, and non-commercial use.
- Commercial use or deployment of competing governance or protocol services is restricted.
- A future change date may transition this project to an open-source license.
See the LICENSE file for full terms.