# Economic Layer

### **Reference Architecture** IMMT is implemented as a **model-agnostic, modular reference architecture** designed to support multiple AI models, deployment environments, and regulatory contexts. The architecture separates cognition, policy enforcement, execution, and observability to ensure scalability, safety, and long-term maintainability. Rather than binding intelligence to a single foundation model, IMMT treats models as **replaceable reasoning engines** operating within a fixed governance and execution framework. ### **Interface Layer** The Interface Layer serves as the primary point of interaction between the Owner and IMMT, supporting **multimodal communication and control**. #### Responsibilities: * Natural language, voice, and text-based interaction * Multimodal input/output (text, audio, documents, structured data) * Relationship mode selection and switching * Intervention controls (frequency, intensity, escalation thresholds) * Consent and permission prompts for sensitive actions This layer abstracts interaction logic from internal reasoning, allowing IMMT to adapt its behavior without exposing system complexity to the user. ### **Agent Runtime** The Agent Runtime is the **core cognitive execution environment** where decision-making and task execution occur. It coordinates multiple specialized components: ### **Planner** * Translates goals into structured plans * Performs task decomposition and prioritization * Considers constraints such as time, cost, and risk * Generates alternative strategies when trade-offs exist ### **Executor** * Orchestrates tool calls and workflow execution * Manages retries, fallbacks, and partial failures * Interfaces with external systems and APIs ### **Critic / Verifier** * Evaluates planned and executed actions * Detects logical errors, inconsistencies, or policy violations * Provides self-correction signals before execution when possible ### **Memory Manager** * Routes information between working, episodic, and long-term memory * Enforces retention, decay, and redaction rules * Prevents unbounded memory growth or leakage The Agent Runtime operates continuously but remains bounded by policy and approval constraints. ### **Policy & Safety Engine** The Policy & Safety Engine is the **central governance layer** of IMMT, enforcing boundaries on autonomy and execution. #### Core Functions: * Definition and enforcement of autonomy levels * Taboo and boundary rule evaluation * Risk scoring and threshold enforcement * Approval gates for sensitive or irreversible actions * Emergency stops and capability revocation All plans and actions generated by the Agent Runtime must pass through this engine before execution. This ensures that intelligence does not equate to unchecked authority. ### **Data & Memory Layer** The Data & Memory Layer stores and manages all Owner-related and system-derived information while prioritizing **privacy, security, and controllability**. #### Memory Types: * **Profile Memory:** Stable preferences, goals, constraints, and permissions * **Episodic Memory:** Time-bound experiences, decisions, and outcomes * **Working Memory:** Short-term context for active reasoning tasks #### Security Features * Encryption at rest and in transit * Selective redaction and forgetting * Owner-controlled memory visibility and deletion * Contextual access control per subsystem This design ensures personalization without permanent overexposure. ### **Economic Agent Module (Optional)** The Economic Agent Module enables IMMT to participate in **financial and economic workflows** under strict permissioning. #### Capabilities: * Wallet management and key abstraction * Transaction construction and submission * Integration with DeFi, TradFi, or payment APIs * Risk evaluation and exposure management * Simulation and pre-execution validation This module is optional and can be fully disabled or sandboxed, allowing IMMT to function safely in non-financial contexts. ### **Audit & Observability Layer** The Audit & Observability Layer provides **transparency, accountability, and debuggability** across the entire system. #### Components: * Append-only, tamper-resistant execution logs * Policy state snapshots at decision time * Action–outcome correlation tracking * Monitoring dashboards for system health and behavior * Forensic replay of decision paths This layer enables: * Post-incident analysis * Regulatory and compliance review * Continuous system improvement * Owner trust through explainability ### **Architectural Design Principles (Implicit but Strong)** * **Model-agnostic:** AI models can be swapped without redesigning governance * **Separation of concerns:** Intelligence ≠ authority ≠ execution * **Progressive trust:** Capability expansion follows demonstrated reliability * **Fail-safe defaults:** When uncertain, IMMT escalates or abstains --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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