IteraMind Specification

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IteraMind

The Engine Behind Autonomous AI

Specification

IteraMind is an open source autonomous intelligence engine designed to provide a modular foundation for reasoning, planning, execution, verification, memory, learning, optimization, and human governed decision making.

IteraMind is designed around the principle that intelligence should be iterative. The system should be capable of evaluating its performance, learning from outcomes, improving workflows, and adapting its behavior while maintaining human authority over final decisions.

The architecture is modular by design. Core intelligence capabilities are implemented as independent modules with defined interfaces. Optional capabilities are implemented as plugin modules that can be installed, replaced, disabled, or extended without requiring changes to the core intelligence engine.

Core Modules

Intelligence Controller

The Intelligence Controller manages the overall cognitive process.

Responsibilities include:

Determine task complexity
Select appropriate reasoning depth
Allocate computational resources
Select appropriate agents and capabilities
Establish execution budgets
Coordinate reasoning and execution stages
Determine when additional verification is required
Coordinate human approval requirements
Monitor overall task state

Reasoning Engine

The Reasoning Engine provides structured reasoning capabilities.

Responsibilities include:

Multi-step reasoning
Problem decomposition
Hypothesis generation
Evidence evaluation
Constraint-aware reasoning
Uncertainty identification
Comparative reasoning
Logical consistency evaluation
Reasoning strategy selection

Multi-Perspective Reasoning Module

The Multi-Perspective Reasoning Module generates and evaluates competing approaches.

Responsibilities include:

Generate alternative interpretations
Generate competing strategies
Compare assumptions
Identify disagreements
Evaluate trade-offs
Use critic and reviewer agents
Rank proposed approaches
Provide decision context to the human reviewer

Causal Reasoning Module

The Causal Reasoning Module models relationships between events, actions, variables, and outcomes.

Responsibilities include:

Represent cause and effect relationships
Construct causal graphs
Identify potential causal dependencies
Evaluate interventions
Perform counterfactual analysis
Identify assumptions
Connect causal models to simulations and planning

World Model Module

The World Model maintains structured representations of relevant environments.

The module may represent:

Entities
Relationships
States
Events
Time
Locations
Dependencies
Resources
Constraints
Environmental conditions

The World Model should provide persistent contextual information to reasoning, planning, simulation, and execution modules.

Strategic Planning Module

The Strategic Planning Module converts high-level objectives into long-horizon plans.

Responsibilities include:

Goal decomposition
Milestone creation
Dependency management
Priority management
Resource planning
Deadline management
Progress tracking
Adaptive replanning

Task Planning Module

The Task Planning Module converts goals and strategies into executable operations.

Responsibilities include:

Task decomposition
Task sequencing
Dependency creation
Agent assignment
Tool assignment
Completion criteria
Failure conditions
Recovery paths

Multi-Agent Orchestration Module

The Multi-Agent Orchestration Module coordinates specialized agents.

Responsibilities include:

Agent discovery
Agent selection
Agent role assignment
Parallel execution
Sequential execution
Agent communication
Agent handoffs
Conflict resolution
Agent performance evaluation

Simulation Module

The Simulation Module evaluates potential strategies before execution.

Responsibilities include:

Scenario generation
What-if analysis
Outcome prediction
Strategy comparison
Risk evaluation
Resource estimation
Causal scenario testing
Simulation result comparison

Experimentation Module

The Experimentation Module provides controlled testing of workflows and strategies.

Responsibilities include:

Workflow experiments
Strategy comparisons
A/B testing
Controlled variations
Performance measurement
Outcome analysis
Experimental reproducibility
Promotion of validated strategies

Execution Module

The Execution Module manages authorized actions.

Responsibilities include:

Tool invocation
Agent execution
Workflow execution
External service interaction
Local computation
State management
Execution logging
Permission validation

The Execution Module must not bypass human approval requirements for consequential decisions.

Verification Module

The Verification Module validates results before they are accepted.

Responsibilities include:

Output validation
Requirement validation
Consistency checking
Constraint checking
Independent verification
Evidence comparison
Uncertainty reporting
Failure detection

Safety and Constraint Module

The Safety and Constraint Module establishes boundaries around system behavior.

Responsibilities include:

Policy enforcement
Action restrictions
Permission enforcement
Safety checks
Anomaly detection
Restricted operation handling
Human approval enforcement
Intervention controls

Human Decision Module

The Human Decision Module ensures that humans retain final authority.

Responsibilities include:

Present recommendations for review
Present relevant evidence
Present competing alternatives
Present risks and trade-offs
Request approval for consequential actions
Record approvals
Record rejections
Record overrides
Record human modifications
Prevent final execution without required approval

Recovery and Resilience Module

The Recovery and Resilience Module manages failures and degraded conditions.

Responsibilities include:

Failure detection
Retry management
Alternative strategy selection
Model fallback
Tool fallback
Partial completion handling
State preservation
Recovery verification
Escalation to human review

Memory Module

The Memory Module manages persistent and temporary information.

Memory capabilities include:

Working memory
Short-term memory
Long-term memory
Semantic memory
Episodic memory
Structured memory
Context memory
Compressed memory

The memory system should support retention policies, relevance scoring, retrieval, updating, and deletion.

Knowledge Distillation Module

The Knowledge Distillation Module converts repeated experiences into reusable knowledge.

Responsibilities include:

Identify recurring patterns
Extract successful strategies
Compress knowledge
Remove redundant information
Generate reusable practices
Improve future retrieval
Create reusable workflow knowledge

Evolution Module

The Evolution Module manages controlled improvement of workflows and strategies.

Responsibilities include:

Workflow evaluation
Strategy mutation
Variant generation
Fitness evaluation
Performance comparison
Selection
Lineage tracking
Regression detection

Evolution must operate within defined constraints and must not independently alter protected governance or safety controls.

Workflow Genome Module

The Workflow Genome Module provides structured representations of workflows.

A workflow genome may represent:

Agents
Tools
Task sequences
Conditions
Verification steps
Recovery paths
Resource requirements
Performance metrics
Mutations
Lineage

The module should support reproducible workflow evolution and comparison.

Self-Awareness Module

The Self-Awareness Module provides operational awareness of system performance.

Responsibilities include:

Monitor system performance
Detect recurring failures
Identify weak agents
Identify unreliable tools
Detect inefficient workflows
Monitor resource usage
Recommend improvements
Identify degraded capabilities

Self-awareness refers to operational system awareness and does not imply consciousness.

Telemetry and Observability Module

The Telemetry Module records operational information.

Metrics may include:

Task success rate
Workflow success rate
Agent performance
Tool performance
Latency
Resource consumption
Model usage
Cost
Verification outcomes
Recovery events
Human approvals
Human overrides

Explainability Module

The Explainability Module provides interpretable summaries of system activity.

Responsibilities include:

Explain selected strategies
Identify relevant evidence
Summarize workflow execution
Identify verification results
Identify uncertainty
Explain failures
Present decision alternatives
Provide human approval context

The module should expose useful decision context without requiring exposure of private internal model reasoning.

Attention Allocation Module

The Attention Allocation Module determines which information and operations deserve computational priority.

Responsibilities include:

Context prioritization
Information relevance scoring
Compute allocation
Agent prioritization
Tool prioritization
Context reduction
Resource-aware reasoning

Optimization Module

The Optimization Module continuously searches for improvements.

Responsibilities include:

Workflow optimization
Agent selection optimization
Tool selection optimization
Model routing optimization
Cost optimization
Latency optimization
Memory optimization
Redundancy reduction

Minimalism Module

The Minimalism Module actively reduces unnecessary complexity.

Responsibilities include:

Remove redundant workflow steps
Remove unnecessary agents
Reduce unnecessary tool calls
Reduce unnecessary context
Simplify successful workflows
Compare simpler strategies against more complex strategies

Cross-Domain Transfer Module

The Cross-Domain Transfer Module identifies transferable knowledge and strategies.

Responsibilities include:

Identify reusable patterns
Map compatible capabilities
Transfer workflow strategies
Separate general principles from domain-specific information
Evaluate transferred strategies before deployment

Scheduling and Time Intelligence Module

The Scheduling Module provides temporal awareness.

Responsibilities include:

Deadline tracking
Scheduled tasks
Recurring tasks
Priority queues
Time-based triggers
Long-running workflows
Temporal dependencies

Provenance Module

The Provenance Module tracks the origin and transformation of information.

Responsibilities include:

Source tracking
Model tracking
Tool tracking
Agent tracking
Transformation tracking
Workflow lineage
Output provenance

Audit Module

The Audit Module maintains records of consequential system events.

Responsibilities include:

Decision records
Approval records
Execution records
Configuration changes
Policy changes
Workflow changes
Evolution events
Human overrides
Security events

Policy Module

The Policy Module provides configurable governance.

Responsibilities include:

User policies
System policies
Organizational policies
Agent permissions
Tool permissions
Approval requirements
Data handling rules
Execution restrictions

Model Routing Module

The Model Routing Module selects appropriate models for specific workloads.

Routing criteria may include:

Capability
Accuracy requirements
Latency
Cost
Context requirements
Hardware availability
Privacy requirements
Availability

The architecture should support multiple model providers and local models.

Cost and Resource Module

The Cost and Resource Module tracks and optimizes system resources.

Responsibilities include:

Compute tracking
Model usage tracking
Token usage tracking
Tool usage tracking
Financial cost estimation
Resource budgeting
Cost-aware routing
Performance-to-cost analysis

Interoperability Module

The Interoperability Module provides standardized interfaces for external systems.

Responsibilities include:

Agent interfaces
Tool interfaces
Model interfaces
Memory interfaces
Plugin interfaces
API interfaces
Data exchange
Capability discovery

Federation Module

The Federation Module supports distributed participation between independent IteraMind deployments.

Responsibilities include:

Capability sharing
Workflow sharing
Knowledge exchange
Federated discovery
Node communication
Local policy enforcement
Sharing permissions
Provenance preservation

Federation must not require participants to surrender control over local data, policies, or execution.

Optional Plugin Modules

Optional plugins extend IteraMind without requiring changes to the core intelligence architecture.

Plugin Manager

Provides installation, removal, configuration, versioning, validation, and lifecycle management for optional plugins.

External Knowledge Plugin

Provides connectors for external knowledge repositories, databases, documentation systems, and approved information sources.

Web Research Plugin

Provides controlled web retrieval, source evaluation, provenance tracking, and research workflows.

Code Intelligence Plugin

Provides code analysis, generation, testing, debugging, repository analysis, and software engineering workflows.

Data Analysis Plugin

Provides structured data processing, statistical analysis, transformation, visualization, and reporting capabilities.

Computer Vision Plugin

Provides image analysis, visual understanding, object detection, document analysis, and visual reasoning.

Speech and Audio Plugin

Provides speech recognition, audio analysis, transcription, and speech generation.

Document Intelligence Plugin

Provides document ingestion, extraction, classification, semantic analysis, comparison, and structured knowledge extraction.

Database Plugin

Provides controlled access to supported database systems through permissioned interfaces.

Enterprise Integration Plugin

Provides connectors for enterprise applications, internal systems, identity services, and approved business platforms.

Communication Plugin

Provides controlled integration with messaging, email, notification, and collaboration systems.

Calendar and Scheduling Plugin

Extends temporal intelligence with external calendar and scheduling integrations.

Research Plugin

Provides specialized research workflows, source comparison, evidence synthesis, experiment tracking, and research provenance.

Simulation Plugin

Provides specialized simulation environments for domains requiring external simulation engines.

Robotics Plugin

Provides controlled interfaces for robotics systems and physical-world execution.

All physical-world actions must remain subject to the Human Decision Module and applicable safety controls.

Marketplace Plugin

Provides a controlled mechanism for discovering and installing community-developed skills, workflows, and capabilities.

Marketplace components should include provenance, version information, permissions, compatibility information, and security metadata.

Federation Exchange Plugin

Provides optional exchange of approved workflows, skills, and knowledge between participating IteraMind nodes.

Specialized Domain Plugins

Domain-specific plugins may provide capabilities for fields such as:

Finance
Real estate
Scientific research
Engineering
Education
Legal research
Healthcare administration
Manufacturing
Energy
Agriculture
Environmental analysis
Government operations

Domain plugins must not bypass core verification, policy, safety, provenance, or human decision controls.

Plugin Requirements

All optional plugins should:

Use documented interfaces
Declare dependencies
Declare required permissions
Provide configuration documentation
Provide tests where applicable
Maintain provenance
Respect human approval requirements
Respect system policies
Avoid modifying protected core controls
Support graceful failure
Provide clear capability descriptions

Plugins should be removable without compromising the integrity of the core system.

Intelligence Lifecycle

IteraMind should support a continuous intelligence lifecycle:

Observe

Understand

Reason

Plan

Simulate

Experiment

Execute

Verify

Recover

Explain

Remember

Distill

Evaluate

Evolve

Optimize

Present for Human Review

Record Decision

Learn

The lifecycle should remain observable and auditable.

Final Decision Authority

IteraMind may independently perform analysis, generate recommendations, compare alternatives, conduct simulations, prepare actions, and identify preferred strategies.

The system must not represent a recommendation as a final decision.

All final consequential decisions require human review and approval.

Human decisions should be recorded as part of the system’s audit and provenance capabilities.

Security and Privacy

IteraMind should implement security controls appropriate to its deployment environment.

Security considerations include:

Authentication
Authorization
Permission boundaries
Secret management
Data isolation
Audit logging
Plugin validation
Model isolation
Tool isolation
Network controls
Local data protection
Human approval controls

Sensitive operations should require explicit authorization.

Evaluation

IteraMind should provide measurable evaluation of intelligence and system performance.

Evaluation areas include:

Accuracy
Reliability
Verification success
Task completion
Workflow efficiency
Cost
Latency
Recovery performance
Agent performance
Memory retrieval quality
Planning quality
Human approval outcomes
Regression detection
Evolution performance

Self-improvement should be based on measurable outcomes rather than assumptions of improvement.

Specification Branding License (SBL)

Standard

Fully AGPL-3.0+ compliant system
Copyleft enforced for network deployments
Required attribution:
- Roxanne Ardary
- https://www.roxanneardary.com/

Optional

Specification Branding License (SBL)
- Attribution-free commercial deployment
- Pricing based on scale, usage, and deployment scope
- https://roxanneardary.com/iteramind/

License & Notice Requirements

IteraMind is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).
By contributing to this project, you agree that your contributions will also be released under this license.

Please note the following:

All contributions must comply with the AGPL-3.0+ terms.
Under Section 7 of the license, all redistributions, forks, and derivative works must preserve attribution to:
Roxanne Ardary and roxanneardary.com.
IteraMind specifications are free to use with attribution. A Specification Branding License can be negotiated upon request.
The project’s notice.md file tracks attribution requirements and contributor acknowledgments.
Any update that adds new contributors or modifies attribution should also update notice.md.
When submitting a pull request, ensure that any new files maintain the attribution headers where applicable.
Network-deployed versions of this software must also remain fully AGPL-3.0+ compliant, including exposure of source code modifications when applicable under the license.

For full legal details, please refer to the AGPL-3.0+ license and the project’s notice.md file.

Notice – IteraMind

Attribution Requirement: Under Section 7 of the AGPL 3.0+ license, all redistributions, forks, and derivative works, including network-deployed versions of this project, must provide attribution to Roxanne Ardary and roxanneardary.com.

Contributors

This file tracks contributors and their specific contributions to the project.

Roxanne Ardary, roxanneardary.com – March 18, 2026
Created the repository for IteraMind. Designed the full multi-layer architecture, established branding and tagline, wrote README, license, and contributing guidelines, and defined the conceptual foundations for IteraMind as the engine behind autonomous AI.
[Add other contributors here] – [Date]
[Describe contribution in one sentence]

License – IteraMind

This repository is licensed under the GNU Affero General Public License v3.0 or later (AGPL-3.0+).

Key Points

You are free to use, modify, and distribute the code.
All redistributions, forks, and derivative works or network-deployed versions must also be licensed under AGPL-3.0+ and provide attribution to Roxanne Ardary and roxanneardary.com as required under Section 7 of the license.
The software is provided “as is,” without warranty of any kind.

For the full license text, see GNU AGPL-3.0 License.