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Execution Engine

Executive Summary

The Execution Engine defines the business behaviour by which AIOS converts intent into planned, delegated, monitored, approved, recorded, and auditable work. It describes enterprise execution behaviour, not a software engine implementation.

Why This Exists

Define the business execution engine that converts intent into governed work without describing implementation code. AIOS exists because Algosure is not tender software. Algosure gives each customer a Digital Procurement Company made up of Practices, Digital Professionals, Business Capabilities, SOPs, Organizational Memory, AI reasoning, executable workflows, and continuous learning. The operating model is required so those assets work as one accountable enterprise system.

Owner

The owner is the Chief Product Officer and Enterprise Architect. The Executive Office is the orchestration entry point. Ari acts as Chief Procurement Officer for cross-Practice coordination. Ava supports executive administration, schedules, reminders, approvals, and governance cadence. Intelligence provides the orchestration engine.

Business Value

Creates dependable operating behaviour for task planning, monitoring, approval, retry, failure handling, and closure.

Scope

  • Execution states.
  • Retry model.
  • Failure handling.
  • Approval wait states.
  • Outcome recording.
  • Memory review.

Non-Scope

  • Spring Boot implementation details.
  • API specifications or endpoint design.
  • Database schema design.
  • Model provider selection or runtime infrastructure.
  • Reassignment of Domain fact ownership.
  • Autonomous high-impact decisions without human approval.

Operating Model

stateDiagram-v2
    [*] --> Requested
    Requested --> Classified
    Classified --> ContextAssembled
    ContextAssembled --> Planned
    Planned --> Delegated
    Delegated --> Executing
    Executing --> WaitingForApproval
    WaitingForApproval --> Approved
    WaitingForApproval --> RevisionRequested
    RevisionRequested --> Executing
    Approved --> OutcomeRecorded
    OutcomeRecorded --> MemoryReviewed
    MemoryReviewed --> Completed
    Executing --> Failed
    Failed --> Retrying
    Retrying --> Executing
    Failed --> Escalated
    Completed --> [*]

Architectural Principles

Principle Operating Meaning
Domains own business facts AIOS may request, interpret, route, and explain work, but source facts remain owned by the appropriate Domain.
Practices own operational capability Practices define repeatable work, SOPs, KPIs, meetings, reports, and performance accountability.
Digital Professionals execute work Digital Professionals perform governed work within assigned role, authority, memory scope, tools, and guardrails.
AIOS orchestrates work AIOS coordinates intent, context, reasoning, delegation, execution, approvals, events, memory, and audit trails.
Humans remain accountable Strategic, financial, legal, compliance-sensitive, external, and irreversible decisions require human accountability.
Every action is auditable Requests, context, reasoning, decisions, approvals, actions, failures, retries, and outcomes must be traceable.
Every recommendation is explainable Recommendations must include evidence, rationale, assumptions, alternatives, risk, confidence, and approval need.
High-impact decisions support approval AIOS prepares high-impact actions for review and blocks execution until authorized approval is recorded.

AIOS does not replace the Domain Model, Practice Model, Business Capability Catalogue, or Digital Professional standards. It coordinates them into one enterprise operating behaviour.

Ownership Boundaries

Layer Owns Does Not Own
Domain Business facts, lifecycle state, rules, commands, and domain events Practice operating cadence or AI workforce structure
Practice Capabilities, SOPs, KPIs, meetings, reports, and operational accountability Source facts owned by Domains
Digital Professional Analysis, preparation, recommendations, collaboration, execution support, and role-specific memory use Final source truth or high-impact decisions
AIOS Orchestration, context assembly, delegation, approval routing, event coordination, memory update workflow, and audit coordination Source facts, API specifications, implementation design, or unbounded autonomy
Human Accountability, final approval, strategic judgement, exception handling, and risk acceptance Routine machine coordination that can be governed safely

Operating Behaviour

Step AIOS Behaviour
Requested A business request, event, schedule, or risk signal creates work.
Planned AIOS selects dependencies, sequence, tools, guardrails, and approval gates.
Executing Professionals perform work within authority and record progress.
Approval High-impact outputs wait for human decision.
Outcome Approved outcomes are recorded through the correct owning workflow.
Failure handling Failures trigger retry, revision, or escalation according to type.

Operating Artefacts

Artefact Purpose
Work intent The business request, event, schedule, or risk signal that starts AIOS coordination.
Work packet The scoped context, task, authority, SOP, expected output, and guardrails given to a Digital Professional.
Evidence bundle Domain facts, documents, events, approved memory, assumptions, and confidence inputs used for reasoning.
Decision record Human or policy decision with approver, timestamp, scope, rationale, and outcome.
Audit trail Traceable record of material requests, context, reasoning, actions, approvals, failures, and outcomes.
Memory update proposal Proposed durable learning with provenance, source owner, confidence, and review status.

Controls

Control Requirement
Tenant isolation Customer context, memory, events, and decisions must remain inside the authorized tenant boundary.
Authority control Digital Professionals can act only within documented role authority and approval limits.
Source ownership AIOS cannot create shadow truth or override Domain-owned facts.
Human approval High-impact decisions must be routed to authorized humans before action.
Audit trail Material work must preserve request, context, reasoning, decision, action, and outcome.
Explainability Recommendations must show evidence, rationale, assumptions, alternatives, confidence, and risk.
Memory governance Durable memory updates require provenance and review when material.
Failure handling Failures must be recorded, assessed, retried only when safe, or escalated.

Human Accountability

AIOS may prepare analysis, generate drafts, coordinate work, summarize evidence, recommend action, and execute approved low-risk tasks. High-impact actions require explicit human approval. Human accountability cannot be hidden inside automation, delegated to a Digital Professional, or implied by AI confidence.

Failure, Retry, and Escalation

Condition Required Response
Missing authoritative context Stop material action, request source evidence, or route to owning Domain.
Low confidence Explain uncertainty and route for review or more evidence.
Tool or workflow failure Retry only within controlled limits and escalate when deadline or impact risk exists.
Ownership conflict Stop execution and route to the owning Domain or Practice governance path.
High-impact consequence Prepare approval package and wait for authorized human decision.
Repeated failure Escalate to AI Governance and Practice retrospective.

Success Measures

Measure Meaning
Cycle time Time from intake to closed outcome.
Approval latency Time waiting for human review when required.
Escalation rate Frequency of low-confidence, blocked, or high-impact escalations.
Audit completeness Percentage of material work with complete traceability.
Confidence calibration Alignment between confidence scores and observed outcomes.
Rework rate Frequency of revisions, rejected outputs, or repeat analysis.

Examples

Scenario AIOS Behaviour
Retry AIOS retries a failed notification delivery within limits but escalates if a submission deadline is affected.
Blocked action AIOS blocks external submission until required human approval is recorded.

Operating Standard

Any future implementation must preserve this operating behaviour. Implementation choices may change, but the enterprise rules remain stable: business first, technology second; One Concept, One Owner; Architecture Mirror Principle; auditable execution; explainable recommendation; and human accountability for high-impact decisions.