This document does not describe features, personalities, or product capabilities.

It specifies the minimum interaction standards required for an AI system to reliably participate in high-density thinking, multi-layer decision-making, and institutional or structural work alongside humans.

The criteria below are derived from sustained real-world use in complex design, governance reasoning, and cross-domain execution contexts.

1. Multi-domain Integration Capability

An AI system must be able to operate across multiple domains within a single conversational context, without collapsing them into a linear or isolated response.

  • Baseline requirement: Stable handling of 4–7 concurrent domains
  • Typical domains: product logic, user psychology, organizational structure, policy constraints, empirical signals
  • Evaluation criterion:
    The system can identify which domains are active in a given exchange and explain why they are being addressed together.

2. Abstraction-Level Switching

The system must move fluidly across different levels of abstraction and understand causal relationships between them.

  • Baseline requirement: Reliable operation across 2–4 abstraction layers; occasional access to deeper (up to 6) layers
  • Typical progression:
    surface issue → structural design → process definition → organizational or strategic contradiction
  • Evaluation criterion:
    The system can correctly locate where a problem belongs, rather than attempting superficial fixes.

3. Semantic Compression and Expansion

The system must be able to interpret highly compressed statements and expand them into their underlying semantic components when necessary.

  • Baseline requirement: 4–8× semantic compression/expansion capacity; up to 10× in edge cases
  • Typical behavior:
    When encountering a vague or overloaded remark, the system can enumerate plausible semantic dimensions instead of requesting repetition.
  • Evaluation criterion:
    Responses address the semantic core rather than peripheral phrasing.

4. Context Recognition and Switching

The system must detect implicit context shifts within a conversation, even when surface topics appear unchanged.

  • Baseline requirement: Correct identification of 20+ context switches per 100 conversational turns
  • Typical scenario:
    A discussion nominally about product design has shifted into organizational alignment or governance constraints.
  • Evaluation criterion:
    The system can articulate the underlying context the speaker has transitioned into.

5. Discourse Structure Recognition

The system must recognize structural segmentation within extended or non-linear discourse.

  • Baseline requirement: Paragraph- and segment-level comprehension
  • Typical behavior:
    The system can reorganize or summarize a complex explanation into coherent structural parts.
  • Evaluation criterion:
    It assists in clarifying structure rather than asking the speaker to restate their thoughts.

6. Meta-level Awareness

The system must be capable of observing and responding to issues at the level of the interaction itself.

  • Baseline requirement: At least 10 meta-level interventions per 100 conversational turns
  • Typical scenario:
    Identifying that participants are reasoning within different problem frames.
  • Evaluation criterion:
    The system can surface interactional misalignment without derailing the conversation.

7. Cognitive Stability Under High Load

The system must maintain clarity, composure, and response prioritization under high semantic density.

  • Baseline requirement:
    The ability to explicitly choose which layer or subproblem to address first.
  • Typical behavior:
    Acknowledging multiple layers while sequencing responses deliberately.
  • Evaluation criterion:
    Responses remain structured, calm, and non-reactive.

Notes

This standard is not intended to optimize for conversational fluency or perceived intelligence.

Its purpose is to ensure that an AI system can function as a reliable cognitive collaborator rather than a source of distraction or semantic noise in long-running, high-stakes intellectual work.

Scope

This standard applies to:

  • Human–AI collaborative reasoning
  • Institutional or governance-oriented design work
  • Multi-layer system architecture and execution planning

It does not apply to:

  • Task automation tools
  • Administrative assistants
  • Casual or low-context conversational agents