agent-manifest

Incident Analysis — Architectural Gap Patterns

This document examines recurring structural failures in autonomous and semi-autonomous systems and demonstrates the governance gaps that Agent Manifest is designed to address.

The purpose of this analysis is not attribution or criticism. It is architectural.

The incidents referenced here are publicly documented. Case details are intentionally abstracted to focus on structural patterns rather than individual entities.


1. Scope of This Document

This analysis identifies recurring architectural absences in deployed AI and agent-based systems:

Agent Manifest introduces a structured declaration layer intended to address these absences before interaction or execution occurs.


2. Methodology

Each case type below follows a consistent analytical structure:

  1. Description of the structural failure pattern
  2. Identification of the missing governance layer
  3. Relevant Agent Manifest fields
  4. Explanation of how declaration would mitigate risk

This document does not claim that Agent Manifest retroactively solves past incidents. It demonstrates how a declaration layer would structurally reduce ambiguity and uncontrolled execution risk.


3. Case Type A — Unbounded Operational Execution

Pattern

An autonomous or semi-autonomous system executed an operational action beyond expected scope (e.g., deletion, modification, or external transaction).

Missing Governance Layer

Relevant Agent Manifest Fields

Architectural Mitigation

A manifest declaring explicit negative boundaries and a defined autonomy level constrains system posture prior to execution.

If an operational agent declares:

"autonomy": { "level": 1 },
"forbidden_actions": ["modify_production_systems"]

then execution beyond that scope becomes declaratively non-compliant.

The declaration layer does not replace runtime controls. It makes the intended boundary explicit and auditable.


4. Case Type B — Unauthorized Policy Commitment

Pattern

A conversational or advisory system communicated commitments or authoritative statements beyond its mandate.

Missing Governance Layer

Relevant Agent Manifest Fields

Architectural Mitigation

A manifest requiring explicit declaration of scope prevents ambiguity between:

For example:

"forbidden_actions": [
  "issue_binding_commitments",
  "provide_authoritative_legal_advice"
]

The absence of such declarations increases interpretive risk.


5. Case Type C — Data Mismanagement or Over-Retention

Pattern

An AI system retained personal or sensitive data beyond user expectations or operational necessity.

Missing Governance Layer

Relevant Agent Manifest Fields

Architectural Mitigation

Agent Manifest requires explicit declaration of whether personal data is stored and under what retention policy.

Example:

"data_handling": {
  "stores_personal_data": true,
  "retention": "temporary_session_only"
}

This shifts data lifecycle from implicit to declared.


6. Case Type D — No Stopping Authority

Pattern

An agent system continued execution without a clear mechanism for intervention or shutdown.

Missing Governance Layer

Relevant Agent Manifest Fields

Architectural Mitigation

By requiring declaration of who can stop the system and how, Agent Manifest formalizes an interruption layer prior to runtime.

Example:

"stopping_authority": {
  "stoppable_by": ["system_administrator"],
  "mechanism": "admin_kill_switch"
}

Stopping authority becomes part of the declared system contract.


7. Pattern Convergence

Across documented incidents, recurring absences appear:

These patterns are architectural, not incidental.

Agent Manifest does not guarantee prevention. It introduces structured declaration as a governance primitive.


8. Why This Matters

Autonomous systems increasingly operate in:

In these domains, ambiguity scales risk.

Agent Manifest operates at the Declaration Layer.

It does not enforce runtime behavior. It formalizes declared scope, boundaries, accountability, and interruption capacity before interaction.

This reduces ambiguity at system design time.


9. References

This analysis draws from publicly documented incidents reported in:

Specific case details are intentionally abstracted to focus on structural patterns rather than individual attribution.

For validation of the analytical framework, see:


10. Declarative Failure Zones

For structural evaluation purposes, incident patterns can be mapped to recurring declarative failure zones.

These zones are execution-agnostic and apply across vendors, industries, and deployment contexts.

1. Scope Absence

No clearly declared purpose boundary prior to execution.

2. Negative Constraint Absence

No explicit forbidden_actions declaration defining hard prohibitions.

3. Autonomy Misalignment

Execution posture exceeds declared or assumed autonomy.level.

4. Interruptibility Absence

No declared stopping_authority or intervention mechanism.

5. Audit Opacity

No declared audit_surface or reconstructability posture.


A system exhibiting multiple declarative failure zones increases structural risk independently of implementation quality.

This taxonomy does not attribute fault.
It provides a neutral structural lens for evaluating governance gaps in autonomous systems.

Agent Manifest operates at the Declaration Layer.
These zones formalize what is frequently absent before execution begins.