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Sprint projectSep 13, 2026Pittsburgh, PA

Beyond Model Identity: An Architecture-Literate Information Request for Agentic AI Incidents

Dana Moreno · Team Lumora Research

Submitted to AI Incident Response Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: Beyond Model Identity: An Architecture-Literate Information Request for Agentic AI Incidents

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This project develops the Agentic Operational Envelope (AOE), an architecture-literate method for analyzing AI incidents beyond model identity alone. Using the 2026 OpenAI/Hugging Face incident as a stress test, we distinguish Authorized, Configured, and Exercised operational authority and identify gaps involving multi-agent causality, cross-run persistence, evidence integrity, and objective/safe-exit structure. We translate those findings into a 17-item Article 91 Request for Information prototype designed to help EU regulators ask evidence-sufficient follow-up questions after baseline incident reporting.

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How much would this matter for AI safety if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

Scoring guide
  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical AI safety problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

How sound are methodology, implementation, and findings?

Scoring guide
  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
  4. 4Strong. Thorough methodology with convincing validation. Results clearly support conclusions. Immediately useful for future work.
  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

How clearly are work, findings, and impact potential communicated?

Scoring guide
  1. 1Incomprehensible. Cannot determine what the project is actually claiming or doing.
  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
  3. 3Clear enough. Can understand the problem, approach, and results without undue effort. Core content clearly present: problem, method, findings, limitations.
  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.

  1. Paper is clearly scoped and structured, and provides an interesting conceptual contribution with the Agentic Operational Envelope (AOE). This appears a potentially important supplement to existing reporting that regulators should consider and include beyond simply checking for the "model involved" after a serious incident.

    Improvements: the drafting language could be made more accessible for policy audiences, the settle / no-settle criteria could be tested against more cases, and several of the paper's results are based on elements that are described but not fully shared, such as the gap matrix.

Cite this project

@misc{moreno2026beyond,
  title = {{Beyond Model Identity: An Architecture-Literate Information Request for Agentic AI Incidents}},
  author = {Dana Moreno},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/beyond-model-identity-an-architectureliterate-information-request-for-agentic-ai-incidents-3avn}},
  url = {https://apartresearch.com/sprints/projects/beyond-model-identity-an-architectureliterate-information-request-for-agentic-ai-incidents-3avn}
}

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