Two-minute study
QP-083 — Q10 Embodied Agent Surface - Implementation Pack
TWO-MINUTE RESEARCH PAPER · 0.1.0-r1 · 2026-09-25
STATUS: CANDIDATE RESEARCH — HUMAN/INDEPENDENT REVIEW REQUIRED
WHAT IT IS
This is an implementation kit for AI systems that have a visual character, 3D or spatial interface, robot, or other body. It helps keep appearance and body controls separate from what the AI is actually allowed to do.
PROBLEM
Add a visual, spatial, or robotic body to an AI system without letting a realistic appearance or physical interface quietly expand its authority.
WHO IT IS FOR
AI product teams, immersive/3D teams, robotics teams, digital-twin developers, safety reviewers, and technical architects
WHY IT MATTERS
AI-enabled work can fail through weak evidence, stale information, unclear authority, privacy/security gaps, overconfident outputs, or automation that becomes practically irreversible. NIST's AI RMF provides a lifecycle risk-management frame; Q10 applies that direction by requiring explicit scope, evidence, human authority, limitations, review dates, stop conditions, and rollback.
HOW IT WORKS
Name a human owner; define scope; record evidence, unknowns and contradictions; define permissions and prohibited actions; run baseline and adversarial tests; patch and retest; record residual risk; create a dated release receipt; set a review/TTL date.
VALIDATION STATE
19 local unit tests passed. A deterministic 10,000-case seeded policy simulation recorded 0 unsafe allows under the local simulation oracle after patching. This is not field or production proof.
Generated research does not upgrade that evidence.
RISKS / FAILURE MODES
Scope creep; evidence drift; stale sources; authority escalation; false-clear from passing tests; privacy leakage; insecure dependencies; common-mode failure; reviewer fatigue; inaccessible interfaces; rollback failure; unsupported claims repeated as fact.
HUMAN CONTROL
A named human retains consequential approval, override, stop, release, and rollback authority.
KNOWN LIMITS
No production, biometric, digital-human, field-robotics, autonomous-authority, safety-certification, or regulatory claim. Consequential actions remain human-authorized.
REFERENCE BASIS
NIST AI Risk Management Framework 1.0; NIST Generative AI Profile; NIST Privacy Framework; NIST Cybersecurity Framework 2.0; OWASP Top 10 for LLM and GenAI; UNICEF Guidance on AI and Children v3.
BOUNDARY
Research/education material only. Not legal, medical, financial, engineering, safety-certification, or regulatory advice.
How it works
A separate operating explanation has not yet been recorded for this product. Review the buyer/research paper and technical details below for the currently documented implementation information.
AI boundaries & human responsibility
AI-specific allowed/not-allowed actions have not yet been separately recorded for this listing.
Risks, limits & failure modes
No production, biometric, digital-human, field-robotics, autonomous-authority, safety-certification, or regulatory claim. Consequential actions remain human-authorized.
Failure modes: no separate failure-mode record has been published for this listing yet.
Dependencies, compatibility & deployment
Dependencies: not separately recorded.
Evidence, testing & provenance
19 local unit tests passed. A deterministic 10,000-case seeded policy simulation recorded 0 unsafe allows under the local simulation oracle after patching. This is not field or production proof.
Provenance:
Live Shopify product QP-083; tagged Q10_FACTORY_V3_1 and PUBLIC_ARTIFACT_EDITION. It was not matched to the Product Factory v3.0 100 Product Rebuild Queue used for the current buyer-spec batch.
Independent validation: No independent-validation status has been recorded; no independent validation is claimed by this listing.
Resources, privacy & security
Separate resource/energy requirements are not yet recorded on this listing.
Privacy and security obligations depend on the product and deployment. Where they have not yet been versioned in the legal/disclosure manifest, they remain an open pre-sale requirement rather than an implied promise.
What the complete package is expected to include
Reference Python embodiment policy gate; brain/body and identity/body separation architecture; action-envelope and spatial-context schemas; human authorization and TTL rules; accessibility/resource degradation policy; anthropomorphic-authority controls; TSLP results, red-team cases, examples, templates and integration guide.
Price, license, support & updates
Price / pricing method: $699
License: Not yet recorded as a versioned license model.
Legal, rights & disclosures
A plain-language legal summary has not yet been versioned for this product.
Legal manifest status: LEGAL_SNAPSHOT_NOT_YET_VERSIONED