Engineering Compiler

204. AI-Assisted Compilation

AI-Assisted Compilation applies artificial intelligence to support the interpretation, creation, validation, correction, optimization, and explanation of engineering configurations processed by the System05 Engineering Compiler.

AI may assist with:

recognizing engineering intent;

converting informal requirements into structured proposals;

identifying missing or inconsistent information;

proposing BDL expressions;

selecting applicable rules and profiles;

exploring design alternatives;

predicting compatibility risks;

organizing evidence;

explaining diagnostics;

prioritizing review;

generating corrective proposals;

supporting lifecycle change analysis.

AI assistance shall remain subordinate to the formal semantics of BDL, deterministic compiler rules, verified engineering methods, authoritative registries, approved configurations, and designated human authority.

AI-generated content shall be explicitly identified and shall not be treated as an original fact, physical observation, manufacturer declaration, regulatory interpretation, professional judgment, certificate, or approval.

Where AI results affect safety, compliance, configuration, manufacturing, robotic execution, commissioning, or BIOS deployment, the compiler shall require appropriate validation and human review.

AI may accelerate compilation but shall not weaken traceability, reproducibility, evidence requirements, or professional responsibility.

205. Natural-Language-to-BDL Compilation

Natural-Language-to-BDL Compilation converts human statements, conversations, specifications, design briefs, field notes, and other informal descriptions into proposed BDL structures.

The process should distinguish:

stated facts;

user requirements;

design preferences;

assumptions;

inferred relationships;

alternatives;

unknown conditions;

questions requiring clarification;

mandatory and optional requirements.

Conversion should occur through an intermediate engineering intent representation before final canonical BDL is generated.

The AI shall preserve uncertainty and ambiguity rather than silently selecting one interpretation. Where a statement may support several engineering meanings, the system shall present alternatives or request clarification.

Generated BDL shall remain a proposal until it has passed:

syntax validation;

semantic validation;

identity resolution;

unit and coordinate validation;

rule applicability analysis;

engineering validation;

configuration validation;

required human review.

Natural language shall not override the formal meaning of validated BDL. Once an approved BDL configuration exists, later conversational instructions shall enter the governed change process.

The system shall retain traceability between each generated BDL object and the source statement, document passage, user instruction, assumption, or inference from which it was derived.

206. AI-Generated Design Alternatives

AI-Generated Design Alternatives provide multiple candidate configurations capable of satisfying declared engineering objectives and constraints.

Alternatives may explore:

spatial arrangements;

structural systems;

Node topologies;

Cartridge configurations;

materials;

component combinations;

interface strategies;

utility routing;

robotic assembly methods;

manufacturing processes;

sensing strategies;

construction sequences;

lifecycle and reuse options.

Every alternative shall identify:

its configuration identity;

objective;

assumptions;

governing constraints;

selected components and profiles;

expected performance;

unresolved conditions;

required evidence;

predicted advantages;

trade-offs;

confidence;

validation status.

Alternatives shall not be ranked solely through an opaque total score. Safety, compliance, cost, constructability, carbon, resilience, maintainability, local availability, robotic readiness, and lifecycle value shall remain separately visible.

AI shall not represent a generated alternative as feasible merely because it is geometrically plausible. Each alternative shall undergo applicable compatibility, engineering, manufacturing, construction, robotic, and lifecycle validation.

Selection of an alternative remains a governed human decision. Acceptance shall create a controlled configuration revision and trigger complete or impact-based recompilation.

207. AI Rule Interpretation

AI Rule Interpretation assists users and compiler services in understanding the meaning, applicability, interaction, and consequences of engineering rules.

AI may:

summarize complex requirements;

map requirements to BDL entities;

identify potentially applicable rules;

compare rule versions;

explain conflicts;

propose precedence questions;

identify required evidence;

show downstream consequences;

prepare issues for professional or regulatory review.

Every interpretation shall identify its source rules, jurisdiction, version, effective date where relevant, context, assumptions, confidence, and interpretation status.

AI-generated interpretation shall not be represented as an authoritative regulatory determination, legal opinion, professional approval, or amendment to the rule.

Where a formal rule is encoded in machine-executable form, the encoded rule and its governed semantics shall control compiler evaluation. AI explanation shall not silently alter that meaning.

Ambiguous, conflicting, novel, or jurisdiction-sensitive requirements shall be escalated to the designated authority.

An accepted interpretation shall be recorded as a governed interpretation decision linked to its scope and configuration. It shall not automatically become a universal rule for other projects.

208. AI Profile Generation

AI Profile Generation creates proposed Engineering Profiles based on project conditions, regional practices, available materials, manufacturing capability, climate, hazards, regulations, labor conditions, robotic capability, cost objectives, and lifecycle priorities.

Generated profiles may define recommended:

dimensions;

materials;

tolerance classes;

load assumptions;

interface options;

component families;

construction methods;

inspection levels;

environmental protections;

sensing configurations;

maintenance intervals;

A profile shall identify its inputs, geographic and technical scope, source data, assumptions, generation method, rule dependencies, exclusions, validity conditions, confidence, and review status.

A generated profile shall not weaken mandatory requirements. It may become binding only when adopted through an authorized project, organizational, certification, contractual, or regulatory process.

Profiles intended for manufacturers with limited engineering resources should provide practical reference geometries and performance targets while preserving vendor neutrality.

Every adopted profile shall receive an identity, version, governance owner, compatibility declaration, validation record, and deprecation policy.

209. AI Component and Cartridge Selection

AI Component and Cartridge Selection proposes products, components, Cartridges, Nodes, adapters, smart modules, sensors, and related assemblies appropriate for a defined configuration.

Selection shall consider:

required function;

structural capacity;

interface compatibility;

geometry;

tolerances;

material compatibility;

environmental exposure;

fire performance;

certification;

lifecycle state;

availability;

manufacturing source;

installation method;

robotic handling;

inspection requirements;

maintenance and replacement;

A proposal shall identify the authoritative data source, product revision, interface version, certifications, known limitations, availability date where relevant, substitutions, assumptions, and confidence.

Nominal dimensions, marketing descriptions, visual similarity, or prior use shall not establish compatibility.

AI shall not invent unavailable product properties or treat missing evidence as satisfactory. Unknown or expired information shall remain explicit.

Final selection shall be validated by the compiler and approved through applicable design, procurement, manufacturer, and professional gates.

210. AI Compatibility Proposals

AI Compatibility Proposals recommend ways to resolve incompatibilities among components, Cartridges, Nodes, interfaces, tools, software, protocols, lifecycle states, or versions.

A proposal may include:

selection of a compatible component;

approved adapter use;

interface migration;

tolerance correction;

geometry modification;

material isolation;

firmware or protocol update;

revised assembly sequence;

additional verification;

controlled derating;

replacement or redesign.

Each proposal shall identify:

the incompatibility addressed;

affected entities;

relevant interface contracts;

proposed resolution;

required modifications;

secondary consequences;

new failure modes;

required evidence;

certification impact;

approvals;

confidence;

validation status.

An adapter shall not be assumed safe merely because it connects two physical geometries. Load transfer, stiffness, tolerances, fire behavior, durability, utilities, data, sensing, access, maintenance, and robotic handling shall be evaluated.

AI proposals shall not modify manufacturer-controlled or certified interfaces without authorization.

A compatibility proposal becomes an accepted solution only after incorporation into a new configuration and successful recompilation.

211. AI Risk Detection

AI Risk Detection identifies patterns, combinations, anomalies, omissions, and emerging conditions that may indicate engineering, construction, operational, cybersecurity, lifecycle, or project risk.

It may detect risks related to:

incomplete load paths;

incompatible interfaces;

insufficient tolerances;

construction sequence;

robotic access;

component substitution;

environmental exposure;

inspection gaps;

sensor anomalies;

degradation;

maintenance delay;

configuration drift;

evidence weakness;

single points of failure;

correlated failure conditions.

Each detected risk shall identify its evidence, affected entities, possible causes, consequence, likelihood or uncertainty, time horizon, dependencies, recommended investigation, and confidence.

AI risk detection shall distinguish observed conditions from inferred risks and predicted future conditions.

Absence of an AI warning shall not establish safety or compliance. AI systems may supplement but shall not replace required calculations, inspections, tests, deterministic rules, or professional review.

High-consequence detections shall be routed through defined escalation and safe-state procedures.

False-positive, false-negative, and confirmed-risk outcomes should be recorded to evaluate and improve the detection system without corrupting historical compilation records.

212. AI Error Explanation

AI Error Explanation converts compiler diagnostics into clear, contextual, and actionable information for users.

An explanation should describe:

what failed;

where it occurred;

the governing rule;

why the condition matters;

affected entities and outputs;

whether the issue is a root cause or dependent consequence;

what information is missing;

possible corrective paths;

required authority or reviewer.

AI may adapt explanations for authors, engineers, manufacturers, contractors, inspectors, owners, regulators, or technicians while preserving the underlying diagnostic meaning.

Corrective examples shall remain proposals and shall not be represented as verified solutions until incorporated into the configuration and recompiled.

The original machine-readable diagnostic shall remain accessible and traceable from every human-readable explanation.

213. AI Confidence Representation

AI Confidence Representation communicates the degree of support for an AI-generated classification, inference, interpretation, proposal, or prediction.

Confidence representation shall identify:

the output concerned;

confidence value or category;

method used;

evidence coverage;

uncertainty sources;

missing information;

model limitations;

sensitivity to assumptions;

conditions that could change the result.

Confidence shall not be presented as probability of engineering safety unless the system has been specifically validated for that meaning.

A high-confidence AI output shall not override a failed deterministic rule, missing evidence, physical mismatch, professional approval gate, or regulatory requirement.

Low confidence shall trigger clarification, additional evidence, alternative analysis, or human review according to consequence.

Where several alternatives are produced, confidence in interpretation, feasibility, compliance, performance, and selection should remain separately represented.

Confidence values shall be calibrated and monitored against observed outcomes where possible. Material model, data, or calibration changes shall be versioned.

The provenance record shall include, as applicable:

model identity and version;

system and task configuration;

input sources;

source revisions;

retrieved rules and registry records;

prompt or instruction identity;

tools and services used;

generation time;

intermediate transformations;

assumptions;

human edits;

confidence;

validation results;

approval status.

Sensitive prompts, proprietary data, or protected model internals need not be disclosed publicly, but the retained record shall be sufficient to identify the engineering basis and reproduce or audit the governed result to the required degree.

Where an AI system cannot provide adequate provenance for a safety-significant output, that output shall be restricted to advisory or exploratory use.

Human Review of AI Outputs ensures that AI-generated engineering content receives scrutiny proportional to its uncertainty and potential consequence.

Review shall consider:

correctness;

completeness;

applicability;

source quality;

assumptions;

omitted alternatives;

uncertainty;

rule consistency;

physical feasibility;

lifecycle impact;

bias or optimization distortion;

Safety-significant AI outputs shall require a qualified reviewer with authority over the affected scope. The reviewer shall have access to underlying sources, assumptions, diagnostics, and provenance.

Review actions shall record:

reviewer identity;

qualifications and authority;

configuration reviewed;

AI output reviewed;

conclusion;

corrections;

conditions;

rejected elements;

date and signature.

Human review shall not consist solely of accepting an AI-generated summary. The reviewer shall examine the information necessary to support the decision.

Acceptance of an AI output shall not convert unsupported content into evidence. Required calculations, tests, inspections, certifications, and approvals shall still be obtained.

216. Prohibited AI Compiler Actions

An AI-integrated System05 compiler shall be prohibited from autonomously:

inventing physical observations or test results;

fabricating certificates, calculations, signatures, approvals, or evidence;

concealing uncertainty or missing information;

altering authoritative rules without governance;

weakening mandatory requirements;

approving exceptions or waivers;

issuing professional or regulatory approval;

selecting an unsafe configuration to satisfy cost or schedule objectives;

changing a signed configuration silently;

releasing manufacturing instructions from invalid information;

authorizing robotic execution without required gates;

activating a safety-significant BIOS change without authorization;

overriding an emergency stop or safety interlock;

representing simulation as physical verification;

presenting predicted compatibility as certified compatibility;

deleting provenance or unresolved conditions;

Where user instructions conflict with safety, legal authority, approved configuration, or higher-priority rules, the system shall preserve the conflict and restrict the affected action.

Prohibited actions shall be enforced through architecture, access control, signing, target gating, runtime isolation, and audit—not merely through conversational instructions.

Attempts to request or induce prohibited actions shall be logged and handled according to applicable security and governance policies.

217. Engineering Agent Integration

Engineering Agent Integration enables specialized software or AI agents to participate in governed compilation activities.

Agents may support domains such as:

architecture;

structure;

materials;

interfaces;

utilities;

fire safety;

manufacturing;

construction;

robotics;

inspection;

commissioning;

maintenance;

cost;

sustainability;

regulatory analysis.

Every agent shall have a declared identity, owner, version, capability profile, input requirements, output schema, authority boundary, validation status, permissions, and prohibited actions.

Agent outputs shall be treated according to their actual status: observation, calculation, interpretation, proposal, validation result, or advisory recommendation.

An agent shall not acquire authority merely because another agent depends upon its output.

Safety-significant agent actions shall be constrained through least-privilege access, configuration binding, deterministic validation, human review, and signed authorization.

The compiler shall preserve the complete chain of agent inputs, outputs, dependencies, disagreements, failures, and human interventions.

Agents shall communicate through governed schemas and interface contracts rather than relying solely on unrestricted natural-language exchanges.

218. Multi-Agent Engineering Coordination

Multi-Agent Engineering Coordination manages the work of multiple specialized agents contributing to the same configuration.

The coordination layer shall define:

shared project context;

canonical configuration identity;

agent roles;

domain ownership;

task boundaries;

dependencies;

authority limits;

communication protocols;

conflict-resolution procedures;

completion criteria.

Parallel agent results shall not be merged solely because they are individually plausible. The coordinator shall verify that all results refer to compatible source versions, assumptions, units, coordinate systems, profiles, lifecycle states, and configuration selections.

Disagreement among agents shall remain visible. Resolution may require rule precedence, source correction, multidisciplinary analysis, or human authority.

No agent shall silently modify an entity owned by another domain. Proposed cross-domain changes shall enter a governed change set.

The coordination system shall detect circular dependencies, stale context, duplicate work, conflicting assumptions, unavailable agents, and incomplete task closure.

A multi-agent consensus shall not substitute for evidence or professional approval. Several agents repeating the same unsupported conclusion shall not increase its authority.

219. Robotics Compiler Integration

Robotics Compiler Integration connects the System05 Engineering Compiler with robot planning, simulation, control, perception, and verification systems.

The integration shall transform approved engineering intent into robot-specific tasks while preserving:

component identity;

interface semantics;

geometry;

tolerances;

coordinate frames;

sequence;

safety constraints;

required verification;

authority boundaries;

Robotics compilation shall distinguish:

task planning;

simulation;

executable generation;

authorization;

physical execution;

verification;

Changes to robot hardware, firmware, calibration, tooling, environment, component geometry, work-cell arrangement, or safety configuration shall trigger compatibility and revalidation checks.

Robot Capability Matching determines whether a specific robot system can safely and reliably perform a compiled task.

The capability model shall include:

payload;

reach;

degrees of freedom;

positional and force accuracy;

repeatability;

speed;

compliance;

sensing;

perception;

communication;

environmental rating;

mobility;

calibration status;

tool compatibility;

safety functions;

Capability matching shall evaluate the complete operation, including approach, grasping, lifting, positioning, insertion, locking, verification, retreat, recovery, and intermediate states.

A robot shall not be considered capable solely because its maximum payload or reach exceeds a nominal value.

The system shall evaluate singularities, occlusion, deflection, center of mass, dynamic loading, cable routing, access constraints, human interaction, and failure recovery.

Capability matches shall be configuration-, tool-, environment-, and task-specific and shall have defined validity conditions.

221. Robot Task Generation

Robot Task Generation produces structured operations required to execute an approved construction, assembly, inspection, maintenance, or decommissioning activity.

Generated tasks shall define:

task identity;

prerequisites;

robot and tool;

target objects;

object identities;

coordinate frames;

initial state;

motion stages;

grasp points;

manipulation forces;

interface engagement;

verification actions;

safe states;

exception behavior;

AI-generated adaptation may be permitted for local path or grasp optimization only within explicitly approved limits. It shall not change the engineering configuration or required assembly state.

Every executed task shall return structured evidence identifying what was commanded, observed, completed, failed, retried, or changed.

222. Tool and End-Effector Selection

Tool and End-Effector Selection identifies the equipment necessary for a robot to manipulate, assemble, inspect, test, maintain, or remove System05 elements.

Selection shall consider:

component geometry;

mass and center of gravity;

surface condition;

grasp features;

required force and torque;

alignment method;

interface access;

material sensitivity;

contamination control;

electrical isolation;

sensing;

calibration;

release behavior;

tool-change requirements.

System05 components should provide standardized robot-readable grasping, alignment, engagement, locking, and verification features where practical.

The selected tool shall be compatible with the robot, work cell, component, process, safety system, and target task package.

Temporary contact shall not damage finishes, seals, sensors, identification marks, fire protection, or controlled interface surfaces.

Tool identity, revision, wear state, calibration, and maintenance status shall be verified before execution.

Unverified or improvised tools shall not be used for safety-significant operations unless evaluated and authorized through the governed change process.

223. Robotic Access and Envelope Checking

Robotic Access and Envelope Checking verifies that a robot and its tool can reach and perform every required action without prohibited collision, obstruction, instability, or unsafe interaction.

The evaluation shall include:

robot body envelope;

tool envelope;

carried-component envelope;

motion uncertainty;

component tolerances;

temporary supports;

scaffolding and equipment;

installed and future elements;

human zones;

emergency clearance;

approach and retreat paths;

A connection may be physically accessible to a human while remaining inaccessible to a robot, or accessible for insertion but inaccessible for locking, inspection, maintenance, or removal.

Robot-ready design shall therefore include adequate approach corridors, tool clearances, alignment allowances, sensing visibility, and recovery space.

Where access depends upon an assumed sequence, that sequence shall become an explicit constraint of the assembly package.

224. Robotic Sequence Validation

Robotic Sequence Validation evaluates whether the proposed order of robot operations is feasible, stable, safe, and consistent with the approved building configuration.

Validation shall address:

prerequisite completion;

temporary stability;

load-path development;

component access;

tool changes;

utility conflicts;

curing or waiting periods;

tolerance accumulation;

inspection hold points;

human coordination;

recovery paths;

emergency access.

The compiler shall detect operations that would trap tools, obstruct future connections, remove necessary supports, overload incomplete assemblies, or prevent required inspection.

Sequence validation shall consider multi-robot interference and shared workspace where applicable.

Optimization for speed shall remain subordinate to structural stability, safety, verification, and configuration control.

A field change in sequence shall be evaluated against the approved dependency and safety model before the affected operation proceeds.

The executed sequence and all approved deviations shall be recorded as part of the as-built and commissioning evidence.

225. Installation Verification Requirements

Installation Verification Requirements establish the evidence necessary to demonstrate that a physical component has been installed in the correct location, identity, orientation, state, and configuration.

Verification may include:

identity scanning;

geometry measurement;

orientation recognition;

seating confirmation;

lock-state sensing;

torque or force records;

electrical continuity;

utility testing;

visual or machine-vision inspection;

photographs;

sensor response;

human inspection;

professional acceptance.

For System05 Nodes and Cartridges, verification shall address the relevant structural, geometric, utility, data, sensing, environmental, and fire interfaces.

Completion of a robot motion shall not establish successful installation.

Verification criteria shall be derived from the exact component, interface, tolerance class, lifecycle stage, and approved configuration.

Where a centralized replaceable smart module receives signals from distributed parts of a Node, the commissioning process shall verify both the physical condition and the signal path used to report it.

Failed, missing, ambiguous, or conflicting verification shall prevent the affected installation from being represented as complete.

226. Building BIOS Integration

Building BIOS Integration connects compiled engineering configurations with the authoritative digital system that records the building’s active configuration and operationally recognized state.

The compiler shall provide the BIOS with controlled information including:

building identity;

configuration identity;

Node and Cartridge registries;

interface relationships;

component capabilities;

spatial and functional topology;

lifecycle states;

sensor mappings;

safety policies;

maintenance requirements;

permitted state transitions;

Digital Twin synchronization rules.

The Building BIOS shall not be treated as a passive document store. It governs the recognized configuration and authorized runtime state of the building.

The BIOS shall not independently reinterpret BDL or modify the approved engineering design.

Changes proposed through operations, maintenance, AI, sensors, or the Digital Twin shall enter the compilation and authorization process before becoming active configuration changes.

BIOS integration shall support offline operation, exportability, migration, recovery, long-term serviceability, and vendor neutrality.

227. BIOS Deployment Protocol

The BIOS Deployment Protocol governs preparation, verification, transfer, activation, observation, acceptance, and rollback of a Building BIOS Deployment Package.

The protocol shall include:

package generation;

integrity verification;

compatibility checking;

authority verification;

backup of the active configuration;

staged installation;

pre-activation tests;

controlled activation;

runtime observation;

commissioning acceptance;

final configuration registration.

The receiving BIOS shall verify package identity, building identity, configuration identity, version path, dependencies, signatures, authorization scope, and rollback availability.

Deployment shall fail safely if the package is incomplete, corrupted, unauthorized, incompatible, expired, or associated with a different physical configuration.

Safety-significant changes should be deployed through isolated or staged transitions where feasible.

Generation, transfer, installation, and activation shall remain distinct events with separately recorded authorities.

A failed deployment shall not corrupt the last verified operational configuration. Recovery status and unresolved discrepancies shall remain visible.

228. Physical Discovery and Reconciliation

Physical Discovery and Reconciliation compares the compiled and BIOS-recognized configuration with the components and conditions detected in the physical building.

Discovery may use:

digital identity scanning;

embedded identifiers;

smart Node modules;

Cartridge signals;

sensor networks;

machine vision;

dimensional scanning;

utility testing;

manual inspection;

commissioning records.

The process shall distinguish:

expected and discovered components;

confirmed matches;

missing components;

unexpected components;

identity conflicts;

version mismatches;

location or orientation errors;

state mismatches;

Likewise, an observed component shall not automatically become an approved part of the configuration merely because it is physically present.

Discrepancies shall trigger investigation, correction, controlled as-built change, exception management, or recompilation.

Reconciliation shall preserve the difference between designed, approved, delivered, installed, commissioned, observed, and inferred states.

229. Commissioning Feedback

Commissioning Feedback returns physical test, inspection, installation, discovery, and performance results to the compiler and Building BIOS.

Feedback may confirm or challenge:

component identity;

interface engagement;

utility continuity;

sensor operation;

control behavior;

geometric condition;

expected performance;

calibration;

safety interlocks;

Digital Twin mappings.

Each feedback item shall identify its source, method, time, location, component, configuration, observer or system, measurement uncertainty, and evidence status.

Commissioning results shall not silently change design requirements. Deviations shall be evaluated through governed resolution and change control.

Failed tests shall generate diagnostics, restrictions, corrective actions, and retesting requirements.

Successful commissioning shall establish the verified operational baseline for the Building BIOS and Digital Twin.

Where commissioning reveals that an accepted design assumption does not match physical behavior, affected calculations, rules, packages, and approvals shall undergo impact analysis.

230. Runtime Configuration Changes

Runtime Configuration Changes are modifications proposed or performed after the building has entered an operational or commissioned state.

Changes may include:

component replacement;

Cartridge exchange;

smart-module replacement;

sensor addition;

firmware update;

control-policy modification;

space reconfiguration;

utility rerouting;

structural repair;

temporary isolation;

emergency reconfiguration.

Every proposed runtime change shall identify the current baseline, requested modification, authority, affected entities, intended duration, risks, dependencies, rollback method, and required validation.

The Building BIOS shall prevent unapproved runtime changes from being represented as part of the active validated configuration.

Temporary operational changes shall have explicit scope, monitoring, expiration, and restoration requirements.

Replacement of a smart module shall preserve the identity of the Node while recording the identity, configuration, calibration, and history of the new module.

Physical and digital changes shall be reconciled. Updating BIOS data without performing the physical change, or performing the physical change without updating the BIOS, shall create a configuration discrepancy.

231. Digital Twin Integration

Digital Twin Integration connects the compiler, Building BIOS, physical observations, simulation models, lifecycle records, and user-facing representations.

The Digital Twin may support:

visualization;

monitoring;

simulation;

prediction;

maintenance planning;

operational analysis;

change proposals;

emergency assessment;

lifecycle optimization.

The Digital Twin shall be generated and updated from the governed building configuration and synchronized with the Building BIOS.

The Building BIOS shall remain authoritative for the active configuration and operationally recognized state. The Digital Twin may contain additional simulated, predicted, historical, or inferred information, but such information shall be clearly classified.

The Digital Twin shall distinguish:

designed state;

approved state;

as-built state;

commissioned state;

BIOS-recognized state;

observed state;

inferred state;

simulated state;

predicted state.

A change made within the Digital Twin shall remain a proposal until compiled, validated, authorized, physically implemented, verified, and deployed to the BIOS where applicable.

Feedback may identify:

predicted failure modes;

insufficient capacity;

thermal or moisture risk;

assembly difficulty;

robotic collision;

energy performance;

control instability;

maintenance need;

resilience weakness;

alternative performance.

Simulation feedback shall retain its originating model, solver, configuration, assumptions, boundary conditions, numerical settings, uncertainty, sensitivity, and applicability limits.

The compiler shall distinguish simulation findings from observed physical facts.

Results may initiate:

design review;

rule evaluation;

alternative generation;

corrective proposal;

additional evidence requirements;

physical testing;

Where multiple simulations produce conflicting results, the conflict shall remain explicit and may require model review, testing, or professional judgment.

Validated physical observations may be used to calibrate future simulation models, but calibration changes shall be versioned and shall not rewrite historical results.

233. Sensor and Inspection Feedback

Sensor and Inspection Feedback incorporates measured or observed building conditions into lifecycle evaluation.

Feedback may include:

load or strain;

displacement;

vibration;

temperature;

moisture;

smoke or fire indicators;

corrosion;

lock status;

utility flow;

energy use;

component presence;

inspection findings;

maintenance observations.

Every feedback record shall identify its source, sensor or inspector, calibration status, time, location, configuration context, accuracy, integrity, and data-quality status.

The compiler and BIOS shall distinguish raw measurements, processed values, detected events, inferred conditions, and predicted consequences.

Centralized replaceable smart modules may collect signals from multiple locations within a Node or connected assemblies. The design shall preserve traceability from each reported condition to its physical sensing path.

Sensor absence, communication failure, battery depletion, calibration expiration, or contradictory readings shall not be interpreted as confirmation of normal condition.

Safety-significant thresholds shall trigger defined notification, inspection, restriction, shutdown, emergency response, or recompilation procedures.

234. Recompilation after Physical Change

Recompilation after Physical Change evaluates the consequences of an actual modification, replacement, deviation, damage event, repair, or discovered as-built condition.

The process shall begin with the last verified configuration and the evidence describing the physical change.

It shall determine impacts on:

load paths;

interfaces;

tolerances;

fire performance;

utilities;

sensing;

robotic access;

maintenance;

certifications;

warranties;

BIOS configuration;

Digital Twin models;

future reuse.

Emergency work performed before full recompilation shall be represented as a temporary, authority-limited condition requiring subsequent reconciliation.

If the exact physical state cannot be established, the affected configuration shall remain unknown, provisional, restricted, or indeterminate.

Recompilation shall produce a new configuration revision, updated outputs, required inspections, commissioning activities, approval gates, and deployment instructions.

Continuous and Event-Driven Compilation performs impact analysis or recompilation when relevant information changes.

Triggers may include:

BDL edits;

rule or profile updates;

component changes;

certificate expiration or revocation;

sensor events;

inspection findings;

BIOS state changes;

Digital Twin proposals;

physical discovery;

commissioning results;

damage events;

cybersecurity events;

The system shall classify events according to consequence and determine whether they require notification, analysis, partial recompilation, full recompilation, human review, safe-state transition, or emergency action.

Event storms, duplicate signals, unreliable sensors, or unstable external services shall not cause uncontrolled configuration changes.

Results shall be bound to the exact event set, configuration baseline, compiler version, rules, evidence, and time context.

Automatic deployment may occur only for narrowly defined low-consequence changes within an explicitly authorized policy. Safety-significant changes shall require the applicable review, approval, commissioning, and deployment gates.

236. Human–AI–Robot Authority Model

The Human–AI–Robot Authority Model defines how responsibility, decision rights, execution authority, verification, and control are distributed across people, AI systems, engineering agents, compilers, robots, the Building BIOS, and the Digital Twin.

The general authority structure shall be:

humans establish objectives, approve governed decisions, and retain professional and legal responsibility;

AI systems interpret, propose, explain, predict, and assist;

deterministic compiler functions evaluate formal rules and generate controlled outputs;

robots execute authorized physical tasks within approved envelopes;

sensors and inspectors provide evidence;

the Building BIOS records and governs the active recognized configuration and runtime state;

the Digital Twin represents, analyzes, simulates, and predicts without independently activating physical change.

No participant shall exceed its declared authority.

Robots shall have authority to stop when safety, verification, identity, calibration, or configuration conditions are not satisfied. They shall not have authority to waive requirements or redesign the building.

AI may recommend but shall not approve safety-significant changes, professional decisions, waivers, physical execution, or BIOS activation.

Human authority shall itself be scoped. An owner, operator, engineer, manufacturer, inspector, regulator, and emergency responder shall not be treated as interchangeable authorities.

All safety-significant actions shall preserve:

accountable identity;

configuration binding;

evidence;

authorization;

bounded execution;

independent safety control;

verification;

auditability;

rollback or recovery where possible.

The final authority model shall prevent both uncontrolled machine autonomy and informal human override of governed engineering requirements. Human judgment remains essential, but it shall operate through explicit roles, evidence, responsibility, and traceable decisions.