MDM — Migration Decision Module

Architecture:

VEGA™ — Value Execution Governance Architecture

Parent Standard:

Decision Governance Standard (DGS)

Category:

Governance & Enforcement

Subcategory:

Value Execution Governance

Type: Core Module

Governed Space:

Intelligence Migration Decision Governance

Module ID: VEGA-DGS-MDM-004

Origin ID: OOF.CM.VEGA.10.04.01

Version: 1.0

Status: Canonical · Open Standard

Effective Date: 1 October 2026

Compatibility: OOF® Methodology OS™ · Modular OOF® Architecture Ecosystem

AI-Readable: Yes

Authority: OOF® — OriginOpen® Foundation

Protection:

MIP® — Methodological Intellectual Property

Canonical Language:

English (UCL™)

1. Canonical Definition

The Migration Decision Module (MDM) governs whether an intelligence capability should transition from its current operating configuration, mechanism, model, provider, infrastructure, agent structure, or execution environment to a materially different alternative.

MDM evaluates whether migration is justified by governed evidence concerning Value preservation or improvement, productivity, resource consumption, Computational Optimization, economics, Strategic Value, sustainability, dependency, attribution, transition feasibility, and applicable governed constraints.

It distinguishes the existence of an alternative from justification for migration to that alternative.

MDM also distinguishes migration benefit from migration feasibility and migration feasibility from migration necessity.

A newer, cheaper, faster, larger, smaller, more capable, or more efficient technology does not by itself justify migration.

Its principal output is:

Governed Migration Decision State

Its foundational distinction is:

Better Alternative ≠ Justified Migration.

2. Operational Role

The operational role of MDM is:

to determine whether moving an intelligence capability from its current operating state to a materially different target state is sufficiently justified, feasible, Value-preserving, proportionate, and governable across the transition.

MDM governs not only the comparison between Current State and Target State.

It governs the decision relevance of the transition itself.

3. Position in the DGS Internal Flow

The DGS internal governance flow is:

Decision Evidence Consolidation → Continuation Decision → Scaling Decision → Migration Decision → Retirement Decision

MDM governs:

Migration Decision

Its principal upstream inputs may include:

Governed Decision Evidence State

Governed Continuation Decision State

and

Governed Scaling Decision State

where applicable.

Its principal output is:

Governed Migration Decision State

Where migration is not justified and continued operation is no longer supportable, the resulting evidence may proceed toward:

Retirement Decision Governance

4. Central Operational Question

Does the governed evidence justify moving the intelligence capability from its current operating state to a materially different target state, and can that transition preserve or improve required Value within applicable governed constraints?

5. Migration Decision Object

Every MDM assessment should identify the intelligence capability whose migration is being considered.

The object may include:

a model deployment,

agent system,

workflow,

automation capability,

decision-support system,

robotic intelligence configuration,

Human–AI operating model,

or another bounded intelligence capability.

6. Current Operating State

MDM should establish the Current Operating State.

This should identify, where material:

current intelligence mechanism,

model,

agent structure,

orchestration,

tools,

compute,

hardware,

infrastructure,

provider,

resource profile,

economic profile,

Value state,

and dependency structure.

7. Target Operating State

The proposed Target Operating State should be explicitly defined.

It should identify what materially changes and what is expected to remain preserved.

Migration cannot be governed through an undefined claim that a “better system” exists.

8. Migration Boundary

The Migration Boundary defines which components are changing.

Migration may involve:

one model,

one provider,

one infrastructure layer,

one agent architecture,

one workflow,

or the complete operating model.

The boundary should prevent local changes from being confused with full-system migration.

9. Migration Horizon

MDM should identify:

transition period,

expected stabilization period,

and relevant post-migration evaluation horizon.

Migration Value should not be evaluated only at the final target state while ignoring the transition period.

10. Migration Context

Migration should be evaluated within the actual operating context.

Relevant conditions may include:

workload,

users,

scale,

operational criticality,

resource availability,

economic conditions,

dependencies,

continuity requirements,

and applicable constraints.

11. Migration Trigger

A Migration Trigger is a condition that creates a legitimate reason to evaluate migration.

Possible triggers include:

cost deterioration,

resource disproportionality,

technology obsolescence,

dependency risk,

provider change,

infrastructure limitation,

sustainability deterioration,

capability mismatch,

scaling limitation,

or emergence of a materially more proportionate configuration.

12. Migration Trigger ≠ Migration Decision

The existence of a migration trigger establishes a reason to evaluate migration.

It does not establish that migration is justified.

Reason to Evaluate Migration ≠ Reason to Execute Migration.

13. Migration Candidate

A Migration Candidate is an alternative operating state sufficiently plausible to enter migration evaluation.

Candidate identification should not imply preference or selection.

14. Candidate Qualification

A candidate should be sufficiently defined to support meaningful comparison.

Relevant information may include:

expected capability,

configuration,

resource requirements,

cost,

infrastructure,

dependencies,

compatibility,

and expected Value.

15. Current-State Evidence

The Current State should be evaluated using governed evidence rather than dissatisfaction, familiarity, or preference.

Evidence may include:

Value,

productivity,

cost,

resource consumption,

sustainability,

dependency,

and attribution.

16. Target-State Evidence

The Target State should be supported by evidence appropriate to its maturity.

Target evidence may be:

observed,

tested,

validated,

projected,

simulated,

or otherwise governed.

Projected evidence should remain distinct from observed evidence.

17. Evidence Symmetry

Current and Target States should be compared using sufficiently compatible evidence where possible.

A mature production system should not be unfairly compared against idealized marketing claims for an untested alternative.

Observed Current-State Evidence ≠ Projected Target-State Evidence.

18. Migration Evidence Sufficiency

Evidence should be sufficient for the materiality and reversibility of the proposed migration.

A low-impact reversible model switch may require different evidence from migration of a mission-critical intelligence infrastructure.

19. Migration Value Baseline

MDM should establish the Value that must be preserved, replaced, or improved through migration.

Without a Value baseline, migration can optimize technology while degrading the actual operational outcome.

20. Value Preservation

A Target State should preserve the required validated Value unless the migration explicitly and legitimately changes the governed Value objective.

Lower Cost + Lost Required Value ≠ Successful Migration.

21. Value Improvement

Migration may be justified where the Target State produces materially greater validated Value.

Improvement should be evaluated against additional:

cost,

resources,

transition burden,

and dependencies.

22. Value Transformation

Migration may intentionally change the form of Value produced.

Where this occurs, the new Value should be appropriately governed rather than assumed equivalent to the previous Value.

23. Value Loss During Transition

Migration may temporarily reduce operational Value.

MDM should identify whether such reduction is:

acceptable,

bounded,

recoverable,

and proportionate to expected migration benefit.

24. Productivity Comparison

Current and Target States may differ in productive capacity.

MDM should compare validated productive output rather than raw activity or technical throughput alone.

25. Resource Comparison

Migration may alter consumption of:

compute,

energy,

hardware,

infrastructure,

human effort,

time,

or other resources.

Resource reduction should remain connected to preservation of required Value.

26. Computational Migration Value

A Target State may improve:

Problem-Space Efficiency,

Cognitive Efficiency,

Orchestration Efficiency,

Model Allocation Efficiency,

Compute Allocation Efficiency,

or Hardware Execution Efficiency.

MDM may consume COS evidence without recreating Computational Optimization governance.

27. Model Migration

Model Migration may involve moving:

between model families,

between model sizes,

between providers,

between proprietary and open models,

or between general and specialized models.

A more capable model does not automatically justify migration.

28. Model Downsizing

Migration may move from a larger model to a smaller model where the smaller model reliably produces the required validated outcome.

Smaller Model ≠ Lower Value by default.

This can be a legitimate VEGA™ migration pathway.

29. Model Upsizing

Migration to a larger or more capable model should require evidence that additional capability addresses an unresolved operational requirement.

Greater Model Capability ≠ Migration Necessity.

30. Mechanism Migration

Migration may occur between fundamentally different intelligence mechanisms.

Examples may include movement from:

advanced model to specialized model,

model to deterministic algorithm,

multi-agent system to single-agent configuration,

AI process to hybrid Human–AI process,

or another mechanism-neutral transition.

31. No-Intelligence Migration

Where the required validated outcome can be reliably produced without an intelligence mechanism, migration may move toward:

deterministic rules,

mathematics,

statistics,

specialized algorithms,

or another simpler mechanism.

Migration can reduce intelligence rather than increase it.

32. Agent Architecture Migration

A multi-agent system may migrate to:

different agent roles,

fewer agents,

more agents,

different coordination,

or a fundamentally different orchestration structure.

Agent count should not itself determine migration Value.

33. Provider Migration

Provider Migration may be considered because of:

cost,

dependency,

availability,

capability,

data conditions,

infrastructure,

or strategic reasons.

Provider change should be evaluated as an operating-model change, not merely a procurement substitution.

34. Infrastructure Migration

Migration may occur between:

cloud environments,

on-premise infrastructure,

edge environments,

data centers,

hardware classes,

or hybrid configurations.

Infrastructure feasibility does not establish migration justification.

35. Cloud-to-Edge Migration

Cloud-to-edge migration may reduce:

latency,

network dependency,

or centralized infrastructure use

while introducing different:

hardware,

maintenance,

capacity,

and lifecycle constraints.

MDM should evaluate the full governed state.

36. Edge-to-Cloud Migration

Edge-to-cloud migration may improve:

centralized management,

compute availability,

or model capability

while increasing:

network dependency,

central infrastructure dependency,

or recurring cost.

Neither direction is inherently preferable.

37. Hardware Migration

A change in hardware platform may alter:

performance,

energy consumption,

precision,

memory behavior,

cost,

and infrastructure requirements.

VEGA™ does not design the hardware.

MDM governs whether the hardware transition is justified by operational Value.

38. Workflow Migration

Migration may involve redesigning the workflow rather than replacing the model.

A new workflow may produce greater Value with the same intelligence capability.

Technology replacement should not be assumed necessary where process redesign solves the governed problem.

39. Human–AI Configuration Migration

Migration may change the distribution of work between:

humans,

AI,

automation,

and validation mechanisms.

VAS evidence may help identify whether the Target State preserves the contributions materially responsible for Value.

40. Economic Migration Value

Migration should consider both steady-state economics and transition economics.

A Target State may be cheaper after migration while requiring substantial transition investment.

Both conditions should remain visible.

41. Migration Cost

Migration Cost may include:

implementation,

integration,

data movement,

validation,

testing,

retraining,

infrastructure,

parallel operation,

contract termination,

and human transition effort.

42. Transition Cost

Transition Cost should be distinguished from long-term Target-State cost.

A high transition cost may still be justified by sufficiently strong lifecycle Value.

A low transition cost does not establish migration Value.

43. Migration Payback Horizon

Where economic evidence is relevant, MDM may identify the expected period required for migration benefits to offset transition cost.

The payback horizon should not replace broader Value governance.

44. Failure Spend During Migration

Transition may temporarily increase:

failure,

correction,

rework,

or support requirements.

These costs should be included where material.

45. Parallel Operation Cost

Some migrations require Current and Target States to operate simultaneously.

Parallel operation may support continuity and validation while increasing temporary cost and resource consumption.

46. Strategic Migration Value

Migration may produce Strategic Value through:

reduced dependency,

new capability,

greater flexibility,

improved future scalability,

or stronger infrastructure positioning.

Strategic claims should remain evidenced.

47. Sustainability Migration Value

Migration may improve long-term:

energy viability,

infrastructure sustainability,

economic continuity,

or dependency sustainability.

ISS evidence may support this evaluation.

48. Dependency Reduction

Migration may reduce reliance on a critical dependency.

This may create Value even where immediate performance improvement is limited.

49. Dependency Transfer

Migration may remove one dependency while creating another.

Dependency Reduction ≠ Dependency Elimination.

MDM should identify where dependency is transferred rather than removed.

50. Lock-In Reduction

Migration may reduce technical, contractual, infrastructural, or provider lock-in.

Lock-in reduction may increase future optionality.

51. New Lock-In

The Target State may introduce new lock-in.

Migration should therefore compare:

current lock-in,

target lock-in,

and transition lock-in.

52. Migration Compatibility

MDM should assess whether the Target State can interoperate with required:

systems,

data,

tools,

interfaces,

workflows,

and infrastructure.

Compatibility is a feasibility condition.

It is not sufficient justification by itself.

53. Data Migration

Where migration requires data movement or transformation, the decision should preserve relevant evidence concerning:

availability,

integrity,

compatibility,

and transition feasibility.

MDM does not replace competent data governance.

54. State Migration

Agent systems, adaptive systems, or persistent intelligence may require transfer of:

state,

memory,

configuration,

or operational context.

Where material, the feasibility and Value implications should be governed.

55. Knowledge Preservation

Migration should identify whether material operational knowledge can be preserved.

Loss of tacit or system-specific knowledge may create hidden migration cost.

56. Configuration Preservation

Where the Target State depends on equivalent configuration, MDM should determine whether:

prompts,

routing,

tools,

agent roles,

validation,

or other configuration mechanisms

can be transferred or reconstructed.

57. Migration Validation

The Target State should be validated sufficiently for the decision being made.

MDM does not replace VALIDOS™.

It consumes the relevant validation state.

58. Equivalence Validation

Where migration claims equivalent Value at lower consumption or cost, equivalence should be evidenced.

Claimed Equivalence ≠ Validated Equivalence.

59. Improvement Validation

Where migration claims greater Value, the improvement should be sufficiently validated relative to the Current State.

60. Transition Feasibility

Migration may be desirable but operationally infeasible.

MDM should assess whether the transition can actually be executed within relevant constraints.

Migration Benefit ≠ Migration Feasibility.

61. Migration Necessity

A feasible and beneficial migration may still not be necessary.

Migration Necessity should be distinguished from:

migration opportunity,

migration benefit,

and migration feasibility.

Migration Feasibility ≠ Migration Necessity.

62. Migration Urgency

Where migration is justified, urgency may vary.

Possible states may include:

Immediate

Time-Bounded

Planned

Opportunistic

Non-Urgent

Unresolved

Urgency should follow evidence.

63. Migration Timing

Migration timing may materially affect:

cost,

continuity,

contractual conditions,

resource availability,

or operational risk.

A justified migration may still require a governed execution window.

64. Migration Sequence

Complex migrations may require staged transition.

Possible sequence:

Preparation → Parallel Validation → Partial Transition → Target-State Validation → Full Transition → Current- State Exit

The exact sequence should fit the governed object.

65. Phased Migration

Where uncertainty or materiality is high, migration may proceed through bounded phases.

Each phase may require renewed evidence before progression.

66. Partial Migration

Only part of the intelligence operating model may need to migrate.

Partial Migration may preserve effective components while replacing disproportionate ones.

67. Conditional Migration

Migration may be justified only if defined conditions are satisfied.

Possible conditions include:

validated Value equivalence,

cost threshold,

infrastructure readiness,

dependency reduction,

or successful transition testing.

68. Migration Condition Object

Each material Migration Condition should identify:

required state,

current state,

evidence source,

threshold,

review point,

and consequence of failure.

69. Migration Stop Condition

Migration should identify conditions requiring the transition to pause.

Examples may include:

Value deterioration,

validation failure,

unexpected dependency,

cost escalation,

or continuity failure.

70. Migration Abort Condition

Where appropriate, MDM should define conditions under which migration should be abandoned.

Abort conditions should be distinguished from temporary pause conditions.

71. Migration Reversal

A migration may need to return to the Current State.

Reversal feasibility should be evaluated before transition where material.

72. Migration Reversibility

Possible states may include:

Highly Reversible

Reversible

Conditionally Reversible

Difficult to Reverse

Effectively Irreversible

Greater irreversibility may justify stronger evidence requirements.

73. Rollback Capability

Where operationally appropriate, migration planning should identify whether rollback is technically and operationally possible.

Rollback capability may increase transition optionality.

74. Point of No Return

Some migrations cross a state after which reversal becomes materially difficult or impossible.

Where relevant, MDM should identify this:

Migration Commitment Threshold

before it is crossed.

75. Migration Continuity

Migration should consider whether required operational capability can remain available throughout transition.

Continuity requirements should correspond to operational criticality.

76. Migration Interruption

Temporary interruption may be acceptable for some systems and unacceptable for others.

MDM should preserve the applicable continuity requirement rather than assume zero downtime universally.

77. Migration Recovery

Where transition fails partially, MDM should support defined recovery pathways.

Recovery may include:

rollback,

partial restoration,

temporary dual operation,

or transition to another configuration.

78. Migration Confidence

Possible confidence states may include:

High Confidence

Moderate Confidence

Conditional

Evidence-Limited

Low Confidence

Conflicted

Unresolved

Confidence should reflect both Target-State evidence and transition evidence.

79. Migration Uncertainty

Uncertainty may concern:

Target-State Value,

transition cost,

compatibility,

resource requirements,

dependency,

or stabilization time.

Uncertainty should remain visible.

80. Migration Conflict

Evidence may support migration in one domain and oppose it in another.

For example:

cost may improve,

while transition risk and dependency increase.

MDM should preserve the conflict.

81. Migration Trade-Off

Migration trade-offs may include:

lower cost versus transition burden,

greater capability versus greater dependency,

lower energy versus higher hardware cost,

or reduced lock-in versus lower immediate performance.

82. Migration Sensitivity

MDM may identify assumptions that materially determine migration justification.

Examples include:

expected cost savings,

Target-State performance,

transition duration,

or future provider pricing.

83. Migration Scenario

Where uncertainty is material, multiple migration scenarios may be evaluated.

Examples may include:

immediate migration,

phased migration,

partial migration,

migration after contract expiration,

or continued operation.

84. No-Migration Alternative

The Current State should remain a legitimate comparison option where continuation is still justified.

Migration analysis should not assume that migration must occur simply because it is being evaluated.

85. Optimization-before-Migration Alternative

The Current State may become sufficiently proportionate through optimization.

MDM should distinguish:

Need to Migrate

from

Need to Improve Current Configuration.

86. Reconfiguration-before-Migration Alternative

Material improvement may be achievable through reconfiguration without full migration.

This alternative should remain visible where appropriate.

87. Migration Opportunity Bias

Organizations may prefer migration because a new technology appears strategically attractive.

Opportunity alone does not establish migration justification.

88. Novelty Bias

New technology should not receive automatic preference.

Newer Technology ≠ Better Governed Migration Outcome.

89. Benchmark Bias

Higher benchmark performance may support Target-State evidence.

It does not establish operational Value equivalence.

Benchmark Superiority ≠ Migration Superiority.

90. Vendor Claim Bias

Provider claims may inform candidate evaluation.

They should not replace governed evidence.

91. Cost-Saving Bias

Lower expected cost may be attractive.

But migration should preserve required Value and account for transition cost.

Cheaper Target State ≠ Better Migration by default.

92. Capability Bias

A more capable Target State may still be unnecessary.

Greater Capability ≠ Greater Migration Value.

93. Sunk-Cost Bias

Past investment in the Current State should not automatically prevent migration.

Historical Investment ≠ Future Configuration Justification.

94. Lock-In Bias

Difficulty leaving the Current State may affect migration feasibility.

It does not establish that continued dependence remains desirable.

95. Migration Momentum

Once migration begins, organizational momentum may encourage completion even when evidence changes.

MDM should preserve the ability to:

pause,

reassess,

or abort.

Migration Momentum ≠ Continued Migration Justification.

96. Migration Evidence Update

Observed evidence during migration should replace projections where possible.

Material divergence should trigger reassessment.

97. Migration Drift

Migration Drift occurs where the actual Target State materially differs from the Target State originally evaluated.

Drift may involve:

models,

providers,

agents,

infrastructure,

cost,

or Value mechanisms.

98. Migration Monitoring

Material Migration Conditions should be monitored throughout the transition.

Monitoring should focus on variables capable of changing migration justification.

99. Migration Review Trigger

Review may be triggered by:

Value deterioration,

validation failure,

cost escalation,

transition delay,

dependency change,

constraint change,

or Target-State drift.

100. Migration Outcome Evidence

After transition, actual evidence should be compared with the expected migration state.

Relevant evidence may include:

Value,

productivity,

resources,

cost,

sustainability,

dependency,

and operational continuity.

101. Migration Success

Migration success should not be defined merely as technical completion.

Technical Cutover ≠ Successful Migration.

A migration succeeds methodologically when the Target State achieves the required governed outcome within applicable constraints.

102. Migration Failure

Migration Failure may occur where:

required Value is not preserved,

Target-State evidence materially fails,

transition conditions cannot be satisfied,

or applicable constraints are violated.

Failure does not automatically determine retirement.

103. Post-Migration Stabilization

A Target State may require a stabilization period before its long-term performance can be evaluated.

Temporary transition effects should be distinguished from persistent Target-State failure.

104. Post-Migration Reassessment

After stabilization, the migrated capability should return to normal VEGA™ lifecycle governance.

Migration is not a permanent exemption from continued Value justification.

105. Migration-to-Retirement Boundary

Where:

Current State continuation is not justified,

no sufficiently viable Target State exists,

and migration cannot preserve required Value,

the evidence may proceed toward:

Retirement Decision Governance

MDM does not itself determine retirement.

106. Migration Decision Authority Boundary

MDM establishes the methodological migration state.

It does not authorize:

provider change,

model replacement,

infrastructure transition,

capital expenditure,

contract termination,

or operational cutover.

Governed Migration State ≠ Migration Authorization.

107. Automated Migration Assessment

Automated systems may support:

candidate discovery,

cost comparison,

simulation,

compatibility analysis,

or threshold monitoring.

Automated assessment does not create migration authority.

108. Governed Migration Decision State

The principal output of MDM is:

Governed Migration Decision State

Possible states may include:

Migrate

Migrate Conditionally

Phased Migration

Partial Migration

Prepare for Migration

Optimize before Migration

Reconfigure before Migration

Continue Current State

Defer Migration

Pause Migration

Abort Migration

Migration Not Supported

Evidence-Limited

Conflicted

Unresolved

The state should preserve:

Current State,

Target State,

Value basis,

transition feasibility,

migration conditions,

confidence,

uncertainty,

reversibility,

continuity,

and Decision Authority boundary.

109. Minimum Implementation Framework

A conforming implementation of MDM must provide exactly the following six capabilities:

1. Migration Object, Current-State & Target-State Governance

Capability to define the Migration Decision Object, Current Operating State, Target Operating State, migration boundary, horizon, context, trigger, and qualified Migration Candidates.

2. Migration Value & Comparative Governance

Capability to compare Value, productivity, resources, Computational Optimization, economics, Strategic Value, sustainability, dependency, attribution, and applicable constraints between Current and Target States.

3. Transition Feasibility & Continuity Governance

Capability to evaluate compatibility, data and state transition, configuration preservation, validation, transition cost, continuity, sequencing, recovery, rollback, and Migration Feasibility.

4. Migration Condition, Reversibility & Commitment Governance

Capability to define migration thresholds, conditions, Stop Conditions, Abort Conditions, reversibility, rollback capability, Migration Commitment Thresholds, and points of no return.

5. Migration Integrity, Monitoring & Outcome Governance

Capability to preserve uncertainty, scenarios, alternatives, bias controls, monitoring, Migration Drift, outcome evidence, stabilization, and post-migration reassessment.

6. DGS Retirement Decision Handoff Governance

Capability to produce a Governed Migration Decision State sufficiently explicit for Retirement Decision Governance where neither continued operation nor viable migration remains sufficiently justified.

110. Governance Logic

The canonical MDM governance logic is:

Governed Scaling Decision State / Governed Continuation Decision State

↓

Identify Migration Decision Object

↓

Establish Current Operating State

↓

Define Target Operating State

↓

Define Migration Boundary / Horizon / Context

↓

Identify Migration Trigger

↓

Identify / Qualify Migration Candidates

↓

Assess Current-State Evidence

↓

Assess Target-State Evidence

↓

Test Evidence Symmetry

↓

Establish Migration Value Baseline

↓

Assess Value Preservation / Improvement / Transformation

↓

Assess Productivity Comparison

↓

Assess Resource / Computational Comparison

↓

Assess Economic Migration Value

↓

Assess Strategic / Sustainability Migration Value

↓

Assess Dependency / Lock-In Change

↓

Assess Attribution Relevance

↓

Identify Applicable Governed Constraints

↓

Assess Compatibility

↓

Assess Validation / Equivalence

↓

Assess Transition Cost / Parallel Operation

↓

Assess Transition Feasibility

↓

Distinguish Migration Opportunity / Benefit / Feasibility / Necessity

↓

Assess Migration Timing / Urgency

↓

Evaluate Phased / Partial / Conditional Migration

↓

Evaluate No-Migration / Optimization / Reconfiguration Alternatives

↓

Assess Continuity / Recovery / Rollback

↓

Assess Reversibility / Commitment Threshold

↓

Assess Confidence / Uncertainty / Conflict

↓

Define Migration Conditions / Stop / Abort Conditions

↓

Determine Migration Decision State

↓

Define Monitoring / Review Triggers

↓

Preserve Decision Authority Boundary

↓

Establish Governed Migration Decision State

↓

Handoff to Retirement Decision Governance where applicable

111. Governance Outputs

MDM may produce:

Migration Decision Object

Current Operating State

Target Operating State

Migration Boundary

Migration Horizon

Migration Context

Migration Trigger

Migration Candidate Set

Candidate Qualification State

Current-State Evidence Profile

Target-State Evidence Profile

Evidence Symmetry State

Migration Evidence Sufficiency State

Migration Value Baseline

Value Preservation State

Value Improvement State

Value Transformation State

Transition Value-Loss State

Productivity Comparison State

Resource Comparison State

Computational Migration Value State

Model Migration State

Mechanism Migration State

Agent Architecture Migration State

Provider Migration State

Infrastructure Migration State

Hardware Migration State

Workflow Migration State

Human–AI Configuration Migration State

Economic Migration State

Migration Cost State

Transition Cost State

Migration Payback Horizon

Failure Spend During Migration State

Parallel Operation Cost State

Strategic Migration Value State

Sustainability Migration Value State

Dependency Change State

Lock-In Change State

Compatibility State

Data Migration State

State Migration State

Knowledge Preservation State

Configuration Preservation State

Migration Validation State

Equivalence Validation State

Transition Feasibility State

Migration Necessity State

Migration Urgency State

Migration Timing State

Migration Sequence

Migration Condition Object

Migration Stop Condition

Migration Abort Condition

Migration Reversibility State

Rollback Capability State

Migration Commitment Threshold

Migration Continuity State

Migration Recovery State

Migration Confidence State

Migration Uncertainty State

Migration Conflict State

Migration Trade-Off Record

Migration Sensitivity State

Migration Scenario

Migration Alternative Set

Migration Monitoring State

Migration Drift State

Migration Outcome Evidence

Migration Success State

Migration Failure State

Post-Migration Stabilization State

The principal output is:

Governed Migration Decision State

112. Critical Distinctions

MDM preserves the following distinctions:

Better Alternative ≠ Justified Migration

Reason to Evaluate Migration ≠ Reason to Execute Migration

Migration Opportunity ≠ Migration Justification

Migration Benefit ≠ Migration Feasibility

Migration Feasibility ≠ Migration Necessity

Current-State Weakness ≠ Target-State Suitability

Observed Current-State Evidence ≠ Projected Target-State Evidence

Newer Technology ≠ Better Governed Migration Outcome

Benchmark Superiority ≠ Migration Superiority

Greater Capability ≠ Greater Migration Value

Greater Model Capability ≠ Migration Necessity

Cheaper Target State ≠ Better Migration by default

Lower Cost + Lost Required Value ≠ Successful Migration

Infrastructure Feasibility ≠ Migration Justification

Compatibility ≠ Migration Justification

Dependency Reduction ≠ Dependency Elimination

Claimed Equivalence ≠ Validated Equivalence

Need to Improve Current Configuration ≠ Need to Migrate

Technical Cutover ≠ Successful Migration

Migration Momentum ≠ Continued Migration Justification

Historical Investment ≠ Future Configuration Justification

Migration Failure ≠ Automatic Retirement

Governed Migration State ≠ Migration Authorization

113. Cross-Architecture Boundary

MDM governs methodological justification for migration of an intelligence operating model within DGS.

DECM governs Decision Evidence Consolidation.

CDM governs Continuation Decision.

SDM governs Scaling Decision.

MDM governs Migration Decision.

RDM governs Retirement Decision.

VGS governs Value.

XGS governs execution.

IPS governs Intelligence Productivity.

RGS governs resources.

COS governs Computational Optimization.

IES governs Intelligence Execution Economics.

SVGS governs Strategic Value.

ISS governs Intelligence Sustainability.

VAS governs Value Attribution.

HAGA™ governs Harm.

LIGA™ governs Liability.

Relevant Accountability architectures govern Accountability.

VALIDOS™ may govern validation methodology.

ADIT® may govern broader evidence and auditability.

Relevant identity, memory, agent, autonomous-system, Operational Reality, and other competent architectures may govern their respective migration-relevant states.

MDM may consume those states.

It does not absorb their governed domains.

114. Canonical Boundary

MDM begins when a materially different Target Operating State is being considered as an alternative to the Current Operating State.

MDM governs:

Migration Decision Objects,

Current Operating States,

Target Operating States,

Migration Boundaries,

Migration Horizons,

Migration Contexts,

Migration Triggers,

Migration Candidates,

Candidate Qualification,

Current-State Evidence,

Target-State Evidence,

Evidence Symmetry,

Migration Evidence Sufficiency,

Migration Value Baselines,

Value Preservation,

Value Improvement,

Value Transformation,

transition Value loss,

Productivity Comparison,

Resource Comparison,

Computational Migration Value,

Model Migration,

Model Downsizing,

Model Upsizing,

Mechanism Migration,

No-Intelligence Migration,

Agent Architecture Migration,

Provider Migration,

Infrastructure Migration,

cloud-to-edge migration,

edge-to-cloud migration,

Hardware Migration,

Workflow Migration,

Human–AI Configuration Migration,

Economic Migration Value,

Migration Cost,

Transition Cost,

Migration Payback Horizon,

Failure Spend during migration,

Parallel Operation Cost,

Strategic Migration Value,

Sustainability Migration Value,

Dependency Reduction,

Dependency Transfer,

Lock-In Reduction,

New Lock-In,

Migration Compatibility,

Data Migration,

State Migration,

Knowledge Preservation,

Configuration Preservation,

Migration Validation,

Equivalence Validation,

Improvement Validation,

Transition Feasibility,

Migration Necessity,

Migration Urgency,

Migration Timing,

Migration Sequence,

Phased Migration,

Partial Migration,

Conditional Migration,

Migration Conditions,

Stop Conditions,

Abort Conditions,

Migration Reversal,

Migration Reversibility,

Rollback Capability,

Migration Commitment Threshold,

Migration Continuity,

Migration Interruption,

Migration Recovery,

confidence,

uncertainty,

conflict,

trade-offs,

sensitivity,

scenarios,

No-Migration Alternatives,

Optimization-before-Migration,

Reconfiguration-before-Migration,

migration integrity,

evidence updates,

Migration Drift,

monitoring,

review,

outcome evidence,

Migration Success,

Migration Failure,

stabilization,

and post-migration reassessment.

MDM does not independently authorize:

model replacement,

provider replacement,

infrastructure transition,

data transfer,

contract termination,

capital expenditure,

operational cutover,

or retirement.

MDM ends when the migration evidence has been represented as a:

Governed Migration Decision State

for competent authority consideration and, where applicable, subsequent Retirement Decision Governance.

115. Use Case 1 — A Smaller Model Can Now Do the Same Job

An organization operates a large reasoning model for a high-volume document-processing workflow.

The system continues to produce validated Value.

A newer smaller model demonstrates comparable validated completion quality while requiring substantially less:

compute,

energy,

latency,

and cost.

MDM does not migrate automatically because the smaller model appears more efficient.

It evaluates:

Value equivalence,

productivity,

transition cost,

integration compatibility,

validation,

provider dependency,

and rollback capability.

If the evidence supports the transition, the resulting state may be:

Migrate Conditionally

subject to production validation and Value-preservation thresholds.

The migration is justified not because the new model is smaller.

It is justified because the required Value can be preserved through a more proportionate operating state.

116. Use Case 2 — The Current Provider Works, but Dependency Has Become Critical

An organization operates a successful intelligence capability through one external provider.

Performance remains strong and current economics remain acceptable.

However, the system has become operationally critical and provider dependency has increased substantially.

An alternative configuration would reduce concentration but requires transition cost and temporary parallel operation.

MDM evaluates:

current Value,

dependency sustainability,

Target-State capability,

transition feasibility,

parallel cost,

continuity,

lock-in change,

and rollback.

The resulting state may be:

Phased Migration

even where immediate cost savings are limited.

The migration Value comes partly from reducing a critical lifecycle dependency.

Dependency reduction can create legitimate migration Value without requiring immediate performance improvement.

117. Canonical Closing Statement

Migration is not progress merely because something newer exists.

A new model may be faster without producing greater Value.

A new provider may be cheaper while creating a stronger dependency.

A new infrastructure configuration may reduce energy while increasing transition cost.

And a technically superior system may still be the wrong destination if the Value-producing conditions of the current system cannot survive the transition.

Migration therefore governs two states and the path between them.

The Current State matters.

The Target State matters.

And the transition between them matters.

Better Alternative ≠ Justified Migration.

Migration Benefit ≠ Migration Feasibility.

Migration Feasibility ≠ Migration Necessity.

Newer Technology ≠ Better Governed Migration Outcome.

Claimed Equivalence ≠ Validated Equivalence.

Technical Cutover ≠ Successful Migration.

Governed Migration State ≠ Migration Authorization.

The purpose of MDM is not to keep intelligence on old technology and not to push it toward new technology.

It is to determine when changing the operating model creates more governed Value than preserving it.

MDM governs the point where intelligence must prove not only that a better destination exists, but that the Value can survive the journey to it.