SAFe Alignment Guide

Integrating LocalM™ AiD AI governance principles across SAFe levels for enterprise-scale AI-assisted development.

FRAMEWORK SAFe 6.0

AUDIENCE Agile Leaders & Architects

ALIGNMENT Level Mapping

STATUS ✅ Available

Overview

SAFe (Scaled Agile Framework) enables enterprise agility through four configuration levels. LocalM™ AiD principles integrate at each level to govern AI-assisted development at scale—from individual team practices to portfolio-level strategy.

flowchart TB
    subgraph safe["SAFe Levels"]
        portfolio["Portfolio"]
        solution["Large Solution"]
        essential["Essential"]
        team["Team"]
    end

    subgraph localm["LocalM™ AiD Integration"]
        ps["PS: Strategy<br/>& Planning"]
        gsc["GSC: Governance<br/>& Compliance"]
        dc["DC: Development<br/>& Coding"]
        tqc["TQC: Testing<br/>& Quality"]
    end

    portfolio --> ps
    portfolio --> gsc
    solution --> gsc
    essential --> dc
    team --> dc
    team --> tqc

    style safe fill:#1a1a2e,stroke:#4361ee
    style localm fill:#1a1a2e,stroke:#00ff94

SAFe Portfolio Level

Strategic Themes and AI Governance

SAFe Focus: Portfolio strategy, budgeting, Lean governance

LocalM™ AiD Alignment:

LocalM™ AiD Principle	SAFe Integration
PS-001: Architecture First	Include AI governance in Strategic Themes
PS-002: AI Integration Strategy	Define AI adoption as Portfolio Epic
PS-004: Risk-Based Adoption	Add AI risks to Lean Portfolio Management

Enabler Epics for AI Governance

Enabler Epic	LocalM™ AiD Principle	Description
AI Governance Foundation	GSC-001	Establish enterprise AI governance framework
AI Tool Platform	TSI-001, TSI-002	Build approved AI tool ecosystem
AI Security Baseline	GSC-003, GSC-006	Implement AI security controls
AI Training Program	TTA-001, TTA-002	Enable organization-wide AI readiness

Portfolio Kanban AI Governance Items

AI governance policy reviews
AI tool evaluations
AI security assessments
AI compliance audits

SAFe Large Solution Level

Solution Train AI Governance

SAFe Focus: Coordinating multiple ARTs, solution-level architecture

LocalM™ AiD Alignment:

LocalM™ AiD Principle	SAFe Integration
GSC-001: Governance Framework	Solution governance includes AI controls
TSI-003: Interoperability & Portability	Cross-ART AI tool standardization
GSC-007: Audit & Accountability	Solution-level AI audit requirements

Solution Intent AI Extensions

Artifact	AI Governance Content
Solution Context	AI tools in solution scope
Fixed Intent	AI security and compliance requirements
Variable Intent	AI capability evolution
Compliance	AI regulatory requirements

SAFe Essential Level

ART-Level AI Governance

SAFe Focus: Agile Release Train coordination, PI Planning, Architectural Runway

LocalM™ AiD Alignment:

LocalM™ AiD Principle	SAFe Integration
DC-001: Human-AI Collaboration	Define AI collaboration patterns for ART
DC-002: Iterative Development	Include AI governance in PI objectives
GSC-003: Access Control	ART-level AI tool access policies

PI Planning AI Considerations

Program Board AI Items:

AI tool configuration across teams
AI-generated code review dependencies
AI security validation milestones

PI Objectives AI Examples:

“Implement AI code review gates for all teams”
“Achieve 100% AI tool access control compliance”
“Complete AI security training for ART”

System Demo AI Governance

Demonstrate AI-assisted development practices
Show AI code review compliance metrics
Present AI security posture

SAFe Team Level

Team-Level AI Practices

SAFe Focus: Agile team practices, iteration execution, built-in quality

LocalM™ AiD Alignment:

LocalM™ AiD Principle	SAFe Integration
DC-004: Code Review & Validation	AI output review in Definition of Done
DC-005: Responsible AI Usage	Team AI usage agreements
TQC-001: AI-Output Testing	AI-specific testing in iteration
TQC-002: Quality Assurance Integration	AI quality in CI/CD

Definition of Done AI Extensions

## DoD - AI Governance Extensions

- [ ] AI-generated code reviewed by human developer
- [ ] AI suggestions documented in commit message
- [ ] AI tool usage logged for audit trail
- [ ] Security scan completed on AI-assisted code
- [ ] No sensitive data exposed to AI tools

Team Iteration AI Practices

Practice	AI Governance Element
Iteration Planning	Identify AI-heavy stories, allocate review time
Daily Standup	Share AI tool learnings, flag concerns
Code Review	Apply AI-specific review criteria
Iteration Retrospective	Reflect on AI collaboration effectiveness

Built-in Quality and AI

Test-First AI Integration

Quality Practice	AI Governance Integration
Test-Driven Development	Write tests before AI generates code
Behavior-Driven Development	Human-written acceptance criteria, AI implementation
Continuous Integration	AI code passes same gates as human code
Automated Testing	AI-generated code has test coverage requirements

Architectural Runway AI Extensions

Runway Element	AI Governance Content
Technical Foundation	AI tool infrastructure, integration APIs
Enabler Capabilities	AI security controls, audit mechanisms
Patterns	AI collaboration patterns, review workflows
Standards	AI coding standards, prompt guidelines

DevOps and AI Governance

Continuous Delivery Pipeline AI Gates

flowchart LR
    dev["Development"]
    review["AI Review Gate"]
    test["Testing"]
    security["Security Scan"]
    audit["Audit Log"]
    deploy["Deployment"]

    dev --> review --> test --> security --> audit --> deploy

    style review fill:#00ff94,stroke:#00cc77
    style audit fill:#00ff94,stroke:#00cc77

Pipeline Stage	AI Governance Gate
Commit	AI usage logged
Build	AI-generated code identified
Test	AI-specific test coverage verified
Security	AI code security scan
Release	AI compliance audit complete

Release on Demand AI Considerations

AI tool versions in release notes
AI-generated component inventory
AI security clearance verification

Continuous Learning and AI

Inspect & Adapt AI Focus

I&A Component	AI Governance Activity
PI System Demo	Demonstrate AI governance metrics
Quantitative Measurement	AI tool effectiveness, quality impact
Retrospective	AI collaboration improvements
Problem Solving	Address AI governance gaps

Innovation and Planning AI Time

Explore new AI tools and capabilities
Develop AI governance improvements
Create AI collaboration experiments
Build AI training content

SAFe Core Values and AI Governance

SAFe Core Value	AI Governance Alignment
Alignment	AI governance aligned with business strategy
Built-in Quality	AI code meets same quality standards
Transparency	AI usage visible and auditable
Program Execution	AI enables, doesn’t impede delivery

Implementation Roadmap

Stage 1: Foundation (Team Level)

Focus: Establish team-level AI practices

Activities:

Add AI governance to Definition of Done
Train teams on AI code review practices
Implement AI logging in CI/CD

LocalM™ AiD Principles: DC-004, DC-005, TQC-001

Stage 2: Coordination (Essential Level)

Focus: Coordinate AI governance across ART

Activities:

Include AI governance in PI Planning
Establish ART-level AI policies
Implement cross-team AI standards

LocalM™ AiD Principles: DC-001, DC-002, GSC-003

Stage 3: Scaling (Large Solution/Portfolio)

Focus: Enterprise-scale AI governance

Activities:

Define AI governance Strategic Themes
Create Enabler Epics for AI capability
Establish portfolio-level AI governance

LocalM™ AiD Principles: PS-001, PS-002, GSC-001, GSC-007

SAFe Roles and AI Governance

SAFe Role	AI Governance Responsibility
Release Train Engineer	Coordinate AI governance across ART
System Architect	Define AI integration architecture
Product Manager	Prioritize AI governance features
Scrum Master	Facilitate AI governance practices
Developer	Follow AI collaboration practices

Next Steps

Assess your SAFe level - Determine which SAFe configurations you’re using
Map current practices - Identify existing AI governance practices
Identify gaps - Determine where LocalM™ AiD principles address needs
Prioritize by level - Start with Team level, scale up
Integrate incrementally - Add AI governance to existing ceremonies

SAFe Alignment Guide

Overview

SAFe Portfolio Level

Strategic Themes and AI Governance

Enabler Epics for AI Governance

Portfolio Kanban AI Governance Items

SAFe Large Solution Level

Solution Train AI Governance

Solution Intent AI Extensions

SAFe Essential Level

ART-Level AI Governance

PI Planning AI Considerations

System Demo AI Governance

SAFe Team Level

Team-Level AI Practices

Definition of Done AI Extensions

Team Iteration AI Practices

Built-in Quality and AI

Test-First AI Integration

Architectural Runway AI Extensions

DevOps and AI Governance

Continuous Delivery Pipeline AI Gates

Release on Demand AI Considerations

Continuous Learning and AI

Inspect & Adapt AI Focus

Innovation and Planning AI Time

SAFe Core Values and AI Governance

Implementation Roadmap

Stage 1: Foundation (Team Level)

Stage 2: Coordination (Essential Level)

Stage 3: Scaling (Large Solution/Portfolio)

SAFe Roles and AI Governance

Next Steps

Related Resources