About LocalM™ AiD
Enterprise Architecture Principles for AI-Assisted Software Development Operations
What is LocalM™ AiD?
LocalM™ AiD (Local Model - AI-Integrated Development) is an Enterprise Architecture Framework that provides governance principles for organizations adopting AI-assisted software development tools.
The Name
- LocalM™ - Emphasizes that AI should operate within defined local boundaries and permissions
- AiD - AI-integrated Development; also suggests the framework can “aid” proper adoption
Framework Scope
LocalM™ AiD is narrowly focused on AI tool operations, NOT general software engineering:
| ✅ IN SCOPE | ❌ OUT OF SCOPE |
|---|---|
| AI tool configuration | Software design patterns |
| Agent permissions & sandboxing | Architecture styles |
| Git access controls for AI | General testing methodology |
| Data classification for AI | DevOps practices (general) |
| Audit trails & compliance | Coding standards |
| Maturity progression | Technology stack decisions |
Core Tenets
Five foundational beliefs underpin every principle:
| Tenet | Statement |
|---|---|
| Human Agency | The programmer directs; AI assists |
| Structured Interaction | Methodology over “vibe coding” |
| Continuous Validation | Quality gates throughout the lifecycle |
| Traceability | All AI interactions documented and auditable |
| Progressive Maturity | Grow capability responsibly |
Why This Framework?
The Problem
Organizations are rapidly adopting AI coding assistants without:
- Clear governance frameworks
- Defined permission boundaries
- Quality assurance processes
- Risk management approaches
The Solution
LocalM™ AiD provides:
- 27 actionable principles across 7 categories
- Maturity model for progressive adoption
- Compliance checklists for governance
- Implementation guides for practitioners
Framework Structure
TOGAF Alignment
Every principle follows a modified TOGAF structure:
- Statement - Clear, actionable principle
- Rationale - Why this matters (technical, business, risk, strategic)
- Implications - What changes when applied
- Maturity Alignment - Requirements at L1/L2/L3
- Governance - Compliance measures and exceptions
- Related Principles - Cross-references
Seven Categories
| Code | Category | Principles |
|---|---|---|
| PS | Planning & Strategy | 4 |
| TSI | Tool Selection & Integration | 3 |
| TTA | Team Training & Adoption | 3 |
| DC | Development & Coding | 6 |
| TQC | Testing & Quality Control | 3 |
| DM | Deployment & Maintenance | 2 |
| GSC | Governance, Security & Compliance | 10 |
Research Foundation
LocalM™ AiD synthesizes insights from academic research, industry practitioners, and emerging standards.
Key Sources
| Source | Key Contribution |
|---|---|
| AI4SE Taxonomy | AI classification in SE lifecycle |
| V-Bounce Model | AI-native SDLC methodology |
| Ten Simple Rules | Evidence-based coding guidelines |
| Metacognitive Framework | AI education principles |
| Single Conversation | Session management patterns |
| Security Guidelines | Security rules for AI agents |
See Research Sources for complete bibliography.
Explore the Framework
- Principles Overview - Browse all 27 governance principles
- Implementation Guides - Practical guidance for adoption
- Research Sources - Academic and industry foundation
- Community - Join the discussion on r/agentic_sdlc
How to Contribute
We follow Build-in-Public principles. All feedback is welcome through our community channels.
See How to Contribute for details.