ADR Methodology
Structured frameworks for documenting architectural decisions with human-in-the-loop AI assistance.
Core Principle
AI handles drafting, formatting, and enumeration. Humans provide project-specific context, stakeholder awareness, and final decision accountability.
AI assists with:
- •Research and enumeration of options
- •Consistent formatting
- •Risk/trade-off summarization
- •Matrix generation
Humans provide:
- •Project-specific context and constraints
- •Stakeholder empathy and political nuance
- •Final decision accountability
Workflow Stages
Stage 1: Context to Criteria (/adr-assistant:new)
Gather decision context and generate assessment criteria.
- •Ask for problem description, constraints, stakeholders, initial options
- •Select appropriate framework (Salesforce Well-Architected or Technical Trade-off)
- •Generate criteria grouped by framework pillars
- •For each criterion: name, rationale for this decision, definition of "good"
- •Write criteria to
.claude/adr-session.yaml - •Prompt user to refine criteria before analysis
Stage 2: Options Matrix (/adr-assistant:analyze)
Evaluate options against criteria with risk ratings.
- •Read criteria from
.claude/adr-session.yaml - •For each option, rate against each criterion (Low/Medium/High risk)
- •Include rationale for each rating
- •Generate comparison matrix table
- •Write analysis to state file
- •Prompt user to refine ratings before generation
Stage 3: ADR Generation (/adr-assistant:generate)
Output final ADR document using MADR template.
- •Read criteria and analysis from state file
- •Ask user which option they're choosing and why
- •Generate ADR with AI disclosure
- •Auto-detect next ADR number from
docs/adr/ - •Write ADR file
- •Clear state file
Assessment Frameworks
Salesforce Well-Architected (Trusted/Easy/Adaptable)
Use for enterprise decisions with security, UX, and scale concerns.
Trusted: Data security, compliance, access control, audit/governance Easy: User experience, deployment complexity, integration effort, maintenance Adaptable: Scalability, future flexibility, cost trajectory, team skill alignment
Technical Trade-off Framework
Use for infrastructure and tooling decisions.
Operational: Setup complexity, maintenance burden, monitoring, failure modes Development: Learning curve, velocity, testing approach, documentation quality Integration: Ecosystem compatibility, migration path, dependency management, lock-in risk
Custom Framework
When neither standard framework fits:
- •Extract 3-5 key decision drivers from context
- •Create criteria that directly measure those drivers
- •Ensure criteria are evaluatable (not vague)
- •Include at least one "reversibility" criterion
Risk Ratings
| Rating | Definition | Governance |
|---|---|---|
| Low | Minimal risk to requirements, performance, or scale | Standard review |
| Medium | Manageable risk with proper governance | Documented mitigation |
| High | Significant risk without active mitigation | Explicit acceptance |
Assign Low when: Option aligns naturally, no significant trade-offs, team has experience, reversible Assign Medium when: Trade-offs exist but manageable, requires discipline, some learning curve, partially reversible Assign High when: Conflicts with requirement, requires significant mitigation, team lacks experience, hard to reverse
Consistency rule: At least one option should be Low or Medium for each criterion. If all options are High, the criterion may be a blocker rather than a trade-off.
State File Format
State persists to .claude/adr-session.yaml:
topic: "Database selection for user service"
status: "analyzed" # new | criteria_defined | analyzed
framework: "technical" # salesforce | technical | custom
criteria:
- name: "Data consistency"
pillar: "Operational"
rationale: "ACID compliance needed for financial data"
good_looks_like: "Full transaction support with rollback"
options:
- name: "PostgreSQL"
ratings:
"Data consistency":
risk: "Low"
rationale: "Full ACID support, mature transaction handling"
ADR Output Format
Use MADR template. Include AI disclosure section:
## AI Disclosure This ADR was drafted with AI assistance (Claude). Assessment criteria and rationale were reviewed by decision-makers listed above. Final decision made by humans.
Additional Resources
Reference Files
For detailed templates and frameworks, consult:
- •
references/templates.md- Complete ADR templates (MADR, Nygard, Y-statement) - •
references/criteria-frameworks.md- Detailed assessment criteria by framework - •
references/risk-ratings.md- Comprehensive risk rating guidelines