Technical Governance

Documentation-First Engineering

This project was built using a Documentation-First approach, where comprehensive governance documents, architecture specifications, and engineering standards were written before and during development. These documents served as the foundation for both human decision-making and AI-assisted implementation.

The Philosophy

Rather than writing code first and documenting later, this project inverts the traditional workflow:

1. Define Intent — Engineering standards, architecture decisions, and governance principles are captured in markdown documents
2. Establish Governance — Clear rules, quality gates, and decision-making frameworks are documented
3. Build with Guidance — Code is written with these documents as the source of truth, ensuring consistency and alignment
4. AI as Co-Pilot — AI tools (like Cursor) use these documents to understand context, make informed suggestions, and maintain architectural integrity

Spec-Driven Development (SDD) in Practice

Core Governance Documents

The project's technical governance is defined through several key documents:

Engineering Standards (docs/ENGINEERING_STANDARDS.md)

A comprehensive north-star document that captures engineering intent across:

• Architectural Foundations — Modular, component-based architecture principles
• Frontend Engineering Standards — Code quality, component engineering, and design system guidelines
• Accessibility (A11y) — WCAG 2.1 AA targets, testing practices, and tooling
• Security Hardening — Runtime security, build-time checks, and authentication patterns
• Performance & Web Vitals — Core Web Vitals targets, Lighthouse thresholds, and optimization strategies
• SEO & Discoverability — Technical SEO, structured data, and content optimization
• Testing Standards — Unit, integration, and E2E testing expectations with coverage thresholds
• Design System Standards — Design tokens, component guidelines, and documentation practices

This document serves as the single source of truth for what "good" looks like in this codebase.

Solution-Agnostic Policy and SDD

• The machine-readable SDD at /sdd.yaml is authoritative for principles, boundaries, and CI expectations.
• Governance and standards are solution-agnostic: technology choices may evolve, but the principles must remain intact.
• Any change that affects architecture or cross-cutting concerns should update the SDD and relevant documentation in the same PR.

Architecture Overview (docs/ARCHITECTURE.md)

Defines the technical architecture including:

• System components and their relationships
• Technology stack decisions (Next.js, React, Tailwind, etc.)
• Content architecture (Markdown + Contentlayer)
• Deployment model (Vercel)
• Key data flows and integrations

Engineering Constitution (docs/CONSTITUTION.md)

Establishes how the repository is run and maintained:

• Principles — Single Source of Truth, Quality Over Volume, Accessibility First, SEO as a Feature
• Decision-Making — How architectural decisions are documented and made
• Change Process — PR workflow, quality gates, and CI expectations
• Coverage & Testing — Minimum thresholds (90% lines, 85% branches, 90% functions)
• Automation & Bots — Dependabot, auto-merge policies, release notes

Additional Governance Documents

• Design System (docs/DESIGN_SYSTEM.md) — Visual design tokens, component patterns, usage guidelines
• Accessibility Guidelines (docs/ACCESSIBILITY.md) — Technical accessibility practices and tooling
• SEO Guide (docs/SEO_GUIDE.md) — SEO implementation patterns and best practices
• Error Handling (docs/ERROR_HANDLING.md) — Error boundaries, logging, and monitoring strategies
• Security Policy (docs/SECURITY_POLICY.md) — Security practices and vulnerability reporting

How AI-Assisted Development Works

Context-Aware Development

With comprehensive documentation in place, AI tools can:

1. Understand Intent — By reading ENGINEERING_STANDARDS.md, AI understands the quality bar, architectural patterns, and coding standards
2. Maintain Consistency — When suggesting code, AI references the design system, accessibility guidelines, and testing standards
3. Enforce Governance — AI can flag deviations from documented standards and suggest corrections
4. Generate Tests — Coverage thresholds and testing patterns guide AI to generate appropriate test suites
5. Document Decisions — AI helps maintain documentation as code evolves

Example Workflow

When implementing a new feature:

1. Reference Standards — AI reads ENGINEERING_STANDARDS.md to understand component patterns, accessibility requirements, and testing expectations
2. Check Architecture — AI consults ARCHITECTURE.md to ensure the implementation aligns with system design
3. Apply Design System — AI uses DESIGN_SYSTEM.md to suggest appropriate design tokens and component patterns
4. Generate Tests — AI creates tests that meet coverage thresholds defined in CONSTITUTION.md
5. Maintain Documentation — AI helps update relevant docs if the feature introduces new patterns

Benefits of This Approach

For Development

• Faster Onboarding — New contributors (human or AI) can understand the project quickly through documentation
• Consistent Quality — Standards are explicit, not implicit, reducing variance in code quality
• Reduced Technical Debt — Decisions are documented, making it easier to understand "why" and avoid regressions
• Better AI Assistance — AI tools have rich context to provide more accurate suggestions

For Maintenance

• Clear Decision History — Architecture decisions are captured, not lost in commit messages
• Easier Refactoring — Understanding original intent helps make safe changes
• Quality Gates — CI/CD enforces documented standards automatically
• Living Documentation — Docs evolve with the codebase, staying current

For Collaboration

• Shared Understanding — Everyone (including AI) works from the same source of truth
• Explicit Trade-offs — Decisions and their rationale are documented
• Governance as Code — Standards are version-controlled and reviewable
• Transparency — Project structure and quality expectations are clear

Implementation Details

Documentation Structure

All governance documents live in the docs/ directory:

docs/
├── ENGINEERING_STANDARDS.md  # North-star engineering intent
├── ARCHITECTURE.md           # Technical architecture
├── CONSTITUTION.md           # Repository governance
├── DESIGN_SYSTEM.md          # Visual design system
├── ACCESSIBILITY.md          # A11y guidelines
├── SEO_GUIDE.md              # SEO practices
├── ERROR_HANDLING.md         # Error management
└── SECURITY_POLICY.md        # Security practices

CI/CD Integration

Documentation standards are enforced through:

• Linting — ESLint rules enforce code quality standards
• Type Checking — TypeScript strict mode ensures type safety
• Testing — Coverage thresholds enforce testing standards
• Accessibility — Automated a11y checks in CI
• Security — CodeQL and dependency scanning
• Performance — Lighthouse CI enforces performance budgets

Version Control

All documentation is:

• Version-Controlled — Tracked in Git alongside code
• Reviewable — Changes go through PR review
• Linked — Documents reference each other for context
• Living — Updated as the project evolves

Future Considerations

This documentation-first approach scales well:

• Team Growth — New team members can onboard quickly
• AI Evolution — As AI tools improve, richer context yields better results
• Knowledge Preservation — Institutional knowledge is captured, not lost
• Compliance — Standards can be audited and verified
• Tooling — Documentation can drive automated tooling and checks

Related Documentation

For developers and contributors:

• Tech Stack — Complete technology stack and tooling overview
• Engineering Standards — Comprehensive engineering intent
• Architecture Overview — Technical architecture
• Engineering Constitution — Repository governance
• Design System — Visual design tokens and patterns
• Accessibility Guidelines — Technical a11y practices

Issue Templates and Community Feedback

The repository uses structured issue templates to facilitate bug reports, feature requests, and documentation improvements:

• Bug Reports — Structured form for reporting functional issues with browser/device context
• Feature Requests — Template for proposing enhancements with use case and priority assessment
• Documentation Issues — Form for reporting documentation gaps or improvements

Issue templates ensure consistency, capture necessary context, and integrate with CI/CD workflows through automatic labeling. Security vulnerabilities should be reported privately through GitHub Security Advisories rather than public issues.

See .github/ISSUE_TEMPLATE/ for template definitions and usage guidelines.

Last Updated

This technical governance documentation was last reviewed and updated on December 2, 2025.