Context Driven Development

Context-Driven Development

Guide for implementing and maintaining context as a managed artifact alongside code, enabling consistent AI interactions and team alignment through structured project documentation.

When to Use This Skill

• Setting up new projects with structured context
• Understanding the relationship between context artifacts
• Maintaining consistency across AI-assisted development sessions
• Onboarding team members to an existing project
• Deciding when to update context documents
• Managing greenfield vs brownfield project contexts

Core Philosophy

Context-Driven Development treats project context as a first-class artifact managed alongside code. Instead of relying on ad-hoc prompts or scattered documentation, establish a persistent, structured foundation that informs all AI interactions.

Key principles:

1. Context precedes code: Define what you're building and how before implementation
2. Living documentation: Context artifacts evolve with the project
3. Single source of truth: One canonical location for each type of information
4. AI alignment: Consistent context produces consistent AI behavior

The Workflow

Follow the Context → Spec & Plan → Implement workflow:

1. Context Phase: Establish or verify project context artifacts exist and are current
2. Specification Phase: Define requirements and acceptance criteria for work units
3. Planning Phase: Break specifications into phased, actionable tasks
4. Implementation Phase: Execute tasks following established workflow patterns

Artifact Relationships

product.md - Defines WHAT and WHY

Purpose: Captures product vision, goals, target users, and business context.

Contents:

• Product name and one-line description
• Problem statement and solution approach
• Target user personas
• Core features and capabilities
• Success metrics and KPIs
• Product roadmap (high-level)

Update when:

• Product vision or goals change
• New major features are planned
• Target audience shifts
• Business priorities evolve

product-guidelines.md - Defines HOW to Communicate

Purpose: Establishes brand voice, messaging standards, and communication patterns.

Contents:

• Brand voice and tone guidelines
• Terminology and glossary
• Error message conventions
• User-facing copy standards
• Documentation style

Update when:

• Brand guidelines change
• New terminology is introduced
• Communication patterns need refinement

tech-stack.md - Defines WITH WHAT

Purpose: Documents technology choices, dependencies, and architectural decisions.

Contents:

• Primary languages and frameworks
• Key dependencies with versions
• Infrastructure and deployment targets
• Development tools and environment
• Testing frameworks
• Code quality tools

Update when:

• Adding new dependencies
• Upgrading major versions
• Changing infrastructure
• Adopting new tools or patterns

workflow.md - Defines HOW to Work

Purpose: Establishes development practices, quality gates, and team workflows.

Contents:

• Development methodology (TDD, etc.)
• Git workflow and commit conventions
• Code review requirements
• Testing requirements and coverage targets
• Quality assurance gates
• Deployment procedures

Update when:

• Team practices evolve
• Quality standards change
• New workflow patterns are adopted

tracks.md - Tracks WHAT'S HAPPENING

Purpose: Registry of all work units with status and metadata.

Contents:

• Active tracks with current status
• Completed tracks with completion dates
• Track metadata (type, priority, assignee)
• Links to individual track directories

Update when:

• New tracks are created
• Track status changes
• Tracks are completed or archived

Context Maintenance Principles

Keep Artifacts Synchronized

Ensure changes in one artifact reflect in related documents:

• New feature in product.md → Update tech-stack.md if new dependencies needed
• Completed track → Update product.md to reflect new capabilities
• Workflow change → Update all affected track plans

Update tech-stack.md When Adding Dependencies

Before adding any new dependency:

1. Check if existing dependencies solve the need
2. Document the rationale for new dependencies
3. Add version constraints
4. Note any configuration requirements

Update product.md When Features Complete

After completing a feature track:

1. Move feature from "planned" to "implemented" in product.md
2. Update any affected success metrics
3. Document any scope changes from original plan

Verify Context Before Implementation

Before starting any track:

1. Read all context artifacts
2. Flag any outdated information
3. Propose updates before proceeding
4. Confirm context accuracy with stakeholders

Greenfield vs Brownfield Handling

Greenfield Projects (New)

For new projects:

1. Create all artifacts interactively
2. Answer questions about product vision, tech preferences, and workflow
3. Generate initial style guides for chosen languages
4. Create empty tracks registry

Characteristics:

• Full control over context structure
• Define standards before code exists
• Establish patterns early

Brownfield Projects (Existing)

For existing codebases:

1. Analyze existing code, configs, and documentation
2. Pre-populate artifacts based on discovered patterns
3. Review and refine generated context
4. Reconcile existing patterns with desired patterns

Characteristics:

• Extract implicit context from existing code
• Reconcile existing patterns with desired patterns
• Document technical debt and modernization plans
• Preserve working patterns while establishing standards

Benefits

Team Alignment

• New team members onboard faster with explicit context
• Consistent terminology and conventions across the team
• Shared understanding of product goals and technical decisions

AI Consistency

• AI assistants produce aligned outputs across sessions
• Reduced need to re-explain context in each interaction
• Predictable behavior based on documented standards

Institutional Memory

• Decisions and rationale are preserved
• Context survives team changes
• Historical context informs future decisions

Quality Assurance

• Standards are explicit and verifiable
• Deviations from context are detectable
• Quality gates are documented and enforceable

Directory Structure

.claude/context/
├── product.md            # Product vision and goals
├── product-guidelines.md # Communication standards
├── tech-stack.md         # Technology preferences
├── workflow.md           # Development practices
├── tracks.md             # Work unit registry
└── tracks/
    └── <track-id>/
        ├── spec.md
        ├── plan.md
        ├── metadata.json
        └── index.md

Context Lifecycle

1. Creation: Initial setup
2. Validation: Verify before each track
3. Evolution: Update as project grows
4. Synchronization: Keep artifacts aligned
5. Archival: Document historical decisions

Context Validation Checklist

Before starting implementation on any track, validate context:

Product Context

• product.md reflects current product vision
• Target users are accurately described
• Feature list is up to date
• Success metrics are defined

Technical Context

• tech-stack.md lists all current dependencies
• Version numbers are accurate
• Infrastructure targets are correct
• Development tools are documented

Workflow Context

• workflow.md describes current practices
• Quality gates are defined
• Coverage targets are specified
• Commit conventions are documented

Track Context

• tracks.md shows all active work
• No stale or abandoned tracks
• Dependencies between tracks are noted

Common Anti-Patterns

Avoid these context management mistakes:

Stale Context

Problem: Context documents become outdated and misleading. Solution: Update context as part of each track's completion process.

Context Sprawl

Problem: Information scattered across multiple locations. Solution: Use the defined artifact structure; resist creating new document types.

Implicit Context

Problem: Relying on knowledge not captured in artifacts. Solution: If you reference something repeatedly, add it to the appropriate artifact.

Context Hoarding

Problem: One person maintains context without team input. Solution: Review context artifacts in pull requests; make updates collaborative.

Over-Specification

Problem: Context becomes so detailed it's impossible to maintain. Solution: Keep artifacts focused on decisions that affect AI behavior and team alignment.

Integration with Development Tools

IDE Integration

Configure your IDE to display context files prominently:

• Pin product.md for quick reference
• Add tech-stack.md to project notes
• Create snippets for common patterns from style guides

Git Hooks

Consider pre-commit hooks that:

• Warn when dependencies change without tech-stack.md update
• Remind to update product.md when feature branches merge
• Validate context artifact syntax

CI/CD Integration

Include context validation in pipelines:

• Check tech-stack.md matches actual dependencies
• Verify links in context documents resolve
• Ensure tracks.md status matches git branch state

Session Continuity

Support multi-session development through context persistence:

Starting a New Session

1. Read product.md to orient yourself
2. Check tracks.md for active work
3. Review relevant track's plan.md for current task
4. Verify context artifacts are current

Ending a Session

1. Update plan.md with current progress
2. Note any blockers or decisions made
3. Commit in-progress work with clear status
4. Update tracks.md if status changed

Handling Interruptions

If interrupted mid-task:

1. Mark task as [~] with note about stopping point
2. Commit work-in-progress to feature branch
3. Document any uncommitted decisions in plan.md

Best Practices

1. Read context first: Always read relevant artifacts before starting work
2. Small updates: Make incremental context changes, not massive rewrites
3. Link decisions: Reference context when making implementation choices
4. Version context: Commit context changes alongside code changes
5. Review context: Include context artifact reviews in code reviews
6. Validate regularly: Run context validation checklist before major work
7. Communicate changes: Notify team when context artifacts change significantly
8. Preserve history: Use git to track context evolution over time
9. Question staleness: If context feels wrong, investigate and update
10. Keep it actionable: Every context item should inform a decision or behavior

Iron Laws

1. ALWAYS read all relevant context artifacts (product.md, tech-stack.md, workflow.md) before starting any implementation track — never begin coding against stale or unverified context.
2. NEVER create a new artifact type or document location when an existing category in the defined directory structure already fits — resist context sprawl.
3. ALWAYS update context artifacts atomically with code changes in the same commit — context updates in separate PRs create drift and stale references.
4. NEVER let any context file exceed 20KB without rotating or archiving — unbounded growth makes context unusable and slows AI interactions.
5. ALWAYS flag stale or contradictory context before implementation — an outdated tech-stack.md or wrong product.md is technical debt that compounds with every AI interaction.

Memory Protocol (MANDATORY)

Before starting:

cat .claude/context/memory/learnings.md

After completing:

• New pattern -> .claude/context/memory/learnings.md
• Issue found -> .claude/context/memory/issues.md
• Decision made -> .claude/context/memory/decisions.md

ASSUME INTERRUPTION: If it's not in memory, it didn't happen.