Working with AI assistants on complex features hits an inevitable wall: context window limitations. Here's the methodology that transforms marathon debugging sessions into efficient, successful implementations.

The Context Window Challenge

You've been there: three hours into implementing a complex feature with your AI assistant, everything is going well, when suddenly the responses become less helpful. Implementation details from earlier in the session start getting forgotten. You find yourself re-explaining decisions you made an hour ago.

The AI's context window is full, and older context has been "compacted" or dropped entirely. What started as productive collaboration devolves into frustration as you lose the shared understanding you'd built.

Symptoms of Context Overflow

• Lost implementation details from earlier in the session
• Repeated questions about already-discussed decisions
• Inconsistent code patterns across the feature
• Wasted time re-explaining context
• Decreasing quality of suggestions and solutions

The Solution: Phased Development

Instead of attempting to complete an entire feature in one marathon session, break it into discrete phases that can each be completed within a single context window. The key is meticulous documentation between phases.

Core Principle

Each phase should be atomic, testable, and completely documented for handoff to the next session.

The Four-Phase Pattern

Here's the approach that worked brilliantly for a recent optimization feature implementation:

Phase 1: Backend Infrastructure

Duration: ~2 hours

• Build core services and data models
• Implement database schema
• Create API endpoints
• Result: Self-contained, testable backend

Phase 2: Integration Layer

Duration: ~1.5 hours

• Connect backend to existing systems
• Modify service providers
• Add state management
• Result: Backend fully integrated

Phase 3: Frontend Components

Duration: ~1.5 hours

• Create UI components in isolation
• Build hooks for state management
• Design without integration
• Result: Complete UI toolkit ready to plug in

Phase 4: UI Integration

Duration: ~1 hour

• Wire components into existing pages
• Remove deprecated UI elements
• Final testing and refinement
• Result: Feature complete and deployed

The Secret Sauce: Session Documentation

The key to making phased development work is a detailed session document that grows with each phase. This becomes your shared memory between AI sessions.

# Feature Name - Implementation Session

*Date: YYYY-MM-DD*

*Branch: feature/branch-name*

*Status: Phase X Complete | Phase Y Ready*

## Overall Progress Summary

[High-level description of what's being built]

## Phase 1: [Name] (COMPLETE ✅)

### What Was Built:

- Specific files created/modified

- Key design decisions made

- Important function/class names

### Technical Details:

- Critical code patterns used

- Integration points identified

- Any gotchas discovered

## Phase 2: [Name] (TO DO)

### Required Steps:

1. Specific task with file location

2. Exact functions to modify

3. Commands to implement

Critical Success Factors

1. Atomic Phases

Each phase must be self-contained and deliverable:

✅ Good Phase Characteristics

• Compiles independently
• Testable in isolation
• Provides clear deliverables
• Takes less than 2 hours to complete
• Has obvious success criteria

❌ Poor Phase Characteristics

• Depends on incomplete future work
• Can't be tested until "later"
• Vague or subjective goals
• Requires more than 3 hours to implement
• Success is unclear

2. Explicit Handoff Context

Document everything the next AI session needs to know:

Exact line numbers for modifications
Function signatures that were created
Design patterns being followed
Decisions made and why they were made
Integration points for the next phase

3. Progressive Integration

Structure phases to build on each other logically:

Phase 1: Build in isolation (backend, services, models)

Phase 2: Connect to existing systems (integration, state)

Phase 3: Create new UI components (isolated development)

Phase 4: Wire everything together (final integration)

This approach means early phases can be tested thoroughly before moving on, and integration issues are caught early when they're easier to fix.

4. Git Commits as Checkpoints

Commit after each phase with detailed messages:

git commit -m "feat: Phase 1 - Backend infrastructure for feature X

- Created services A, B, C

- Added database migrations

- Implemented commands Y, Z

- All tests passing"

These commits serve as recovery points if context is lost and provide a clear history of what was accomplished in each phase.

The Handoff Protocol

When starting a new session for the next phase, use a structured prompt that sets clear context:

Handoff Prompt Template

Continue implementing [feature] from Phase X.

Branch: feature/branch-name

Please read: .project/context/session-[date]-[feature].md

for full context

Phase Y Goal: [Specific objective]

Required Tasks:

1. [Specific file]:[line numbers] - [what to do]

2. [Next specific task]

Success Criteria:

- [Measurable outcome]

- [Another measurable outcome]

Real-World Results

Using this phased approach on a complex optimization feature delivered remarkable results:

Phased Approach Results

• Zero context loss between sessions
• Each phase completed in under 2 hours
• Clean handoffs between development sessions
• All phases compiled successfully on first attempt
• Feature completed in 6 hours across multiple days
• High code quality throughout

Previous Marathon Approach

• Lost context after 3 hours
• Had to re-explain requirements multiple times
• Inconsistent patterns across the codebase
• Took 8+ hours with lower quality results
• Frustrating experience for both human and AI
• Required significant refactoring

Advanced Patterns

The Dependency Map

For complex features, create a visual dependency map showing how phases connect:

Phase Dependencies:

Phase 1 (Backend) ──→ Phase 2 (Integration)

↓

Phase 3 (Frontend) ──→ Phase 4 (UI Integration)

Parallel phases: 1 & 3 can run simultaneously

Sequential phases: 2 requires 1, 4 requires 2 & 3

The Testing Contract

Define clear testing criteria for each phase completion:

Phase 1: All API endpoints return expected responses
Phase 2: Existing functionality remains unbroken
Phase 3: All components render in Storybook
Phase 4: End-to-end user flows work correctly

The Recovery Plan

Always document how to recover if a phase fails:

Recovery Documentation

• Rollback commands: Exact git commands to undo changes
• Safe state: Last known working commit
• Alternative approaches: Plan B if current approach fails
• External dependencies: What might break and how to fix

Key Takeaways

The Five Principles of Phased Development

Think in phases, not features - Break large features into 2-hour chunks
Document religiously - Your session document is your lifeline
Test each phase - Don't accumulate technical debt
Commit frequently - Each phase should be a clean, documented commit
Design for handoff - Write as if a different AI (or human) will continue

The Meta-Lesson

Phased development mirrors excellent software engineering practices: modular development, clear interfaces, comprehensive documentation, and incremental delivery. The context window limitation actually forces better development practices.

By working within AI constraints rather than fighting them, we achieve better results with less frustration. The phased approach isn't just a workaround for context limits—it's a superior way to develop complex features, period.

The Ultimate Question

Next time you're planning a complex feature with an AI assistant, ask yourself: "How can I break this into phases where each one delivers value and can be completed in under 2 hours?"

Resist the urge to power through in one session. Break it down, document thoroughly, and watch your productivity—and code quality—soar.

Ready to Master Phased Development?

Learn how UpNorthDigital.ai can help you implement efficient phased development methodologies in your AI-assisted development workflow.

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