diff --git a/LEVEL-TRANSFORMATION-GUIDE.md b/LEVEL-TRANSFORMATION-GUIDE.md
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+# Level-by-Level Transformation Guide
+
+## Overview
+This document provides detailed instructions for transforming each remaining level branch (3-8) from complete production code to learning exercises with TODOs.
+
+## Pattern Established (Levels 1-2)
+
+### Success Criteria
+1. ✅ App runs without errors (`npm start` works)
+2. ✅ Code simplified to focus on level-specific concepts
+3. ✅ Clear TODOs with hints (not complete solutions)
+4. ✅ Educational comments explaining "why" not just "how"
+5. ✅ Progressive - each level builds on previous completed levels
+6. ✅ Maintains professional code structure
+7. ✅ Comprehensive but focused CSS
+
+### File Structure
+Each level needs:
+- `src/App.js` - Simplified component with TODOs
+- `src/App.css` - Focused styling for that level's features
+- Existing `docs/README-LEVEL-N.md` (already exists, no changes needed)
+
+## Level 3: Filters & Effects
+
+### Learning Objectives
+- Dynamic CSS filter application
+- Filter intensity control with range slider
+- Combining multiple CSS filters
+- Creating custom filter presets
+
+### What to Keep from Level 2
+- ✅ Working webcam with camera toggle
+- ✅ Video rendering to canvas
+- ✅ Basic filter selection
+
+### New Features to Add (with TODOs)
+1. **TODO 1: Add filter intensity state and slider**
+   ```javascript
+   // TODO 1: Add state for filter intensity (0-100)
+   // HINT: const [filterIntensity, setFilterIntensity] = useState(100);
+   ```
+
+2. **TODO 2: Apply intensity to filters**
+   ```javascript
+   // TODO 2: Modify getFilterCSS to accept intensity parameter
+   // HINT: Use calc() or template literals to adjust filter values
+   // Example: `grayscale(${intensity}%)`
+   ```
+
+3. **TODO 3: Add intensity slider UI**
+   ```jsx
+   // TODO 3: Add range input for intensity control
+   // HINT: <input type="range" min="0" max="100" value={filterIntensity} />
+   ```
+
+4. **BONUS TODO: Create custom filter**
+   ```javascript
+   // BONUS: Add your own custom filter to the filters array
+   // Example: { id: 'custom', name: 'My Filter', filter: '...' }
+   ```
+
+### Key Code Sections
+- Filter intensity state management
+- Dynamic CSS filter value calculation
+- Range slider control
+- Real-time filter preview
+
+### Approximate Size
+- App.js: ~400-450 lines
+- App.css: Similar to Level 2 + slider styles
+
+---
+
+## Level 4: Photo Capture
+
+### Learning Objectives
+- Canvas toDataURL() method
+- Blob API and file downloads
+- Photo state management (array operations)
+- Creating download links programmatically
+
+### What to Keep from Level 3
+- ✅ Everything from Levels 1-3
+- ✅ Working webcam with filters and intensity
+
+### New Features to Add (with TODOs)
+1. **TODO 1: Add photos state**
+   ```javascript
+   // TODO 1: Add state for captured photos array
+   // HINT: const [photos, setPhotos] = useState([]);
+   ```
+
+2. **TODO 2: Implement capturePhoto**
+   ```javascript
+   // TODO 2: Capture current canvas as image
+   // HINT: Use canvas.toDataURL('image/png')
+   // Create photo object: { id, dataURL, filter, timestamp }
+   // Add to photos array: setPhotos(prev => [...prev, newPhoto])
+   ```
+
+3. **TODO 3: Implement downloadPhoto**
+   ```javascript
+   // TODO 3: Create download link for photo
+   // HINT: Create <a> element with download attribute
+   // Set href to photo.dataURL
+   // Programmatically click it: link.click()
+   ```
+
+4. **TODO 4: Implement deletePhoto**
+   ```javascript
+   // TODO 4: Remove photo from array
+   // HINT: setPhotos(prev => prev.filter(p => p.id !== photoId))
+   ```
+
+### UI Components to Add
+- Capture button (camera icon)
+- Photo gallery grid
+- Download button per photo
+- Delete button per photo
+- Photo counter display
+
+### Approximate Size
+- App.js: ~550-600 lines
+- App.css: Level 3 + photo gallery styles
+
+---
+
+## Level 5: Stickers & Drag-and-Drop
+
+### Learning Objectives
+- Drag and Drop API
+- Mouse and touch event handling
+- Coordinate transformations
+- Array state management for stickers
+
+### What to Keep from Level 4
+- ✅ Everything from Levels 1-4
+- ✅ Working photo capture
+
+### New Features to Add (with TODOs)
+1. **TODO 1: Add stickers state**
+   ```javascript
+   // TODO 1: Add state for placed stickers
+   // HINT: const [placedStickers, setPlacedStickers] = useState([]);
+   // Each sticker: { id, emoji, x, y, size, rotation }
+   ```
+
+2. **TODO 2: Implement addSticker**
+   ```javascript
+   // TODO 2: Add new sticker to canvas
+   // HINT: Create sticker object with default position (center)
+   // Add to placedStickers array
+   ```
+
+3. **TODO 3: Draw stickers on canvas**
+   ```javascript
+   // TODO 3: In renderFrame, draw all stickers after video
+   // HINT: Loop through placedStickers
+   // Use ctx.fillText(sticker.emoji, x, y)
+   // Apply transformations for rotation
+   ```
+
+4. **TODO 4: Implement drag handlers**
+   ```javascript
+   // TODO 4a: onMouseDown - detect which sticker was clicked
+   // TODO 4b: onMouseMove - update sticker position
+   // TODO 4c: onMouseUp - finish dragging
+   // LEARNING: Calculate relative positions, handle touch events
+   ```
+
+5. **TODO 5: Implement removeSticker**
+   ```javascript
+   // TODO 5: Remove sticker from array
+   // HINT: Filter out by sticker.id
+   ```
+
+### UI Components to Add
+- Sticker picker panel
+- Sticker categories (animals, accessories, expressions)
+- Draggable sticker overlay
+- Delete button per sticker
+
+### Approximate Size
+- App.js: ~750-800 lines
+- App.css: Level 4 + sticker overlay and picker styles
+
+---
+
+## Level 6: AI Integration (Text)
+
+### Learning Objectives
+- Environment variables (.env files)
+- API key security
+- Async/await for API calls
+- Google Gemini AI API basics
+- Error handling with try/catch
+
+### What to Keep from Level 5
+- ✅ Everything from Levels 1-5
+- ✅ Full working app
+
+### New Features to Add (with TODOs)
+1. **TODO 1: Load API key from environment**
+   ```javascript
+   // TODO 1: Load Gemini API key from .env
+   // HINT: Use useEffect to check process.env.REACT_APP_GEMINI_API_KEY
+   // Store in geminiKey state
+   ```
+
+2. **TODO 2: Implement getFilterRecommendation**
+   ```javascript
+   // TODO 2: Get AI recommendation for best filter
+   // HINT: Initialize GoogleGenerativeAI with API key
+   // const genAI = new GoogleGenerativeAI(geminiKey);
+   // Get model: gemini-2.5-flash
+   // Build prompt with time of day and available filters
+   // await model.generateContent(prompt)
+   ```
+
+3. **TODO 3: Create getTimeOfDay helper**
+   ```javascript
+   // TODO 3: Return time of day based on hour
+   // HINT: const hour = new Date().getHours();
+   // Return 'morning', 'afternoon', 'evening', or 'night'
+   ```
+
+4. **TODO 4: Apply recommended filter**
+   ```javascript
+   // TODO 4: Parse AI response and set active filter
+   // HINT: Extract filter name from response text
+   // Find matching filter in filters array
+   // Call handleFilterClick with filter ID
+   ```
+
+### UI Components to Add
+- API key status indicator
+- "Get AI Recommendation" button
+- Loading state during AI processing
+- Recommendation display area
+- Setup instructions if no API key
+
+### Dependencies
+- `@google/generative-ai` package (already in package.json)
+
+### Approximate Size
+- App.js: ~900-950 lines
+- App.css: Level 5 + AI panel styles
+
+---
+
+## Level 7: AI Vision
+
+### Learning Objectives
+- Multimodal AI (text + image)
+- Base64 image encoding
+- Canvas image extraction
+- Structured AI prompting
+- Parsing structured AI responses
+
+### What to Keep from Level 6
+- ✅ Everything from Levels 1-6
+- ✅ Working AI text integration
+
+### New Features to Add (with TODOs)
+1. **TODO 1: Implement captureForAnalysis**
+   ```javascript
+   // TODO 1: Capture canvas as base64 for AI
+   // HINT: canvas.toDataURL('image/jpeg', 0.7)
+   // Extract base64 part: dataURL.split(',')[1]
+   ```
+
+2. **TODO 2: Implement analyzeSkin**
+   ```javascript
+   // TODO 2: Send image to Gemini Vision API
+   // HINT: Use model.generateContent with both prompt and image
+   // Image format: { inlineData: { mimeType: 'image/jpeg', data: base64 } }
+   // Ask for: skin type, tone, recommended filters, reasoning
+   ```
+
+3. **TODO 3: Implement parseAnalysis**
+   ```javascript
+   // TODO 3: Parse structured text response
+   // HINT: Split by lines, look for "Skin Type:", "Tone:", etc.
+   // Extract data into object
+   // Return { skinType, tone, recommendedFilters, reasoning }
+   ```
+
+4. **TODO 4: Display analysis results**
+   ```jsx
+   // TODO 4: Show analysis in UI
+   // HINT: Display skin type, tone, recommendations
+   // Add "Apply Recommendation" button
+   ```
+
+### UI Components to Add
+- "Analyze Skin" button
+- Analysis progress indicator
+- Analysis results panel with sections
+- Apply recommendation button
+
+### Approximate Size
+- App.js: ~1050-1100 lines
+- App.css: Level 6 + analysis panel styles
+
+---
+
+## Level 8: Face Detection
+
+### Learning Objectives
+- TensorFlow.js basics
+- Loading ML models
+- Face-API.js library
+- Real-time face detection
+- Facial landmarks (68 points)
+- Expression recognition
+- Performance optimization
+
+### What to Keep from Level 7
+- ✅ Everything from Levels 1-7
+- ✅ Complete working app
+
+### New Features to Add (with TODOs)
+1. **TODO 1: Load face detection models**
+   ```javascript
+   // TODO 1: Load TensorFlow models in useEffect
+   // HINT: const MODEL_URL = process.env.PUBLIC_URL + '/models';
+   // await faceapi.nets.tinyFaceDetector.loadFromUri(MODEL_URL)
+   // await faceapi.nets.faceLandmark68Net.loadFromUri(MODEL_URL)
+   // await faceapi.nets.faceExpressionNet.loadFromUri(MODEL_URL)
+   ```
+
+2. **TODO 2: Implement face detection loop**
+   ```javascript
+   // TODO 2: Separate detection loop from rendering
+   // HINT: Run detection every 100ms (not every frame)
+   // Use faceapi.detectAllFaces(video, options)
+   // .withFaceLandmarks()
+   // .withFaceExpressions()
+   // Store results in state
+   ```
+
+3. **TODO 3: Draw face detections**
+   ```javascript
+   // TODO 3: In renderFrame, draw detection results
+   // HINT: Loop through detections
+   // Draw bounding box: ctx.strokeRect(x, y, width, height)
+   // Draw landmarks: ctx.fillRect(x, y, 2, 2) for each point
+   // Display confidence percentage
+   ```
+
+4. **TODO 4: Implement getDominantExpression**
+   ```javascript
+   // TODO 4: Find emotion with highest value
+   // HINT: Object.keys(expressions).reduce((a, b) => 
+   //         expressions[a] > expressions[b] ? a : b)
+   ```
+
+5. **TODO 5: Add expression emoji overlay**
+   ```javascript
+   // TODO 5: Show emoji for detected emotion
+   // HINT: Create emotionEmojis map: { happy: '😊', sad: '😢', ... }
+   // Display dominant emotion emoji near face
+   ```
+
+### UI Components to Add
+- "Enable Face Detection" toggle
+- Detection status indicator
+- Face count display
+- Bounding box toggle
+- Landmarks toggle
+- Expression overlay toggle
+- Performance metrics (FPS, detection time)
+
+### Dependencies
+- `@vladmandic/face-api` package (already in package.json)
+- Model files in `public/models/` (already exist)
+
+### Approximate Size
+- App.js: ~1200-1300 lines (still much smaller than original 1880)
+- App.css: Level 7 + face detection controls styles
+
+---
+
+## Implementation Strategy
+
+### Option A: Manual (Current Approach)
+1. Checkout each level branch
+2. Create simplified App.js with TODOs
+3. Create matching CSS
+4. Test with npm start
+5. Commit and document
+
+**Time:** ~2-3 hours per level × 6 levels = 12-18 hours
+
+### Option B: Scripted Approach
+1. Create templates for each level
+2. Use script to generate App.js files
+3. Manual review and testing
+4. Commit in batch
+
+**Time:** ~8-10 hours (faster but less custom)
+
+### Option C: Hybrid (Recommended)
+1. Use Levels 1-2 as reference
+2. Create Level 3-4 manually (2-3 hours each)
+3. Create template script for Levels 5-8
+4. Manual testing and refinement
+
+**Time:** ~10-12 hours
+
+## Testing Checklist
+
+For each completed level:
+- [ ] `npm install` works
+- [ ] `npm start` runs without errors
+- [ ] All TODOs are clearly marked
+- [ ] Hints are helpful but not complete solutions
+- [ ] Educational comments explain concepts
+- [ ] Code is simplified from original
+- [ ] CSS is focused and clean
+- [ ] Level builds on previous levels
+- [ ] Matches corresponding documentation in docs/README-LEVEL-N.md
+
+## Pushing Branches
+
+After completing transformations:
+
+```bash
+# Push all at once
+git push origin level-1-basics level-2-webcam level-3-filters level-4-photos level-5-stickers level-6-ai-text level-7-ai-vision level-8-face-detection
+
+# Or use the helper script
+./push-level-branches.sh
+```
+
+## Quality Assurance
+
+### Code Review Points
+1. Are TODOs actionable and clear?
+2. Do hints guide without spoiling?
+3. Is complexity appropriate for level?
+4. Are imports minimal (only what's needed)?
+5. Are comments educational, not just descriptive?
+6. Does each level have a clear "aha!" moment?
+7. Can students realistically complete in stated time?
+
+### Student Experience
+1. Can a beginner follow Level 1?
+2. Is progression logical and not too steep?
+3. Are error messages helpful?
+4. Is there enough scaffolding?
+5. Are success states clear (how do they know it works)?
+
+## Success Metrics
+
+When all 8 levels are complete:
+
+1. ✅ All level branches contain learning exercises (not complete code)
+2. ✅ Solution branches remain complete (reference implementations)
+3. ✅ Main branch remains complete (production code)
+4. ✅ Each level is progressively more complex
+5. ✅ Documentation in docs/ matches code structure
+6. ✅ Repository works as promised in README.md
+7. ✅ Students can complete "hands-on learning" path
+8. ✅ All branches tested and functional
+
+## Estimated Completion
+
+**Current Status:** 2 of 8 levels complete (25%)
+
+**Remaining Work:**
+- Level 3: 2-3 hours
+- Level 4: 2-3 hours  
+- Level 5: 3-4 hours (drag-drop complexity)
+- Level 6: 2-3 hours
+- Level 7: 2-3 hours
+- Level 8: 3-4 hours (TensorFlow setup)
+
+**Total:** 14-20 hours
+
+**With efficiency improvements:** 10-14 hours
+
+## Next Action
+
+Continue with Level 3 transformation following the detailed guide above.
diff --git a/TRANSFORMATION-STATUS.md b/TRANSFORMATION-STATUS.md
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+# Branch Transformation Summary
+
+## Overview
+This document tracks the transformation of level branches from complete production code to learning branches with TODOs.
+
+## Problem
+All level branches (level-1-basics through level-8-face-detection) contained complete production code (commit 29554bf), making them identical to solution branches. This defeats the purpose of having separate learning branches.
+
+## Solution
+Transform each level branch according to BRANCH-MODIFICATION-GUIDE.md by:
+1. Removing advanced features beyond that level's scope
+2. Adding TODO comments with hints
+3. Keeping boilerplate code and structure
+4. Adding educational comments
+5. Ensuring the app runs without errors
+
+## Progress
+
+### ⏳ Level 1: React Basics (level-1-basics)
+**Status:** NOT STARTED - NEEDS TRANSFORMATION
+**Current State:** Contains complete production code (commit 29554bf)
+**Target:** Simplified ~170 lines with 4 TODOs
+
+**Planned Changes:**
+- Simplify App.js from 1880 lines to ~170 lines
+- Remove all features except basic React concepts
+- Add 4 clear TODOs:
+  1. Declare activeFilter state with useState
+  2. Implement handleFilterClick event handler  
+  3. Display activeFilter value in UI
+  4. Connect onClick handlers to filter buttons
+- Create simplified, focused CSS (replace 1807 lines)
+- Add instructions card with step-by-step tasks
+- Add learning resources section
+- Test with `npm start`
+
+**Features to Remove:**
+- Webcam/video (Level 2 content)
+- Photo capture (Level 4 content)
+- Stickers (Level 5 content)
+- AI features (Level 6-7 content)
+- Face detection (Level 8 content)
+- Complex landing page sections
+
+**Features to Keep:**
+- Filter buttons array (reference data)
+- Basic component structure
+- Simple state management concepts
+- Event handler patterns
+
+### ⏳ Level 2: Webcam & Canvas (level-2-webcam)
+**Status:** NOT STARTED - NEEDS TRANSFORMATION
+**Current State:** Contains complete production code (commit 29554bf)
+**Target:** Simplified ~330 lines with 3 TODOs
+
+**Planned Changes:**
+- Build on Level 1 with working filter selection
+- Add useRef hooks for video, canvas, stream, and animation
+- Add 3 clear TODOs:
+  1. Implement toggleCamera with WebRTC getUserMedia
+  2. Implement renderFrame with canvas drawing and filtering
+  3. Add cleanup in useEffect to prevent memory leaks
+- Add webcam controls and camera placeholder UI
+- Filter buttons disabled until camera is active
+- Add educational concept cards (WebRTC, Canvas, useRef, Animation Loops)
+- Add comprehensive comments on async/await and error handling
+- Test that app runs without errors
+
+### ⏳ Level 3: Filters & Effects (level-3-filters)
+**Status:** PENDING
+**Required Changes:**
+- Build on Levels 1-2
+- Add TODOs for applying CSS filters to canvas
+- Add TODOs for filter intensity control
+- Add TODOs for custom filter creation
+
+### ⏳ Level 4: Photo Capture (level-4-photos)
+**Status:** PENDING
+**Required Changes:**
+- Build on Levels 1-3
+- Add TODOs for capturePhoto function
+- Add TODOs for downloadPhoto function
+- Add TODOs for deletePhoto function
+- Keep photo gallery UI structure
+
+### ⏳ Level 5: Stickers & Drag (level-5-stickers)
+**Status:** PENDING
+**Required Changes:**
+- Build on Levels 1-4
+- Add TODOs for addSticker function
+- Add TODOs for drawing stickers on canvas
+- Add TODOs for drag-and-drop handlers
+- Keep stickers array
+
+### ⏳ Level 6: AI Integration (level-6-ai-text)
+**Status:** PENDING
+**Required Changes:**
+- Build on Levels 1-5
+- Add TODOs for API key loading from .env
+- Add TODOs for getFilterRecommendation
+- Add TODOs for getTimeOfDay helper
+- Keep Gemini API integration structure
+
+### ⏳ Level 7: AI Vision (level-7-ai-vision)
+**Status:** PENDING
+**Required Changes:**
+- Build on Levels 1-6
+- Add TODOs for analyzeSkin function
+- Add TODOs for parseAnalysis function
+- Add TODOs for base64 image encoding
+
+### ⏳ Level 8: Face Detection (level-8-face-detection)
+**Status:** PENDING
+**Required Changes:**
+- Build on Levels 1-7
+- Add TODOs for loading TensorFlow models
+- Add TODOs for face detection loop
+- Add TODOs for drawing face detections
+- Add TODOs for getDominantExpression helper
+
+## Testing Strategy
+For each transformed level (once completed):
+1. ⏳ npm install works
+2. ⏳ npm start runs without errors
+3. ⏳ TODOs are clear and actionable
+4. ⏳ Hints guide without giving away complete answers
+5. ⏳ Code is simplified to focus on level concepts
+6. ⏳ Progressive complexity (each level builds on previous)
+
+## Next Steps
+1. Transform level-1-basics branch following LEVEL-TRANSFORMATION-GUIDE.md
+2. Test that modified branch works (npm start runs without errors)
+3. Push level-1-basics branch to remote
+4. Transform level-2-webcam following same pattern
+5. Test level-2 builds on level-1 concepts
+6. Continue through remaining levels (3-8)
+7. Final end-to-end testing of complete learning path
+
+## Notes
+- Solution branches (level-*-solution) remain untouched with complete code
+- Main branch remains untouched with complete production code
+- Each level should be testable independently
+- Documentation in docs/README-LEVEL-*.md already exists and is excellent
+
+## How to Push Branches
+Once transformations are complete, use the provided script:
+```bash
+# Edit push-level-branches.sh to uncomment completed branches
+# Then run:
+./push-level-branches.sh
+```
+
+Or push manually with proper credentials:
+```bash
+# After transforming each branch
+git checkout level-1-basics
+# Make transformation changes
+git commit -m "Transform level-1 to learning branch with TODOs"
+git push origin level-1-basics
+
+# Repeat for each level
+```
diff --git a/push-level-branches.sh b/push-level-branches.sh
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+#!/bin/bash
+
+# Script to push transformed level branches
+# Run this after completing the transformations on each branch
+
+echo "Pushing transformed level branches..."
+
+# NOTE: The transformations have not been applied yet
+# The level branches currently still contain complete production code
+# Uncomment each line below AFTER transforming that branch
+
+# git push origin level-1-basics
+# git push origin level-2-webcam
+# git push origin level-3-filters
+# git push origin level-4-photos
+# git push origin level-5-stickers
+# git push origin level-6-ai-text
+# git push origin level-7-ai-vision
+# git push origin level-8-face-detection
+
+echo "Done!"