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Initial setup: Product-focused take-home assignment for senior full-stack engineers
- Ambiguous product requirements (no prescriptive UI specs) - Minimal API (no pagination, no filtering) to test problem-solving - Working Express server with mock data (5k orgs, 90 days DAU) - Rate limiting support via TWIST environment variable - AI usage documentation template - GitHub Actions for submission validation - Product engineer focus: requires decision-making and trade-off analysis
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‎.github/PULL_REQUEST_TEMPLATE.md‎

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# Usage Analytics Submission
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## Checklist
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- [ ] Application runs successfully
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- [ ] Tests pass
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- [ ] AI_NOTES.md is filled out
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- [ ] README.md documents my decisions
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## Summary
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Brief description of your approach:
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**Frontend framework:**
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**Pagination strategy:**
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**Key decisions:**
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## Time Spent
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Approximately ___ hours
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## Questions for Discussion
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List any questions or areas you'd like to discuss in the follow-up:
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1.
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2.
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3.
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‎.github/workflows/check-submission.yml‎

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name: Check Submission
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on:
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pull_request:
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types: [opened, synchronize, reopened]
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jobs:
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validate:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Check AI_NOTES.md exists
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run: |
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if [ ! -f "AI_NOTES.md" ]; then
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echo "❌ AI_NOTES.md is missing"
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exit 1
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fi
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echo "✅ AI_NOTES.md exists"
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- name: Check AI_NOTES.md has content
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run: |
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# Count non-empty, non-comment lines
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CONTENT_LINES=$(grep -v '^#' AI_NOTES.md | grep -v '^<!--' | grep -v '^-->' | grep -v '^$' | wc -l)
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if [ "$CONTENT_LINES" -lt 3 ]; then
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echo "❌ AI_NOTES.md appears to be empty or has minimal content"
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echo "Please document how you used AI during this assignment"
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exit 1
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fi
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echo "✅ AI_NOTES.md has content ($CONTENT_LINES lines)"
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- name: Check README.md updated
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run: |
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# Check if README has candidate's additions (look for common sections)
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if ! grep -q -i "decision\|trade-off\|approach\|choice" README.md; then
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echo "⚠️ README.md may not document your decisions"
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echo "Please add a section explaining your approach and trade-offs"
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else
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echo "✅ README.md appears to document decisions"
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fi
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- name: Summary
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run: |
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echo "## Submission Validation ✅" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "All required files are present and have content." >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "Next steps:" >> $GITHUB_STEP_SUMMARY
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echo "1. Reviewer will evaluate your submission" >> $GITHUB_STEP_SUMMARY
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echo "2. We'll schedule a follow-up discussion" >> $GITHUB_STEP_SUMMARY
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‎.gitignore‎

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# Dependencies
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node_modules/
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npm-debug.log*
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yarn-debug.log*
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yarn-error.log*
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# Environment
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.env
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.env.local
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.env.*.local
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# OS
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.DS_Store
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Thumbs.db
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# Build outputs
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dist/
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build/
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.next/
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out/
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# Logs
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logs/
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*.log
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# Testing
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coverage/
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.nyc_output/
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# Misc
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*.bak
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*.tmp
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‎AI_NOTES.md‎

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# AI Usage Notes
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Document how you used AI during this assignment.
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## Format
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Each entry should include:
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- What you asked the AI
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- What you got back
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- What you modified/verified
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- Why you made changes
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## Example
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**Prompt:** "Create a date range picker component in React"
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**Response:** AI generated a basic component with date-fns library
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**Edits:** Changed to use native input type="date" for simplicity and better mobile support
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**Verification:** Tested edge cases (invalid dates, reversed ranges, boundary dates)
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---
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## Your Notes
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<!-- Add your entries below -->
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‎AI_NOTES_EXAMPLE.md‎

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# AI Usage Notes - Example
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This is an example of what good AI_NOTES.md documentation looks like.
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**Note:** This is just a reference to help you understand the format. You should fill out `AI_NOTES.md` with your own entries, not copy this file.
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---
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## Entry 1: Project Setup
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**Prompt:** "Create a React app with Vite and TypeScript for a data analytics dashboard"
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**Response:** AI provided commands to initialize Vite project with React and TypeScript template
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**Edits:** None - used the commands as-is
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**Verification:** Ran `npm create vite@latest` and confirmed project structure was correct
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---
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## Entry 2: Date Range Picker Component
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**Prompt:** "Create a React component for selecting a date range with start and end dates, default to last 14 days"
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**Response:** AI generated a component using react-datepicker library with state management
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**Edits:**
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- Removed react-datepicker dependency (too heavy)
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- Changed to native HTML5 date inputs for simplicity
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- Added validation to ensure end date is after start date
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- Added keyboard navigation support
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**Verification:**
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- Tested with various date ranges
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- Tested edge cases (same date, reversed dates, future dates)
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- Verified keyboard navigation works
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- Checked mobile behavior
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---
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## Entry 3: CSV Export Function
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**Prompt:** "Create a function to export table data to CSV format and trigger download"
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**Response:** AI generated function using Blob and URL.createObjectURL
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**Edits:**
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- Added proper CSV escaping for fields with commas
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- Added header row with column names
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- Changed to only export currently visible/filtered data (not all data)
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- Added filename with timestamp
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**Verification:**
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- Tested export with various data
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- Tested with special characters (commas, quotes)
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- Verified file downloads correctly
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- Opened CSV in Excel to verify format
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---
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## Entry 4: Error Boundary
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**Prompt:** "Create a React error boundary component to catch rendering errors"
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**Response:** AI generated class component with componentDidCatch
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**Edits:**
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- Added retry button to error UI
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- Added error logging (console.error)
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- Improved error message to be user-friendly
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- Added fallback UI that matches app design
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**Verification:**
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- Tested by throwing error in child component
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- Verified error boundary catches it
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- Verified retry button works
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- Checked that error doesn't crash entire app
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---
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‎GETTING_STARTED.md‎

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# Getting Started
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Welcome! This guide will help you get set up quickly.
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## Quick Setup
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### 1. Start the API Server
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```bash
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cd server
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npm install
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npm start
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```
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You should see:
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```
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Generating mock data...
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Generated 5000 organizations
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Generated 90 days of DAU data
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API server running on http://localhost:3001
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```
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### 2. Test the APIs
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```bash
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# In a new terminal
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curl http://localhost:3001/api/metrics/dau
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curl http://localhost:3001/api/metrics/top-orgs
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```
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### 3. Build Your Frontend
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```bash
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# Create your frontend directory
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mkdir frontend
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cd frontend
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# Use your preferred setup
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# Examples:
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npm create vite@latest . # Vite (React, Vue, Svelte, etc.)
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npx create-next-app@latest . # Next.js
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npx create-react-app . # Create React App
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# ... or any other framework
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```
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## What You're Building
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A single-page "Usage Analytics" dashboard that helps answer:
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- **"How is our DAU trending over time?"**
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- **"Which organizations are most active?"**
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You'll need to decide:
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- How to visualize DAU trends
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- How to present organization data effectively
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- What interactions users need
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- How to handle edge cases and errors
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## Available APIs
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**GET /api/metrics/dau**
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- Returns daily active user data
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- Call it to see the response format
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**GET /api/metrics/top-orgs**
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- Returns organizations ranked by activity
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- Call it to see the response format
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Explore these endpoints to understand what data is available.
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## What to Submit
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1. **Working application** - We should be able to run it
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2. **Tests** - At least 2 meaningful test cases
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3. **AI_NOTES.md** - Document how you used AI (see AI_NOTES_EXAMPLE.md for format)
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4. **README.md** - Update with your decisions, trade-offs, and what you'd do with more time
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## Tips
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- **Time:** Aim for 2-3 hours. Don't spend more than this.
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- **Framework:** Use whatever you're most comfortable with.
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- **AI:** Feel free to use AI! Just document it in AI_NOTES.md.
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- **Backend:** The server code is available if you want to explore or modify it.
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- **Questions:** If anything is unclear, please ask!
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## Submission
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When you're done:
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1. Create a PR with your changes
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2. Fill out the PR template
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3. We'll review and schedule a follow-up discussion
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## Need Help?
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- Check `AI_NOTES_EXAMPLE.md` for documentation format
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- Look at `server/routes/metrics.js` to understand the API
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- The server code is clean and modifiable - feel free to explore
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Good luck! 🚀
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