🔗 Quick Links
- GitHub Repo: github.com/MegaSF/Ai_Competition_Week1
- Builder: Evan Rhea on LinkedIn
- Video Demo: Watch on YouTube
📺 Watch Evan's Demo
See the Calorie Tracker in action as Evan walks through his AI-powered workflow and demonstrates the app:
The Builder
Evan Rhea, a student at Iowa State, entered the Launch Into AI competition with a clear goal: build something functional using AI tools, focusing on data visualization over polished aesthetics.
AI Tool Workflow
Evan combined two powerful AI coding assistants to get this built:
- GitHub Copilot Agent: Used for planning and writing the markdown file with instructions
- Codex: Used to transcribe code from Windows to Mac-friendly setup for recording
Cross-Platform Journey
One of the standout aspects of this submission was the portability challenge. Evan initially built the app on Windows, then used Codex to transcribe the code to work on Mac for the video demonstration.
This is a real-world problem that AI tools are increasingly good at solving — taking working code from one environment and adapting it to another without manual rewrites.
The App: Calorie Tracker
The app is simple and functional:
- Users upload CSV or JSON files with calorie data
- The app visualizes the data through bar charts and line charts
- Shows calories consumed vs. calories burned
- Built entirely with AI tools from start to finish
No complex auth. No database setup. Just upload data, see charts, understand your patterns.
What Makes This Submission Work
Evan's entry hits the competition theme squarely:
- Data visualization focus: Bar charts and line charts showing calories consumed vs. burned
- AI-native workflow: Copilot Agent for planning + Codex for transcribing Windows→Mac
- Functional over fancy: "It could look like a preschooler built it" — and that's fine
- Cross-platform: Real-world portability demonstration (Windows to Mac in minutes)
- Open source: Code shared for others to learn from
The Demo Moment
In the video, Evan demonstrates uploading a CSV file with sample fitness data and watching the charts populate instantly. He even does some on-the-fly analysis: "We're bulking because we're eating more than we're burning — about a 300 calorie surplus."
The app handles both bar charts (for comparing values) and line charts (for seeing trends over time). Week 1 and Week 2 show lower activity, then Week 3 ramps up through Week 6. Simple data, clear visualization, immediate insight.
In Evan's Words
"I wanted to take the GitHub Copilot that I already use, and I wanted to combine that with GPT's codecs. And I wanted to see like how that sort of agent to agent interaction would work... I think the whole thing took me about 20 minutes, max."
"It could look like a preschooler built it, which I specialize in... But a big part of the competition about also just making things exist, so not making them perfect."
The Lesson
This submission proves that you don't need to be a senior developer to ship something useful. With the right AI tools and a clear scope, you can go from idea to working app in a weekend.
The competition rewards shipping. Evan shipped.
🏆 Think You Can Build Something Better?
The competition runs until March 5th. Ship early, ship often, and remember: the multiplier rewards action, not polish.