Inspiration
As a busy professional juggling work and wellness, I grew frustrated with last-minute weekday meal decisions and food waste. Watching friends struggle with the same chaos—spending hours cooking nightly or relying on expensive takeout—sparked the idea: what if Sunday prep could fuel the entire workweek, in just 2 hours? That’s how MealPrep Sunday was born.
What it does
MealPrep Sunday is a web app that delivers AI-generated weekly meal plans (5 lunches + 5 dinners) balanced in macros, with a 2-hour optimized prep timeline, categorized shopping lists, and storage/reheating guides—all for a $9.99/month subscription.
How we built it
We started by mapping core user needs (time efficiency, nutrition balance, simplicity) to build the page structure (4 key sections). We used React for the frontend UI (card-based, mobile-friendly), Node.js for backend logic, OpenAI API to generate meal plans, and Stripe for subscription processing. AWS hosted the app, with PostgreSQL storing meal plan and user subscription data.
Challenges we ran into
The biggest hurdle was optimizing the 2-hour timeline—balancing parallel cooking steps while ensuring total prep time never exceeded 2 hours. We also struggled with grouping shopping list items without duplicates and aligning storage guidelines to different meal types (freezer vs. fridge).
Accomplishments that we're proud of
We created a streamlined UI that prioritizes readability (short, direct steps) and mobile usability (large tap targets). The AI meal plans strike the perfect balance of nutrition and batch-cooking practicality, and the subscription flow is seamless with zero friction for users.
What we learned
We mastered timeline optimization logic and macro-balancing rules for meal planning. We also learned how to design a "preview mode" that entices users to subscribe without requiring login—critical for reducing onboarding barriers.
What's next for this project
We plan to add dietary preference filters (gluten-free, vegetarian), integrate grocery delivery service APIs, and build a meal plan export feature. We also want to expand archived plan access and add short video tutorials for key prep steps.
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