🧠 Problem Framing: Reimagining Meal Planning for Real Life

Meal-prepping promised efficiency, but I found myself frustrated by the repetitiveness of eating the same thing every day. I wanted flexibility without the hassle — something that helped me:

​

• Maximize the ingredients I already had or make the most of my mismatched fridge ingredients

• Avoid decision fatigue after a long day

• Maintain control over how much time I spent cooking

​

These pain points inspired the question: "What Should I Eat Tonight?" — a product idea born from personal friction, designed to simplify everyday cooking decisions.

​

​​

​

🎯 The Insight

In today’s fast-paced, post-pandemic world, many young adults are cooking more but planning less. They’re not looking for rigid meal plans — they want responsive tools that match their energy levels, time constraints, and available ingredients. So I asked: "What if we could reduce the mental load of everyday cooking — while still giving people choice, variety, and control?"

​​

​

​

💡 Product Vision: Helping People Eat Better, Smarter, Easier

"What Should I Eat Tonight?" helps users generate recipe ideas based on what they already have and how much time they want to spend cooking. Here’s how it works:

• Users input the ingredients they have on hand

• They choose their preferred cooking time

• The app returns curated recipe options, complete with instructions

• A built-in AI assistant helps answer questions or customize recipes

By removing the friction of decision-making, the app frees up headspace — making mealtime less about stress and more about ease. 

​​​​

​

​

🔍 Enhancing the Experience: Designing for Real Life & Future Expansion

My goal wasn’t just to solve a meal planning problem for today — I wanted to explore how this tool could become a smart, supportive presence in everyday life. A system that’s not just reactive, but proactively helpful.

​

🛒 1. Smart Grocery Integration

To extend the app’s utility, I envisioned a deeper integration with grocery platforms — transforming meal planning into an end-to-end, intelligent system. The idea?

• Automatically generate shopping lists from selected recipes

• Suggest items based on budget constraints and personal preferences

• Sync with grocery delivery apps for a seamless checkout experience

• Translate recipe quantities into relatable, visual terms — like “half a pack of spaghetti” or “3 stalks of spring onion” instead of grams

• Track pantry inventory dynamically, adjusting available ingredients based on the recipes you’ve used

• Pre-plan and schedule grocery orders ahead of time based on your weekly meal plan

This turns the app into a true meal-planning assistant — one that not only helps you cook tonight’s dinner, but also helps you plan the week, reduce food waste, and take control of your time and budget.
→ Think: intuitive inventory meets forward-thinking logistics.

In future iterations, machine learning could enhance this further with:

• Freshness tracking — e.g., “Use your spinach by Thursday”

• Smart nudges — e.g., “You’ve got leftover tomatoes and basil — how about pasta salad tomorrow?”
  → Think: real-time fridge-to-recipe flow that feels effortless and smart.

​​

2. Building for Connection: A Community Layer

Cooking isn’t just functional — it’s emotional. I wanted to design a space where food could also become a way to stay close. So I imagined a community feature that enables users to:

• Share recipes with loved ones

• Discover what others are cooking in real time

• Bond over food and stories — even when apart

• Effortlessly keep loved ones in the loop without needing to individually message or update them about what you're having

Whether you're meal-prepping with a friend, checking what your partner is cooking tonight, or sharing grandma’s dumpling recipe — this feature brings people closer through food. It turns meal planning into a shared experience, not just a solo task.

​​

​

​

✍️ Design Process: From Concept to Clickable

I started designing the product during the AWS PartyRock Hackathon, prototyping with generative AI to explore early proof of concept. To move from idea to interface, I followed these steps:

1. Low-Fidelity Sketching – Mapped out structure and user flow with quick paper sketches

2. Visual Direction – Developed a mood board and style guide to set tone and consistency

3. High-Fidelity UI – Refined font, color, and layout to build an interactive prototype in Figma

You can interact with the AI prototype here, or view the design process in my here.

​​

​

​

​

​​

​

​

​

​

​

​​

​

​

​

​

​

​

​

​

​

​

​

​

​​

​

​

​

​

​

​

​

​

​

​

​

​

​

 

 

 

 

 

 

 

 

​

​

​

​

​

​

​​​​​​

🔥 Product Roadmap: From Friction to Flow

Having mapped out the core features and future potential of the product, I stepped back to consider how this experience might evolve — not just functionally, but emotionally and strategically. This roadmap captures the product’s transformation from functional tool to holistic assistant — blending intelligence, personalization, and emotional design to reshape how users plan, cook, and connect through meals.

​

✅ MVP (Now) – Simplify the starting point

• Input ingredients + time → get recipe suggestions

• Ideal for: quick decision-making, using what you already have

​

🧩 V2 – Personalization + Pantry Sync

• Pantry sync: Know what you already have

• Saved preferences: Track likes, dislikes, dietary needs

• Meal tracking: See your past meals and plan ahead

​

🛒 V3 – Intelligent Planning & Smart Logistics

• Auto-generate grocery lists from selected recipes

• Translate recipe quantities into relatable terms
  → e.g. “half a pack of spaghetti” instead of “250g”

• Smart freshness alerts
  → e.g. “Use your spinach by Thursday”

• Suggest grocery items based on budget + preferences

• Track pantry dynamically based on recipes used

• Pre-plan and schedule grocery orders
  → Think: intuitive inventory meets forward-thinking logistics

​​

​

​

✅ Measuring Success

Having laid out the roadmap, I also considered how we might measure success — not just in terms of functionality, but in how well the product supports real-life habits, decision-making, and emotional connection in the kitchen. If this were to move forward as a product, I’d focus on:

• Engagement – Return rate within 3 days: Are users coming back to explore more meals?

• Intent – Average number of ingredient inputs: Are users actively thinking about what they have and planning ahead?

• Conversion – Recipe clicked → marked as “cooked”: Are we bridging the gap between idea and action?

• Retention – Saved recipes or consistent meal streaks: Are users building habits and relying on the product over time?

​​

​

​

🌱 Evolving into a Strategic Product: Real Needs, Future Vision

As a dreamer, I’m looking ahead to a future where this app doesn’t just fix one problem — it becomes a hyper-personalized cooking assistant. Driven by real user feedback and iterative data, the app could expand to integrate seamlessly with grocery platforms, help users manage inventory, and suggest sustainable choices. It could build a dynamic experience that’s always evolving, helping users save time, reduce waste, and connect with the people they care about.

This project has been about more than just a single prototype; it’s about rethinking how technology can bring people closer to their food and to each other — making daily tasks simpler, more sustainable, and more meaningful.

​​

​

 

 

​