Brief
“What’s for dinner?”
It’s the question we all dread — one that feels deceptively simple but somehow manages to trigger stress, indecision, and an inevitable scroll through apps, fridge inventory, and mental notes from the last grocery run. I found myself asking that question more often than I wanted to admit — especially as someone who loves food, enjoys cooking, but doesn’t have the time or mental space to plan every meal with precision.
That’s when Plannabelle was born.
Plannabelle is my personal response to this universal problem — a meal planning platform designed to make “What’s for dinner?” feel less like a stressor and more like an invitation. It’s friendly, intuitive, and built for real people — the ones who want flexibility, creativity, and clarity without the chaos. Whether you want to manually explore dishes, build your grocery list, or ask a conversational AI assistant for ideas based on what’s in your fridge, Plannabelle meets you where you are.
Designing a Welcoming Home That Curates Recipes and Sparks Mealtime Inspiration
People are always on the lookout for fresh ideas in the kitchen—Plannabelle’s homepage is built to inspire. From trending dishes to seasonal spotlights, it surfaces recipes that spark curiosity and satisfy your inner foodie, making everyday cooking feel a little more exciting and a lot less stressful.
Turning Cravings into a Plan
With busy schedules and endless meal options, staying organized can be a challenge. Plannabelle’s calendar view brings structure to the chaos—helping users visualize their week at a glance, plan ahead with ease, and build balanced meals that fit their lifestyle and cravings.
From Cravings to Cart
No more scattered sticky notes or last-minute dashes to the store. This smart grocery list organizes everything you need, directly from your selected meals—so you can shop with clarity, confidence, and zero guesswork.
View the full prototype here:
The Process
Imagine this: It’s Friday night. You’re full from dinner, sprawled on the couch, when someone asks, “So… what’s the plan for next week’s meals?”
You freeze. The fridge is a mystery, the grocery list is scattered, and suddenly meal planning feels like a second job.
In my family, this moment happened every week — a chaotic routine of repeating meals, last-minute grocery runs, and no inspiration.
Imagine this: It’s Friday night. You’re full from dinner, sprawled on the couch, when someone asks, “So… what’s the plan for next week’s meals?”
You freeze. The fridge is a mystery, the grocery list is scattered, and suddenly meal planning feels like a second job.
In my family, this moment happened every week — a chaotic routine of repeating meals, last-minute grocery runs, and no inspiration.
Today, meal planning feels fragmented.
Some people use the Reminders app to jot down grocery lists, hoping they’ll remember which items were for which meal.
Others use the Notes app to loosely outline a weekly plan — but it’s often buried between to-do lists, birthday ideas, and half-written poems.
Then there are recipe apps like PickUpLimes — great for discovering vegan meals, but not designed to sync with what’s already in your fridge or what your week looks like.
Each tool does one thing well. But nothing ties it all together. Nothing thinks the way we do when we’re actually trying to plan, shop, and cook.
Replit AI
Current Methods
Competitive Analysis
To better understand the current food tech landscape and how users plan meals today, I looked at three leading platforms — Tasty, Pepper, and Yummly. Each of these apps tackles meal inspiration and planning from a unique angle:
1. Tasty is a content powerhouse from Buzzfeed that focuses on short-form, visually engaging videos to inspire quick cooking decisions.
2. Pepper is a social cooking app that allows users to post, discover, and comment on home-cooked meals, turning cooking into a shared social experience.
3. Yummly leans into personalization, dietary filtering, smart grocery lists, and recipe discovery, using machine learning to tailor content and help users plan ahead.
Summary
1. Inspiration is everywhere — but intention is rare.
Tasty excels at grabbing attention with engaging content, but it stops short of helping users turn that inspiration into action. There’s little continuity between seeing a dish and planning it for the week ahead.
2. Social validation is motivating — but not everyone wants to share.
Pepper creates a community where home cooks can share and react to each other’s meals. While it makes cooking feel personal and celebratory, not all users are comfortable publicly sharing what they cook — especially if they’re beginners or don’t want to be “on display.”
3. Planning tools exist — but they feel disconnected or overly rigid.
Yummly offers recipe organization, meal scheduling, and smart grocery lists, but the experience can feel bloated and impersonal. Users are offered too many steps or are forced to conform to fixed plans without flexibility.
Opportunity
While apps like Tasty, Yummly, and Pepper each offer something valuable—whether it's recipe inspiration, social cooking, or smart filtering—they fall short of tying everything together in a cohesive, personalized journey. This revealed a clear gap: the need for a warm, user-friendly platform that blends curated inspiration, flexible planning, and grocery list generation all in one place. Plannabelle aims to fill that gap—meeting users where they are, and making meal planning feel more like a joy than a chore.
Information Architecture
Logo Design
The Plannabelle logo is a charming, character-driven design that captures the heart of joyful, stress-free meal planning. Featuring a smiling stovetop with a gently steaming pot, the illustration conveys warmth, coziness, and a sense of calm—mirroring the app’s goal of simplifying daily food decisions. The peachy pink stove and golden oven door evoke comfort and nourishment, while the rounded forest green typography adds a grounded, organic touch. Together, the playful illustration and soft, inviting palette reflect Plannabelle’s mission to turn the question “What’s for dinner?” into a moment of ease, creativity, and everyday delight.
Selecting an AI Tool
I’m not a coder — but I wanted to find a way to take this prototype beyond Figma and learn what comes after design. To do that, I explored and tested three different AI-powered development tools: Google Stitch AI, Replit AI, and Lovable.
Google Stitch AI
I was intrigued by Stitch because it felt like magic — I could describe a screen like “a meal planning homepage with a recipe carousel and search bar,” and it would instantly generate a visually appealing UI layout in code. As someone coming from a UX and storytelling background, this gave me a glimpse into how developers think and structure components. I loved that it gave me editable HTML and CSS, and I could play with styling, spacing, and layout without starting from scratch.
But as powerful as Stitch was for visual scaffolding, I quickly realized its limits. It didn’t let me add real interactivity or logic — for example, I couldn’t simulate recipe selection, calendar views, or API integration. It was incredibly useful as a rapid visualization tool, especially in the early stages, but not enough to bring Plannabelle to life as a working product.
I gave Replit AI a shot to dive deeper into development. While it offered more flexibility in writing and editing actual code, I quickly realized it wasn’t the best fit for my needs — it didn’t support seamless API integration out of the box, and as someone without a coding background, I found the experience overwhelming. It felt more like a traditional coding environment with AI assistance rather than an end-to-end app-building tool.
Lovable AI - Plannable V0.1
After testing other tools, I finally landed on Lovable AI, which felt like the perfect middle ground between design and development. As someone who's not a coder, Lovable allowed me to build a working version of Plannabelle (V0.1) using real logic, structure, and flow — all without writing code. I was able to bring my prototype to life, connect screens, simulate real user interactions, and experiment with functional behaviors. This version helped me visualize how my design decisions played out in context and pushed the project from idea to interactive reality.
View Prototype Here: