I enjoy cooking, but I usually like to have a recipe to guide me so I don’t feel like I’m wasting my time by making subpar food. Cookbooks get expensive and don’t quite have the variety I need. The internet is full of great recipes, but sometimes it’s hard to find exactly what you want. And then, when you find what you want, there’s a whole essay about the dish that you have to scroll through to get to the recipe. And then there’s using the recipe. Do you print it out? Do you scroll back and forth between the ingredients list and the instructions? Do you keep the printouts in a binder or in a favorites folder on your computer or phone? I just want a way to be able to quickly find recipes, collect the ones I like, and easily use those recipes. Why am I writing about cooking on this blog, you might ask? It’s because I’ve spent the last six months building a solution, and that solution is https://cookcloud.me/ Sure, there are other recipe / meal planner apps out there, but I wanted a project to test out a lot of the emerging AI technology out there while building a tool that did everything I wanted.
The Vision: What CookCloud Needed To Be
Once I had decided on the thing I wanted to build, I used a combination of ChatGPT and Claude to help me brainstorm the core features of the app and to plan out a reasonable roadmap for features to build along the way. In hindsight, I think the set of features that I defined as the MVP weren’t minimal enough, and I probably could have launched sooner if I had been a bit less ambitious. My initial plan, which I announced on social media was the following:
Core Features
- Recipe Search
- Personalized meal planning – Generate weekly meal plans based on user preferences ( diet, allergies, goals)
- Grocery List Automation – Auto-generate shopping lists from meal plans
- Recipe Suggestions – Provide curated or AI-recommended recipes based on available ingredients
- Nutritional Tracking – display calorie and macro nutrient breakdowns for meals
- Meal Scheduling – Allow users to assign meals to specific days/times
- Ingredient Substitutions
I realized fairly early into the process that the recipe suggestion feature was going to have to be a roadmap item. I’m going to need to collect lots of user activity data points to be able to achieve this one. Also, looking back, I realize that I could have had a very useful app much sooner if I had left the meal planning/scheduling and grocery list items as roadmap items as well. These added a lot of effort to the project that I didn’t anticipate, and I committed to them far too early to pivot.
User Experience Enhancements
These are some of the roadmap items I initially planned to add:
- Smart Pantry – Track ingredients at home and suggest meals based on what’s available
- Barcode Scanner – Quick-add grocery items via barcode scanning
- Grocery Delivery Integration – Connect to Instacart or other similar service for easy ordering
- Multi-User Support – Family meal planning with a shared grocery list
- Custom Recipes
- Progress Tracking – Track meal adherence to health goals
- Meal Prep Mode – Enhanced interface for cooking recipes
As it turns out, custom recipes was a natural progression once I got a handle on how I wanted to save recipes in the app, so that made its way into the core features. Meal Prep Mode was something that I wanted too much to wait on a later release. I think Grocery Delivery integration is going to be a fairly light lift, but the rest are going to involve significant effort.
Because some of these features are going to be so effort intensive, I also decided to build a feedback system. I built a GitHub integration so select GitHub Issues get published on the site on the Roadmap page. Registered users can upvote features they want the most as well as comment if they have ideas of how they want to shape those features. And, since I was already integrating with GitHub, I decided to also add a Release Notes page. These are select merged pull requests, showing the relevant issues (labeled as features).
AI Tools Arsenal
I used Claude and ChatGPT for brainstorm what features it should have and how I should plan them out. I started out with a Saas starter project based on Django, and leveraged Cursor to build out most of the features. Cursor didn’t always build exactly what I wanted, but it got me at least 80% of the way – think of it as advanced scaffolding. Amazon Q is an advanced autocomplete engine. The places where it stood out the most were times where I wanted to make several similar changes (things you might use a regex for if you wanted to take the time to build the expression). It sped up my progress writing code tremendously.
Sometimes Cursor would change things I didn’t want it to change or put things in the wrong places. To some degree, this is something that rules can prevent, but I’ve also had several instances where it did things that the rules I had in place told it not to do. AI coding tools aren’t perfect, and they aren’t magic, but they can be highly useful in the right hands. The meal planner interface, I built out as a separate submodule using MGX.dev. It may be gimmicky, but the results I got from it were far better than most tools I’ve tried. It asks a lot of followup questions and asks for periodic feedback along the way. I had to ask it to make a few revisions, but overall, I was very impressed. The down-side is that it’s token based, and you get a fixed number of tokens per month, and I spent them all in a matter of a few days. So, it’s not something I’d want to use regularly, but for quickly standing up a complex interface, I would strongly recommend it. Currently, I’m working with Claude code, and while, like Cursor, doesn’t always give flawless output, it is miles ahead in terms of quality and reliability. One of the big advantages of it is that it makes notes in markdown files to keep track of the project details since it can’t possibly hold the entire codebase in its context window. It has been much more consistent with putting things in the right place, maintaining conventions, etc, and it even creates unit tests without being prompted. It can also run test cases and linting tools and fix the issues that arise.
Final Thoughts
Building CookCloud has been one of those projects that started relatively simple and turned into something much more complex than I had anticipated. What began as “I just want to find recipes without scrolling through life stories” evolved into a full-featured meal planning platform with AI integration, custom recipe creation, and community feedback systems.
The biggest lesson I’ve learned is that even with the most powerful tools, the fundamentals stay the same: Measure twice, cut once. Planning is everything. I wish I had been more rigorous about the MVP scope. I’ve very happy with where the project is now, but I think I could have gotten more user feedback earlier if I had launched with a more focused set of features.
Right now, CookCloud is handling everything I originally wanted it to do. I can quickly search for recipes, save the ones I like. I can even import recipes I find outside the app, and most importantly, I have an intuitive interface for following those recipes which I haven’t seen anywhere else.
Get In Touch
You can check out CookCloud at cookcloud.me to see the kind of polished, feature-rich applications that are now achievable with modern development approaches. If you’re curious about what a custom solution might look like for your business, or if you want to discuss how AI-powered development could accelerate your next project, I’d be happy to have that conversation.