How I Built a Mobile App Without Writing a Single Line of Code
Everyone talks about building web apps fast with AI, but what about real mobile apps? In this post, I’ll share my process for building a fully working mobile app—complete with push notifications, subscriptions, and clean code— without touching a single line of code myself. Instead, I leveraged AI workflows, boilerplates, and a little bit of patience. If you’re curious about validating ideas quickly, shipping fast, and getting real apps into the App Store, this is for you.
Why Speed Matters
The key to success isn’t just having an app idea—it’s validating it quickly. You don’t want to spend months coding only to find out no one wants the product. That’s why shipping fast is essential. With analytics, push notifications, subscriptions, and sign-in already handled, you can focus on testing your idea in the real world.
The Problem With No-Code App Builders
Platforms like Lovable or Bold are fun to experiment with, but they fall short when it comes to real monetizable apps. They don’t give you native features like payments, push notifications, or proper app store submission support. That’s why I turned to a different approach: combining AI-driven workflows with a solid React Native boilerplate.
The Workflow I Used
- Start with a boilerplate app (Expo + Supabase + Tailwind + RevenueCat).
- Use AI to generate requirements (PRD) and break them down into tasks.
- Feed the project structure and requirements into AI for clean, maintainable code generation.
- Iteratively let AI implement tasks while validating the app after each step.
I based much of this process on a blog post and video by Dan, who showed how to do something similar for web apps. I adapted it for mobile development and was blown away by how far it could go.
The App I Built
My project was a newsletter reader app—a cleaner, distraction-free way to read newsletters without clutter from other emails. Think Kindle or Apple Books, but for newsletters. The app lets you manage senders, filter out spam, and enjoy a smooth reading UI.
AI handled onboarding, sign-in, folder structures, hooks, and even subscriptions. The only real manual effort was setting up the boilerplate and guiding the AI with well-structured prompts.
What Worked (and What Didn’t)
- Worked: Task automation, clean folder structures, native features, subscriptions.
- Didn’t Work So Well: Overly complex task lists (25+ tasks, many unnecessary), parsing messy HTML emails, and Apple Mail integration.
Lesson learned: aim for fewer, well-defined tasks (ideally under 10), and be extra clear about what’s already in your boilerplate so AI doesn’t waste time duplicating effort.
Final Thoughts
I’m still amazed: a working mobile app without writing a single line of code. Sure, it’s not perfect and some polish is needed, but this method proves that with the right setup, AI can take care of the heavy lifting. My advice? Use this for smaller apps, validate your idea, and then iterate. The real limit is your creativity.
Should I try building another app like this? Let me know what I should tackle next.
The Single Best Way to Build Profitable Apps Fast (Without Writing Code)
Everyone wants to build an app quickly, but many "quick" solutions fail to deliver the crucial features needed for a profitable business. Tools like Lovable or Bold might get a working app, but they leave out payments, push notifications, and other native features essential for monetization. The real goal is to validate your idea as fast as possible. Here’s the proven process for building a full-featured mobile MVP without writing a single line of code.
Why Typical "Quick" Builders Fall Short
If you want to build an app that actually makes money, you need a solid foundation. You need:
- Payments & Subscriptions
- Push Notifications
- Native Features
- Assistance for App Store Submission
- Analytics & Sign-In
This process is about building fast, shipping fast, and validating fast with a complete, monetizable codebase.
The Blueprint: Building a Newsletter Reading App
The example project is a "Kindle-like" newsletter reading app. It solves a real problem: a cluttered email inbox is a terrible reading experience. This app will pull in newsletters and display them in a clean, focused, native UI.
The Step-by-Step, No-Code Process
Step 1: Generate Detailed Requirements with AI
Start by using a powerful AI model (like GPT-4). The prompt is critical. You must be hyper-detailed:
"I would like to create concise function requirements for the following application..."
Describe your app's purpose, features, and desired tech stack in extreme detail. For UI inspiration, grab screenshots from Dribbble and feed them to the AI as a reference.
Step 2: Create a Bulletproof Product Requirements Document (PRD)
Take your generated requirements and use them in a specialized "Create PRD" prompt (shoutout to Dan's blog for the inspiration). This PRD will be your project's bible. The most important part is the technical requirements section. You must specify:
- Your pre-existing boilerplate structure (using Expo, Supabase, Tamagui, etc.)
- How you want the code structured for maintainability
This step ensures the AI generates clean, logical code, not spaghetti, making future bug fixes possible.
Step 3: Set Up Your Boilerplate & Environment
Clone your starter kit (e.g., Native Express). Get it running locally by installing dependencies and setting up necessary services like Supabase and RevenueCat. A solid boilerplate is non-negotiable; it handles the boring setup so you can focus on features.
Step 4: Implement Taskmaster MCP for Cursor
This is the magic. Install the Taskmaster MCP (Model Context Protocol) for your code editor (Cursor). This allows the AI to break down the PRD into actionable tasks and execute them autonomously.
Step 5: Let the AI Go to Work
In Cursor, using an agentic mode, point the AI to your PRD and tell it to set up the initial tasks. It will analyze your project and generate a detailed task list. Your job is to review these tasks. Refine them, remove unnecessary ones (e.g., "Accessibility Implementation" for an MVP), and ensure they align with your goals.
Once the task list is refined, simply command: "What's the next task I should work on? Please consider dependencies and priorities." Then, "Implement task X and all its subtasks." The AI will now code, build, and troubleshoot on its own. Your role is to monitor, test, and provide feedback when things break.
The Result: A Functional, Monetizable App
After letting the AI work, you'll have a real, functioning app. The newsletter reader included:
- Onboarding & Sign-in Flows
- A "New" Tab for incoming newsletters
- A "Read" Tab for finished items
- A clean, native reading experience
- A Sender Management screen to control which newsletters appear
The code was well-structured, separated into logical hooks and components, providing a maintainable base for future development.
Key Takeaways & Lessons Learned
- Preparation is Everything: The time spent on a detailed PRD and a solid boilerplate pays off massively in development speed.
- Curate the Task List: The AI will generate many tasks. Be ruthless. Cut everything that isn't essential for your MVP (e.g., extensive testing, background sync). Aim for under 10 core tasks.
- Boilerplate is Key: A high-quality starter kit prevents the AI from wasting time on setup and ensures a professional foundation with monetization baked in.
- This Isn't Magic: It's a process. You must test after each major task, report bugs to the AI, and guide it. But you truly don't have to write the code yourself.
This method fundamentally changes the app development game. It's not about playing around with simple tools; it's about strategically using AI to build real, profitable businesses at an unprecedented speed. The only limit is your creativity.
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