Can you ship a mobile app mostly by prompting? I set out to find out. I’m Tiago Pinto, a Full-stack Developer at AppX, and I recently built a simple, but complete, mobile app using Cursor and its “vibe coding” workflow. The goal was straightforward: measure how quickly and efficiently AI-assisted tooling can take you from idea and rough design to something you can actually install and use.
Cursor’s pitch is simple: describe what you want, behavior, layout, even the “vibe” and it turns prompts and sketches into working code. That makes prototyping surprisingly fast, especially if mobile UI isn’t your daily bread. And while experiments like this are common right now, what’s really interesting is how (and whether) this approach fits the development workflow of a software house.
In this post, I’ll first unpack the core ideas behind vibe coding and how Cursor implements them. Then I’ll walk through my build: what worked, what didn’t, and how long it took to get from concept to a running app.
What is Vibecoding?
Vibe coding is a collaborative way of programming where you and an AI work as a team to bring your ideas to life. Instead of writing every line of code yourself, you guide the AI with natural-language prompts, watch it generate solutions, and then refine the results until they match your vision. The process typically flows like this:
- Prompt: You describe what you want in simple, clear terms. This could be a feature, a function, a webpage layout, or even an algorithm.
- AI Generate: The AI interprets your prompt and produces code that attempts to solve your problem.
- Execute and Observe: You run the code, see how it behaves, and observe the results. Does it do what you envisioned? Are there errors or unexpected outcomes?
- Refine: Based on what you observed, you adjust your prompt, tweak the code, or ask the AI to improve or optimize it.
- Repeat: You iterate through this cycle – prompt, generate, execute, refine – until the final solution works smoothly and efficiently.
In essence, vibe coding turns programming into a dialogue between human creativity and AI capability. You focus on the ideas and high-level design, while the AI handles the details, making coding faster, more experimental, and surprisingly playful.
Cursor
Cursor is a next-generation AI-powered code editor that turns vibe coding from concept into practice. Instead of writing every line manually, you can describe what you want in plain language, and Cursor generates the code for you, helping you focus on higher-level logic, design, and experimentation. It’s like having an intelligent coding companion right in your editor.
Key Features of Cursor
- Smart Autocomplete: Predicts your next lines of code based on context, speeding up coding while maintaining style consistency.
- Code Generation: Creates entire functions, components, or scripts from natural-language prompts.
- Refactoring & Optimization: Automatically suggests improvements, cleans up messy code, and even rewrites multiple lines at once.
- Integrated Debugging: Test and debug directly in the editor while receiving AI insights for potential issues.
- Collaboration Tools: Seamlessly integrates with GitHub, Slack, and other tools to support team workflows.
- Privacy & Security: Offers local-first or private modes, so your proprietary code stays secure.
- Customizable Workflows: Fine-tune the AI to match your coding style or project conventions.
Best Practices for Vibe Coding with Cursor
Vibe coding with Cursor can supercharge your programming workflow, but to get the most out of it, it helps to follow a few best practices. Here’s how to make your AI-assisted coding sessions smooth, productive, and creative:
1. Start with Clear Prompts
The AI works best when it understands exactly what you want. Be specific about the functionality, expected inputs and outputs, language, and style. For example:
“Create a React component that displays today’s date and a friendly greeting, styled with TailwindCSS.”
Providing clear instructions reduces ambiguity and ensures the AI generates more accurate and useful code.
2. Work Iteratively
Vibe coding is a conversation, not a one-shot process. Generate, test, refine, and repeat. Cursor makes this easy: you can quickly adjust prompts, regenerate code, and see the results in real time. Iterative refinement helps produce higher-quality solutions and gives you full control over the final code.
3. Validate Everything
Even though Cursor produces functional code, always review and test what it generates. Run unit tests, check edge cases, and verify logic. This ensures reliability, especially for production-level code.
4. Leverage AI Features Wisely
Cursor offers features like smart autocomplete, automated refactoring, and multi-line rewrites. Use these tools to speed up repetitive tasks, clean up messy code, or explore alternative approaches—but remain the decision-maker. You’re guiding the AI, not outsourcing critical thinking.
5. Keep Context in Mind
Cursor performs best when it has context: past code in the project, naming conventions, and file structures. The more consistent your project setup, the more accurate and cohesive the AI suggestions will be.
6. Protect Privacy and Security
Avoid sharing sensitive or proprietary code unless you’re using local/private modes. Always review generated code for potential security risks, especially when dealing with authentication, API keys, or sensitive data.
7. Learn and Document Along the Way
Every iteration is a learning opportunity. Keep track of effective prompts, snippets, and patterns that work well. This builds a personal “vibe coding playbook” you can reuse in future projects.
My Experience
To put vibe coding with Cursor into practice, I decided to replicate an existing mobile app using ReactJS. My approach was visual and iterative: I used screenshots of the app as reference material and fed them into prompts. I was honestly surprised at how well the AI interpreted the images – Cursor was able to translate them into functional components and layouts almost seamlessly, allowing me to rebuild the interface and functionality step by step.
The process unfolded in phases. I began by having Cursor generate the main dashboard, using mock data to visualize results immediately. Once the core layout was working, I added authentication, secondary pages, and backend integration for real data. Whenever the AI’s output didn’t match the desired layout, or a page broke after adding another, I refined prompts or made manual adjustments. Finally, I integrated CapacitorJS to test the prototype on mobile devices, completing the app.
This exercise highlighted both the strengths and nuances of vibe coding. Cursor allowed for rapid prototyping, implementing navigation, UI elements, and basic API integration quickly. Yet, success depended on clear and precise prompts; vague instructions required multiple iterations to reach the intended result. Challenges included layout inconsistencies and maintaining code organization, and for experienced developers, expect some tasks to take longer than coding them manually.
Reflections on AI-Assisted Development
Overall, this project was a hands-on proof that Cursor can speed up delivery without taking control away from the developer. With screenshots, clear prompts, and tight iteration, I rebuilt a mobile app quickly and kept quality in check, real, useful acceleration rather than a demo-night party trick.
For a software house, the value is practical. AI helps you move from ticket to working prototype fast, trim boilerplate, and spend more time on architecture, UX, and business logic. It shines on spikes, MVPs, and internal tools where rapid feedback matters, and it can unblock smaller teams without bloating headcount.
But speed only pays off with guardrails. AI is a strong collaborator, not a substitute for engineering judgment.
Here’s what AI does not do: decide product priorities, make architectural trade-offs, guarantee security/compliance, perform code reviews, ensure performance/accessibility, or own production readiness. Those remain firmly human responsibilities. AI can scaffold configs, but the team owns safe releases, CI/CD pipelines, env parity, secrets management, migrations, feature flags, rollbacks and monitoring/alerts.
Treat generated code like code from a junior pair: review it, test it, and make it fit the house style. Keep ownership clear and handoffs clean: small PRs, CI checks, unit/UI tests, security and license scanning, and adherence to your design system. Make prompts first-class artifacts (commit them, version them, link them to tickets) so changes are traceable and knowledge outlives any one developer.
Used this way, vibe coding is a professional way to integrate AI into the delivery workflow: it boosts productivity, supports creativity, and helps teams ship more with the same standards. The balance is simple: let AI accelerate the boring parts, but never outsource the engineering!
