App development was once exclusively for seasoned engineers, but AI tools are fundamentally changing who can participate in this space. We’ve watched tools like v0 and Cursor evolve from experimental novelties into essential parts of our engineering workflow, and we’re not alone. According to the 2025 Stack Overflow survey, 65% of developers now use AI coding tools at least weekly, with 82% reporting daily or weekly usage.
From my perspective as Head of Engineering, these tools don’t replace technical expertise. Rather, they accelerate how we build mockups, prototypes, and MVPs, often cutting initial development time in half. We’ve moved from asking “can AI help?” to “which AI tool fits this specific task?” The shift happened faster than I expected.
Here’s what we’ve learned about using v0.app for design generation and Cursor 2.0 for code development, based on real projects, not just theory.
Why AI and no-code tools matter
Building an app from scratch used to require deep programming knowledge, significant time investment, and often substantial capital to hire a development team. AI-driven tools and no-code platforms are lowering these barriers, allowing more people to participate in app creation.
We’ve seen this shift ourselves. Recently, we worked with a non-technical startup founder who used these tools to validate their marketplace concept in three weeks. They built a functional prototype, tested it with real users, and secured initial funding, all before hiring a single developer. This is increasingly common: 41% of all code written in 2025 is now AI-generated or AI-assisted.
For entrepreneurs looking to validate an idea quickly, these tools are invaluable. For developers like us, they streamline the initial stages of projects, letting us focus on complex business logic and architecture rather than boilerplate code.
The combination of v0.app‘s agentic capabilities and Cursor 2.0‘s Composer model has changed how we approach early-stage development. You still need to understand software fundamentals, or have someone on your team who does, but AI can take you remarkably far toward a functional prototype.
Step 1: Creating your UI with v0.app
One of the key components of any app is its user interface, how users interact with the app visually. This is where v0.app steps in. In August 2025, Vercel transformed v0 from v0.dev into v0.app, evolving it from a simple UI generator into a fully agentic AI builder that plans, researches, debugs, and builds autonomously.
How it works now
We use v0.app by describing what we need in natural language. The tool has evolved significantly, it’s no longer just about frontend mockups. v0.app now handles UI, backend logic, content, and application architecture. With over 3.5 million users, it’s become one of the most credible AI development accelerants available.
The evolution of v0 surprised us. Six months ago, it gave you React components. Now it delivers full-stack applications with one-click deployment. That’s not incremental improvement, that’s a fundamental shift in capability.
Want a homepage with navigation, call-to-action buttons, and a footer? Describe it to v0.app, and it generates the design. Need a login screen with authentication logic? Same process. The tool iterates with you until you’re satisfied.
Example prompts we use:
- “Create a homepage layout with a navigation bar at the top, three sections for content, and a footer with social media icons.”
- “Design a login screen for a mobile app with fields for username, password, and a login button at the bottom.”
What v0.app can do now
| Capability | Description |
|---|---|
| Agentic planning | Automatically identifies next steps and manages workflows |
| Full-stack building | UI, backend, content, and application logic |
| One-click deployment | Live production deployment in seconds |
| Web research | Searches and integrates external information |
| iOS app | Build anywhere with mobile access |
Iteration remains key
The first design you get won’t be perfect. We typically go through 3-5 iterations, refining based on specific requirements. v0.app keeps all versions, making it easy to compare approaches or revert to earlier designs.
This iterative process is much faster than coding a frontend UI from scratch. In a recent client project, we explored five different dashboard layouts in an afternoon, something that would have taken days with traditional development.
Save your work
When you’re satisfied with your UI design, export or save the generated code. Note that all code is generated in React and Tailwind CSS, as your app will be built using the Next.js framework. You’ll need this when moving to Cursor for backend development.
Step 2: Setting up Cursor 2.0
Now that you have your UI, it’s time to bring your app to life. This is where Cursor 2.0 comes in. Cursor is an AI-first code editor built on VS Code that helps you write and debug code based on natural language prompts.
In October 2025, Cursor released version 2.0 with two major updates: their proprietary Composer model and a redesigned multi-agent interface.
What changed with Cursor 2.0
Composer model: Cursor’s first in-house AI coding model, built specifically for agentic coding workflows. Composer completes most tasks in under 30 seconds and is reportedly 4x faster than similarly intelligent models. We’ve found this speed makes a tangible difference, iterations feel instant rather than laboured.
Multi-agent architecture: You can now run up to eight agents simultaneously, each working in isolated environments using git worktrees. This means you can tackle the same problem from different angles or handle multiple features in parallel without file conflicts.
The Composer model changed how we prototype. The speed difference sounds incremental on paper, 4x faster, but in practice, it transforms the feedback loop. You think, test, adjust, and move forward without breaking flow. That matters more than raw capability for early-stage work.
Cursor 2.0 key features
| Feature | Benefit |
|---|---|
| Composer model | 4x faster than alternatives, <30 second task completion |
| Multi-agent support | Run up to 8 agents in parallel with git worktree isolation |
| Built-in browser | Test and refine code automatically |
| Agent-first interface | Designed around outcomes, not just files |
| Flexible model selection | Plan with one model, build with another |
Create a project
To begin, create a new project in Cursor. Most web and mobile apps today are built on development frameworks, pre-packaged sets of tools and components that make building apps easier. Here’s a quick overview:
- Next.js: A React-based framework popular for building web apps
- React Native: Used to build mobile apps that run on both iOS and Android
- Vue.js: Known for its simplicity and flexibility in web development
We often start with a Next.js project template in Cursor. These templates provide a solid foundation, especially when integrating the code generated by v0.app.
It’s important to note that v0.app creates code based on shadcn/ui, which is a component library for Next.js projects. If you’re following this method, you’ll need to install shadcn/ui in Cursor, then paste the code from v0.app.
Tip: Use templates to accelerate development
Starting with a pre-made template reduces manual setup. In most cases, you only need to customise components and connect the UI elements you created earlier. This is where we’ve seen the biggest time savings, developers report saving 30-60% of time on routine coding and testing tasks when using AI tools effectively.
Step 3: Writing code with Cursor and Claude
Once your project is set up, you’ll use Cursor to generate code. Based on the prompts you provide, Cursor can write code for both front-end and back-end functionalities. If you’re working with the UI code generated by v0.app, simply upload or copy that code into Cursor and start building out the functionality.
Iterate and debug
App development is rarely linear, and you’ll inevitably run into bugs or issues. Cursor 2.0’s Composer model is designed to help you debug quickly. By describing the issue you’re facing, Cursor can generate solutions or suggest edits to your existing code.
We’ve found that the quality of your prompts directly impacts output quality. Specific, context-rich prompts consistently outperform vague requests. For example, “Add email authentication with magic links using our existing users table” works better than “Add login functionality.”
Example prompts we use:
- “Add a login authentication API to this form using magic links and our existing users table.”
- “Debug the button click event on the homepage so it routes to the correct page.”
- “Optimise the loading time of this component by implementing lazy loading.”
The iteration process
In a recent project, we used Cursor to iterate through five design variations for a client’s dashboard in a single afternoon. Each iteration took minutes rather than hours. The agent mode handled routing logic, API connections, and even basic error handling, work that traditionally would have consumed a full development day.
It’s an iterative process, but Cursor 2.0’s speed makes rapid experimentation practical. The tool’s value isn’t just in generating code, it’s in enabling rapid hypothesis testing. You can try an approach, see results immediately, and pivot without significant time investment.
What’s the end result?
After spending time iterating on both frontend and backend, you’ll have a working prototype of your app. It won’t be production-ready or optimised for thousands of concurrent users, but it serves as an excellent proof of concept.
From our experience, a basic MVP built with these tools typically requires 20-40 hours of focused iteration. You can take this prototype to investors, potential users, or developers who can help refine it further. For entrepreneurs with technical knowledge about setting up servers, domains, and basic marketing, you could even launch it yourself to test market fit.
The current state of AI adoption supports this approach: DX’s Q4 2025 report shows 91% AI adoption among engineering teams, with developers consistently reporting faster prototyping and iteration cycles.
Pros and cons of building apps with AI tools
While these AI tools are powerful, they’re not magic solutions that transform anyone into an app developer overnight. Here’s what we’ve observed from using them in real projects:
Comparison table
| Advantages | Limitations |
|---|---|
| Speed: AI drastically reduces time from idea to prototype. We’ve seen 50%+ time savings on initial builds. | Technical knowledge still required: Understanding frameworks, debugging, and architecture remains essential. |
| Cost efficiency: For startups, these tools provide an affordable way to test ideas without hiring a full team initially. | Reliance on AI: Complex coding issues may still require experienced developer review. |
| Lower entry barrier: 82% of developers now use AI tools daily or weekly, showing widespread accessibility. | Limited scalability: AI-generated apps may not scale well. Growth requires rethinking your tech stack. |
| Streamlined UI design: v0.app makes UI mockups accessible without design tool expertise. | Not suitable for complex projects: Great for MVPs but falls short for apps with complex business logic. |
| Proven productivity gains: Developers save 30-60% of time on coding, testing, and documentation with AI tools. | Code quality concerns: AI solutions are often “almost right, but not quite,” requiring human refinement. |
Quick reference: When to use these tools
Best use cases:
✓ MVP validation and rapid prototyping
✓ UI mockups and design iteration
✓ Feature testing and experimentation
✓ Learning new frameworks or languages
When to bring in developers:
✗ Production-grade applications
✗ Systems requiring high scalability
✗ Complex business logic and workflows
✗ Security-critical applications
From my perspective: We use these tools for initial exploration and prototyping, but we don’t ship AI-generated code to production without thorough review. The balance is using AI for acceleration, not substitution. Know when you’re prototyping versus building for scale.
Final thoughts
AI tools like v0.app and Cursor 2.0 are revolutionising how we think about app development. From my engineering perspective, the pace of evolution has been remarkable. Six months ago, v0 generated React components. Today, it builds full-stack applications. Cursor 2.0’s Composer model completes tasks in seconds rather than minutes.
These tools genuinely lower the entry barrier, allowing more people to turn ideas into functioning prototypes without extensive coding knowledge. The statistics support this: 65% of developers now use AI coding tools weekly, up significantly from previous years.
However, building an app remains a collaborative process. Even with AI, having the right team and expertise takes you from a basic prototype to a successful app in the marketplace. The future isn’t AI replacing developers, it’s AI amplifying what skilled developers can accomplish. We’re seeing tools evolve from assistants to collaborators, but human judgment, architecture decisions, and quality oversight remain irreplaceable.
The key is understanding where these tools excel and where human expertise is non-negotiable. Use AI for rapid iteration and exploration. Bring in experienced developers for production readiness, scalability, and long-term maintainability.
Looking to turn ideas into scalable solutions?
At WeAreBrain, our team specialises in tackling tough challenges and transforming them into smart, seamless solutions. Our expert engineers and developers work across all key areas to deliver services tailored to your business needs. Whether it’s frontend, backend, mobile, or AI, we’ve got the creativity and skills to handle the tech side of things.
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