Mastering vibe coding: transform your app development experience (and how it compares to Bubble.io)

1. Introduction: Vibe coding is here, what does it mean for founders?

Vibe coding, also referred to as 'ai coding', is a development approach where a generative AI (LLM) turns clear, human-readable instructions into working code.

You type out your instructions "prompt" and the AI will write the code for you. This shines for rapid prototypes, internal tools, and speeding up production delivery through tight “prompt → code → verify → refine” loops.

If you’re a non-technical founder, you might have heard of no-code platforms like Bubble.io. They let you build apps visually, without writing code. Vibe coding sits at the other end: it gives developers superpowers, but there is no visual interface and might still requires technical knowledge to finish the app.

In this article, we’ll break down what vibe coding is: a new kind of software development enabled by AI and natural language prompts, how it works, and when it makes sense compared to tools like Bubble.

Finally we'll answer the question is it the right way to launch your software product?

2. What is vibe coding, and why does it matter?

Vibe coding, also referred to as ‘AI coding’, is a development approach where a generative AI (LLM) turns clear, human-readable instructions into working code. The term vibe coding describes this new approach to software development (with 'vibe code' as the output of this process), where instead of hand-writing every line, you describe the desired behavior, constraints, and environment, the model generates project components, tests, and even migrations. This shines for rapid prototypes, internal tools, and speeding up production delivery through tight “prompt → code → verify → refine” loops.

Andrej Karpathy, co-founder of OpenAI and former AI leader at Tesla, has been influential in popularizing vibe coding and shaping its direction within the AI community. Business Insider has covered the rise of vibe coding as a new approach in software development, highlighting its global impact and the shift it represents in programming workflows.

Why it matters:

• Focus on functionality and value, not syntax
• Dramatically shorter time-to-first-feature
• Developers can iterate faster and test more ideas
• Non-engineers can participate earlier in the development process

By adopting this approach, developers can embrace exponentials and vibes embrace exponentials, trusting AI to handle technical details and focusing on high-level ideas and outcomes.

With the right setup, developers can go from prompt to working backend in a single afternoon. In this workflow, it's common to forget that the code even exists, as the focus shifts to outcomes and the process rather than the code itself.

This paradigm shift means the code written by AI quickly becomes vibed code that grows beyond the developer's usual comprehension. The relaxed, experimental nature of vibe coding allows the code to grow organically, often without traditional review or deep understanding, emphasizing intuition and rapid iteration over manual scrutiny.

3. Getting started with vibe coding: your first steps

Diving into vibe coding is easier than you might think, especially with today’s advanced AI tools designed to help you write code from natural language prompts. The journey begins by selecting an AI tool that fits your needs, popular choices include Replit Agent and Google AI Studio, both of which are built to assist in generating functional code based on your instructions.

Before you start, it’s important to have a clear business idea or app development concept in mind. Think about the problem you want to solve or the type of app you want to build. Once you have your idea, describe your project to the AI agent in plain English, focusing on what you want the app to do rather than how the actual code should look. The more specific your natural language prompts and additional context, the better the generated code will match your vision.

As you interact with the AI models, you’ll iteratively refine your prompts, review the generated code, and provide feedback to improve the results. This process allows you to quickly move from concept to functional code, making vibe coding a powerful approach for rapid app development and prototyping.

3. A real paradigm shift in app development

The rise of vibe coding fundamentally changes how software is created and who gets to participate. Traditionally, building an app meant manually writing code line by line, a process that highlights the persistent challenges of building apps and the crucial role of the software developer in ensuring code is understandable, reliable, and maintainable. Today, with the advent of powerful AI tools and large language models, developers can generate functional code simply by describing what they want in natural language.

This AI-assisted coding approach allows anyone with a clear idea to turn it into a working prototype or even a complete application, no years of manual coding experience required.

This democratization of app development means that more people can bring their business ideas to life, experiment with throwaway weekend projects, or rapidly prototype new features without being limited by their coding background. While low code tools and platforms have made app creation more accessible by enabling rapid prototyping and deployment with minimal traditional coding, vibe coding offers a different approach by leveraging natural language and AI to generate code directly. AI-generated code can be reviewed, tested, and refined by experienced developers to ensure it meets the highest standards of code quality, maintainability, and security. As AI-assisted coding becomes more prevalent, the role of the developer evolves, from manually writing every function to collaborating with AI agents acting as a pair programmer, reviewing generated code, and guiding the overall architecture.

4. How vibe coding works in practice

A practical loop looks like this:

1. State the task: For example, “Build a FastAPI service that converts currency and stores request history.”
2. Provide context and constraints: OS, Python 3.11, PEP8 style, FastAPI, SQLite, etc.
3. Ask for a scaffold: Directory structure, Dockerfile, base tests
4. Run locally and collect feedback (i.e., run stuff to see what happens, using error messages as clues for debugging and refining the app): Test endpoints, adjust behavior, handle edge cases
5. Iterate with follow-up prompts: “Add rate limit,” “Move config to .env,” “Add test for zero amount”, use these prompts to add features or sometimes make random changes based on AI suggestions
6. Commit in small diffs: Use linters, tests, and short PRs
7. Document everything: README with commands, .prompt.md for reproducibility

5. Working with AI models: the engine behind the vibe

At the heart of vibe coding are powerful AI models, specifically, large language models, that make it possible to write code with just a few lines of natural language. These AI tools, like Cursor Composer and Replit Agent, interpret your instructions and generate functional software, transforming the way both experienced developers and non-coders build apps.

For experienced developers, AI-assisted coding means less time spent on boilerplate and more time focusing on high-level architecture and unique features. For non-coders, it opens the door to building web apps and experimenting with throwaway weekend projects without needing to master programming languages. The coding experience becomes more about guiding the AI, refining prompts, and testing the results, rather than manually writing every line of code.

By leveraging these AI models, users can rapidly prototype, deploy, and iterate on real world applications. Whether you’re building an entire application or just testing out a new feature, vibe coding with AI assistance accelerates the process and makes software development more accessible than ever.

6. Benefits of vibe coding

• Rapid prototyping: Clickable versions in hours, not weeks
• Fastest path from idea to deployment
• Less boilerplate: Generate scaffolds, CRUD, migrations, tests
• Consistent quality: Style guides, reusable prompt templates
• Enables experimentation: Low-cost iteration for developers
• Deploy your app directly: Launch your application from the development environment, often with one-click deployment for seamless publishing.

Vibe coding can be the best tool for rapid prototyping and experimentation, especially for those seeking the fastest path from idea to deployment.

7. Working with existing code

Vibe coding isn’t just for new projects. It works well for:

• Explaining and auditing existing code
• Goal-driven refactors (e.g. layering, interface extraction)
• Safe migrations (e.g. sync → async)
• Adding incremental features
• Integrating new logic with minimal disruption

Modern LLMs can understand long context windows, recognize architectural patterns, and even suggest contract tests and schema changes.

8. The evolving role of software engineers

Vibe coding, or AI enabled coding, shifts the focus shifts from manual coding to orchestrating AI agents and ensuring the quality of generated code. Professional developers are now expected to work alongside AI models, using natural language prompts to produce code and then refining it to meet specific requirements.

Software engineers must pay close attention to code quality, security, and maintainability, even when much of the code is AI-generated. The role of the developer becomes more about reviewing, testing, and guiding the AI, rather than writing every function by hand. As AI assistance becomes more common, the line between programmers and non-programmers blurs, allowing a wider range of people to contribute to coding projects.

However, experienced developers remain essential for overseeing the process, catching subtle bugs, and ensuring that the final product meets professional standards. The future of software engineering will be defined by collaboration between humans and AI agents, with a strong emphasis on clear communication, robust review processes, and continuous learning.

9. Limitations and risks

• Requires technical oversight: You still need developers to review, test, and secure the code
• Security is not automatic: Must add rate limits, secrets management, dependency checks
• Scaling is your responsibility: AI won’t architect your app
• Code quality is prompt-dependent: Vague input = vague output
• Don’t ask AI to do the dumbest things: Relying on AI for trivial or careless tasks can introduce subtle bugs or unnecessary complexity.
• Beware of copy paste, copy paste stuff, and paste stuff: Simply copying and pasting code from AI outputs without proper review can lead to security vulnerabilities and poor maintainability.
• Don’t skip reviewing diffs anymore: Failing to check code changes generated by AI increases the risk of introducing errors and degrading code quality.

Building a robust, scalable app with vibe coding is possible, but only with solid engineering behind it.

10. Security considerations in vibe coding

Security should always be top of mind when using vibe coding to build applications. Since much of the code is generated by an AI tool, there’s a risk that vulnerabilities or errors could slip through unnoticed. Relying solely on generated code without proper oversight can expose your app to security flaws, especially if the AI model isn’t configured with best practices in mind.

To safeguard your projects, it’s crucial to involve professional developers in the review and testing process. Regularly update dependencies, monitor the code for potential issues, and use automated tools to scan for vulnerabilities. Don’t assume that the AI tool will always produce secure code, take proactive steps to validate and harden your application. By prioritizing security at every stage of coding, you can ensure that your vibe-coded software is both reliable and safe for users.

11. Best practices for reliable results

• Use the “context → task → definition of done” format
• Request diffs and justifications
• Automate quality gates: Ruff, Flake8, Black, Mypy, Pytest
• Add validators: JSON schemas, OpenAPI specs
• Version prompts: Store them with your codebase
• Work in small cycles: Easier to review, test, and revert
• Document commands: Use Makefile or Taskfile with clear CLI steps
• Utilize a text box for input: When working with AI tools, enter your prompts or user data into a text box to ensure clear and structured communication.

Example of a good follow-up prompt: “Add a 30-per-minute IP rate limit to app/main.py; on overflow return 429 with {“error”:”rate_limited”}. Update tests to assert this limit. Provide a diff and test command.”

12. Tools for vibe coding

• Lovable: Generates React + Tailwind UIs from prompts
• Cursor: AI-first IDE with integrated context
• Base44: Conversational builder for full-stack apps
• Bolt.new / Tempo / Windsurf: Fast, lightweight prototyping tools

13. What is Bubble.io and how does it compare to vibe coding?

Bubble.io is a mature no-code platform that lets founders build full apps with visual tools. It includes:

• Built-in database
• Workflows and logic editor
• Privacy rules and permissions
• Plugin ecosystem

It’s ideal for non-technical founders who want to:

• Launch SaaS MVPs
• Build CRMs, admin dashboards, internal tools
• Iterate live with real users

Compared to vibe coding:

• Bubble is easier to actually finish apps (no code needed)
• More structured and secure by default
• Less flexible at scale (no code export, limited backend control)

However, despite the advancements of both platforms, building apps remains a complex and challenging process, and founders should be prepared for persistent difficulties in app development.

If you’re non-technical and want something stable, Bubble is often the better choice.

11. When to use each (or both)

Use vibe coding when:

• You have developers
• You want to own the codebase
• You’re building APIs, services, or automation

If you prefer to avoid traditional coding for web app development, consider these no-code tools for building web apps.

Use Bubble.io when:

• You’re a solo founder or early-stage team
• You want to be able to adapt the app using a visual editor
• You want a reliable MVP without hiring devs

Or use both:

• Prototype with vibe coding
• Build your MVP in Bubble
• Rebuild with code once you have traction

14. The future of vibe coding: where is this all heading?

The future of vibe coding is bright, with rapid advancements in AI models and tools set to further revolutionize software development. As AI-assisted coding becomes more mainstream, we’ll see a true paradigm shift: non-coders and professional developers working side by side to create high-quality, functional software at unprecedented speed.

Vibe coding will continue to offer the fastest path from idea to implementation, making rapid prototyping and deployment of web apps more accessible than ever. However, as the technology evolves, it will be essential to maintain a strong focus on code quality, security, and maintainability. Expect to see innovative uses of vibe coding, such as integrating AI-generated code with existing codebases and applying it to real world applications across industries.

Ultimately, the future of vibe coding will depend on finding the right balance between the power of AI assistance and the expertise of human developers. By embracing this new approach, the software development community can unlock new possibilities and build better, smarter applications for everyone.

15. Conclusion: Build fast, but build smart

Vibe coding shifts how we think about development. With clear prompts, fast feedback, and smart iteration, it can take you from idea to prototype faster than ever before.

But it’s not a silver bullet. Use it with discipline, planning, and experienced oversight, especially if you plan to launch to real users. Unfortunately the AI can hallucinate, or even change parts of your app which you did not intend to change, which can be highly problematic when you have live users.

Meanwhile, Bubble remains a strong option for early-stage founders who want results without writing a single line of code, but there is a learning curve.

The smartest approach? Pick the tool that matches your current stage, skill set, and business goals.

Need help deciding how to build your MVP? Book a free call with Tom