How to Use AI to Build an MVP with No Coding Experience

The information required to build a web-based startup has never been more accessible, and AI is changing the game even further. Founders no longer need to be full-stack engineers to bring their ideas to life. With tools like ChatGPT and GitHub Copilot, AI can fill in knowledge gaps, generate code, write documentation, and even help debug your app. Developers call the process of coding with AI assistance "vibe-coding". Vibe-coding involves explaining what you want in plain language and letting AI write the code for you.

While AI can be a powerful co-founder, it is not a silver bullet. The biggest challenge is knowing what questions to ask. AI is great at filling in the blanks, but you have to know where the blanks are. The real danger lies in the unknown unknowns — the blind spots you do not even realize exist until something breaks. This post aims to help you identify those gaps and use AI effectively as you build your web app minimum viable product (MVP).

Steps to Building a Web App MVP with AI

1. Define your solution
Start with clarity. Describe the problem your startup solves and how your MVP will demonstrate that value. AI can help refine your idea and even brainstorm use cases or customer segments, but you have to know what success looks like.

2. Choose a tech stack
Before asking AI to write the code for your MVP, you must decide which programming language(s) to use, and what supporting technology you will need. AI can suggest frameworks, languages, and databases that fit your goals. Make sure they align with your team’s capabilities and growth plans. Choosing incompatible or antiquated technology from the start makes it harder to change course later on. Keep in mind that all the infrastructure you choose will need to be deployed, and there is cost involved.

3. Write a clear prompt
Your AI assistant is only as good as your instructions. Be specific about what you want, what tools you are using, and what the output should look like. A well-crafted prompt can turn a vague idea into working boilerplate code in minutes.

4. Debug locally
“Running and debugging locally” means testing your app on your own machine before deploying it. Think of it as trying out the app on your computer before it is accessible to anyone else. This lets you catch issues (bugs), experiment freely, and see real-time feedback. AI can help spot syntax errors or logic bugs, but human judgment is still critical here, especially when integrating multiple components.

A common pitfall for non-programmers is not realizing how literal computers are. For example, when asking AI to create a page that lists a user's posts, it may omit a check for the edge case when a user has no posts, or blow up the page length by displaying all posts on one page. Every instruction must be specified. You cannot assume it will know what you want.

5. Choose a host
Once your MVP runs locally, you will need a place to deploy it, called a host. A host is a server that runs your app in a way that allows people to access it over the internet. AI can suggest platforms like Vercel, AWS, or Render based on your stack and goals.

6. Deploy your code
Finally, you will push your code to production, which means putting it somewhere it can be read by the host. Typically, this is through a version control system like GitHub, which facilitates automated deployment pipelines. AI can guide you through setup steps, but the process still requires attention to configuration and security details.

A common pitfall for non-programmers is to leak secrets in the source code. For example, if your app relies on an API call to a large language model (LLM), you likely need to provide an API key. This key should be kept secret, by storing it securely in a place the host server can access.

AI Helps You Build, but Bloomware Helps You Succeed

Building an MVP with AI is absolutely doable for people with no technical background. It is just not easy, and could take a long time, depending on how many questions you need to ask along the way. A technical foundation, architectural foresight, and an understanding of product lifecycles, significantly reduces that time.

At Bloomware, we fill in the technical gap, helping founders go from idea to MVP to scalable product. Whether you need guidance choosing a tech stack, writing code, setting up deployment pipelines, or preparing for general availability, our team ensures your build turns into a real, reliable startup that is ready for growth.

Let us be your AI. Contact us to discuss how we can help.