My Efficient AI-Powered Product Design Workflow Explained in 10 Minutes |

With AI tools advancing so quickly, there's no longer a single, unified process for UI/UX design. In this article, I'll share my experience and present an updated, efficient process to build products from idea to UX and UI with AI. Finally, I'll show you the easiest way to build a working product prototype using AI.

We're going to be building a complex app with a lot of interaction just to show how powerful AI has become. This is my own process where I leverage experience to implement AI at every step without losing the human touch. I don't want to give AI too much liberty with design decisions; instead, I'm using AI to enhance my output without letting it take over.

Step 1: Flesh Out the Idea with AI

The first step is to get AI to ask the right questions to flesh out the core idea and vision. You can use any AI chat platform like Claude, Gemini, or DeepSeek. In this example, I'm using ChatGPT.

To build the perfect prompt, you should follow this structure:

Product Type: Mention if it's a mobile app, web app, or website.
Target Users: Elaborate as much as you want on your audience.
Main Goal: What problem are you solving? What should the user achieve?
User Scenarios: Explain how the product can be used with concrete examples.
Main Features: List the rough features that come to mind.
Desired Outcome: Specify what you want from the AI. In this case, it's to ask clarifying questions and then generate a project brief.

Here’s what my prompt looked like:

I want to create a web app for professionals and lifestyle creatives that allows them to brainstorm and organize projects by saving all relevant info in one board like links, notes, images, and drawing.

The idea is to start a new board whenever I have a new project as the very first phase to brainstorm. This will be useful for professional projects as well as personal ones like decorating a house, buying a car, planning a vacation, or a wedding. The possibilities are endless.

Each board will be for a specific project and allow the user to freely move and resize items.

Ask me any questions that would help narrow down my vision. My desired outcome is a concise project brief that includes all the features for an MVP.

It's very important to get the AI to ask you relevant questions. That way, the project will move forward with exactly what you have in mind, not what the AI assumes is best.

Step 2: Answering Questions and Defining the MVP

The AI will then provide all the necessary questions to complete the project brief. I answered all of them, elaborating as much as possible. The AI organizes these thoughts, so you don't have to be overly careful with your answers. You can even skip questions that don't make sense.

The questions it generated were excellent. It immediately asked me to define my primary persona, which was helpful because the initial idea was broad. I focused on solopreneurs. This exercise is great for challenging and fleshing out an idea without letting the AI take control.

After submitting the answers, I received a concise and organized project brief that clearly explained all the ideas.

Step 3: Naming and Market Validation

With a narrowed-down idea, it's time to come up with a name. Here’s the prompt I used:

Give me some name options for this app that reflect my main value proposition and main features. The name should be simple and unique. Feel free to come up with words from a different language or create new words entirely.

After chatting back and forth to narrow down the options, you can use the AI's web search capabilities to check for domain and social media handle availability. Once a name is chosen, you can move to validation.

At this stage, you can create a survey for market validation and to understand user pain points. This will guide your design decisions.

I want to validate this idea with a small user sample. Create an interactive survey in HTML to collect actionable data to determine the features and to guide the design decisions based on user needs. Also, add a submit button at the end which opens the print menu to save the answers as a PDF document.

This creates an interactive survey that anyone can open, fill out, and save as a PDF to share back. It's a great way to collect actionable feedback. Once you get your answers, you can even feed them back into the AI and ask for a user feedback report.

Step 4: Generating the UI with AI

Now, let's get into the UI. I asked the AI for the exact prompts needed to generate the UI with a tool like UX-Pilot.

I want to generate the UI screens for my app, "MindCraft," in UX-Pilot. Give me the exact prompt to describe the whole app in one paragraph and then a detailed description for each page. Include the UI elements and building blocks from top to bottom. Don't worry about styling for now; I only need the structure.

This prompt gets the AI to generate prompts in a format that works well with UI generation tools. It provided a main app context and a page-by-page breakdown.

In the UI tool, I created a new project and entered my styling preferences separately: dark theme, transparency, bold colors, modern, thin lines, rounded corners. I selected a hi-fi, desktop design and pasted the AI-generated context and screen descriptions.

The results were impressive. It produced a dark-themed login page, a dashboard for viewing boards, and the main board interface with a toolbar and controls. The glassy, transparent look was a nice touch that adhered well to the styling prompts.

This is the time to make changes. Go through the design and note any improvements. For example, I wanted the freehand drawing option to be a toggle in the top bar, not a sidebar item. A simple prompt to the UI tool's editor fixed this:

Remove the freehand drawing from the sidebar and add it as a toggle in the top bar to switch between freehand drawing and panning.

The tool understood perfectly, creating an interactive toggle that even changed the cursor.

Step 5: Building a Functional Prototype

With the UI looking good, it's time to build the app. While there are many great production-ready tools, I found a new tool on Hugging Face called Deepsite, which is excellent for prototyping complex UIs.

The process is simple: 1. In the UI design tool (UX-Pilot), open the code view for a page. 2. Copy the source code. 3. In Deepsite, enter the prompt "Build this:" and paste the code.

Deepsite built the entire layout, making it interactive with floating animations. You could add text nodes, checklists, images, and links. However, implementing the exact interactions for drawing, zooming, and panning was challenging. Small details, like how an item resizes or ensuring drawings move with the canvas during panning, require complex calculations that the AI struggled with.

For more complex interactions, a more robust tool might be necessary. I found that Lovable's agent feature, which analyzes requests and explains its implementation steps, handled these intricate mechanics more accurately right off the bat. For complex products, you get what you pay for.

From Prototype to Product

Now, the front end of the app is a complete, high-fidelity prototype. To make it a fully working product, the next step is the backend. For a complex app like this, where canvas contents, item positions, and drawings must be saved correctly to a database, AI is still not quite there. I'm partnering with a developer to implement the database and backend, trusting a human for this critical part.

The current prototype is already quite versatile. You can add notes, images, lists, links, and drawings, making it handy for planning any project. For example, one board can be used for decorating a room, while another can be for comparing options when buying a car. It demonstrates how useful a freeform board can be for organizing any kind of project.