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  • Writer's pictureAdam Ginsburg

The New Way to Build Your Minimum Viable Product (MVP): Accelerate Your Startup with AI & Nocode

Updated: Jun 13

Leverage AI super powers to build solutions quickly and cost effectively.

A person and a robot interacting with futuristic technology

Goal of this article: Our approach and tools aim to help you build an MVP faster, cheaper, and with less technical expertise.

Caveat: Remember, AI is a co-pilot method. The AI assists and speeds up the process, but won't do everything for you. So get ready, this is going to be game-changing!

Introduction to MVPs

For clarity, we’ll define a MVP as:

A minimum viable product is a version of a product with just enough features to be usable by early customers who can then provide feedback for future product development.[1]

A MVP must be usable, facilitate speedy iteration, and be reliable.


Must see: consider Michael Siebel's must watch advice from YCombinator:

The best advice is to actually launch something quickly and iterate, get a product into the hands of your customers...

So you’re sold: your goal is to build an MVP!!!

The problem: In my experience, as a founder, I've witnessed numerous entrepreneurs develop MVPs only to stagnate after only one iteration, by going beyond what was needed or running out of money,

The solution: Use a killer combo of an agile methodology plus AI plus no-code. It's insanely fast and cost effective. At least try it!

I remember asking one founder of a solution that was built with Buzzy tech, of what he saw were the benefits were and he responded with:

We did it in a fraction of time, with a fraction of the team at a fraction of cost.

The funny thing is that it was before AI; now with AI in the mix, expect that each of those factors will improve dramatically.

Step 0: Choosing a Methodology

Agile combined with a Design Thinking can help provide a structured approach to build your MVP. While Agile is the core project management methodology, Design Thinking focuses on user needs and involves stages like empathy, defining the problem, ideation, prototyping, and testing in a non-linear, collaborative process.

Given you are going to be moving at high speed, ensure you have a good ability to measure each iteration, including customer feedback and features in/out.

Hint; Use simple prioritization methodologies like MosCoW or Eisenhower Matrix to help you cut out the features you don’t need and focus on what’s important on the drive towards Product Market Fit (PMF)

Ok, enough acronyms, let’s get on with it…

Step 1: Ideation and Conceptualization

Your journey begins with a solid idea. Reflect on the problems you aim to solve and the needs of your target audience. What makes your product unique? Utilize AI tools like ChatGPT to brainstorm, refine your idea, and ensure it’s aligned with market demand. This step is about laying the groundwork for your MVP by clearly defining its purpose and scope.

  • Start by identifying the core idea for your MVP. Consider the market need, target audience, and unique value proposition.

  • Use AI tools like ChatGPT for brainstorming and refining your concept, ensuring it’s focused and viable.

Hint: Pick the most basic version of your product or service, build it, test it with users and work out what’s missing. This will be faster and cheaper than building too much and then removing it.

It’s worth noting that massively successful products like AirBnB and Uber had no where near the capabilities like they have today, after they raised millions of dollars and their MVPs were very basic [1]. So keep it simple!

There are some great collaborative white boarding tools like FigJam & Miro for this part of the process. You can always use a Google Doc/Sheet or Microsoft alternative, but please make it collaborative with your team so everyone is on the same page.

Step 2: Rapid Design and Build with Buzzy

With a clear concept in hand, move to Buzzy, an intuitive platform for building and designing your MVP. After setting up your project, you can immediately start shaping your application. Buzzy’s user-friendly interface allows you to create a functional version of your app in minutes from a prompt. This step demonstrates the agility of Buzzy in translating ideas into tangible products, marking a significant departure from traditional, time-consuming development processes.

Disclaimer: The example here is just an idea that popped into my head, it’s not novel and has probably been done a bunch of times and DO NOT USE this application to manage your stock/wealth portfolio or accept its recommendations, it’s using LLMs which are known to get it wrong (hallucinate)… it is just a simple-ish example that I am using for illustrative purposes :-)

So I go to chatGPT, Bard or your favorite Large Language Model (LLM) and ask it:

I want to build a better stock portfolio management startup for users, that leverages GenAI to help users better manage their stock portfolios. Give me some brief variants you think there's an opportunity in the market for. Give me 3 simple ideas. Make the response is short summary format.

ChatGPT’s response:

Certainly! Here are three innovative ideas for a stock portfolio management startup leveraging Generative AI:

1. AI-Personalized Portfolio Advisor: This platform uses AI to analyze individual investor profiles, including risk tolerance, investment goals, and market trends. It then offers personalized stock portfolio recommendations, continuously adapts to changing market conditions, and provides real-time alerts and advice.

2. Automated AI Trading Assistant: This service utilizes advanced AI algorithms to execute trades automatically based on pre-set criteria and real-time market analysis. It offers users the ability to set investment goals, risk levels, and other parameters, and the AI manages their portfolios accordingly, aiming for optimal returns.

3. GenAI Market Sentiment Analysis Tool: This tool harnesses natural language processing and machine learning to analyze market sentiment from various sources like news, social media, and financial reports. It provides investors with insights into how market sentiment is likely to affect stock prices, aiding them in making informed investment decisions.

That’s a great start! Sure you can iterate on these concepts, prompting to your heart's content. For the sake of this article let’s choose the first one and for the sake of MVP at the core it’s a portfolio of stocks then auxiliary information around each stock and the portfolio as a whole.

Put simply, there is a core of the application and then there’s some “cool stuff” that’s been added to it.

So imagine a list of portfolios, which contain stocks and then each stock has some additional information including recommendations generated by AI.

Now is the ideal time to shift from conceptualizing to actualizing your ideas. Visualizing your product helps in identifying its unique features and potential challenges, enhancing your understanding of the MVP's requirements.

Traditionally, transitioning from ideas to design to code, especially without UX/UI and developer expertise, meant hiring a design team and enduring a lengthy process with tools like Figma, then the dreaded Design to Dev Handover. Each of these steps takes effort, time which are multiplied by each iteration/set of changes. It’s not uncommon for this to take weeks and months to achieve a functional MVP.

Enter Buzzy, a game-changer in building web or native applications swiftly. With Buzzy, you can create a scalable web app in minutes, and it also generates a Figma file for any needed high-fidelity design changes. While complexity and specific requirements might extend development time, Buzzy simplifies the process, allowing for rapid progression from idea to a functional MVP. This approach accelerates development, helping you focus on innovation rather than technical details.

Note: Buzzy does not remove the need for good business, design and dev/tech skills, it just allows the team to move faster past the boring stuff and focus on the important stuff. So your human(s)-in-the-loop are essential to helping you create your MVP, they’re just focused on extending the base application to create the current version of the MVP. If you’re outsourcing to freelancers and agencies, you want to ensure that they are utilizing the best tools to maximize speed, quality and cost. As they say, AI will not take your job, but those using AI will.

BTW, Buzzy has a marketplace where you can connect with Buzzy enabled freelancers and agencies to help accelerate your project if you don’t have the time or skill.

For this Stock Portfolio app example, to build the core MVP, there are a number of major components involved:

  1. The core application infrastructure - ie the ability to have users, portfolios and stocks and an interface for getting recommendations

  2. External integrations including

    1. Stock price information, history etc

    2. AI integration for making recommendations, insights etc

Remember, this is going to be iterative so you can start with a simple prompt and “build a house”, starting with solid foundations before you add bells and whistles. I am going to start with the concept prompt from above, with a few additional bits that will help the AI better understand what I am after:

Create an app to track stock Portfolios. Each Portfolio has a number, image and a list of stocks. Each Stock has a name, image, ticket (tickerCode), currentPrice description. Allows users to add a stock to their portfolio. For each stock in the portfolio include a buy price and date and "number of shares".

Hint: Start simple and write your prompt as if you're explaining it to a five-year-old. Be specific to ensure clarity in your explanation. Above you’ll see I am describing some simple functionality and some of the core data elements I want to be captured and their relationships between each other. If you don’t provide these the AI will most probably improvise and increase the chance of hallucinations. Don’t worry, you can always come back and change it later.

It will take a few to several minutes (at the time of writing this - it may be faster/slower depending on new features). Just remember that this is insanely faster than getting a design team, development team and traversing the complexity of handovers between those teams. Used correctly, this can save you loads of time and money.

This is exciting - your ideas are about to come to life!

Here’s a screenshot of the initial app with some sample data, to help us better visualize the concept. You can see we have navigation to Home, Portfolios and Stocks:

A screenshot of the initial app with some sample data, to help us better visualize the concept
This is the list of stocks

Now you can use the AI chat to change the application to better meet your requirements. Using the chat or just starting from scratch with a better prompt are all just easy ways to tweak and refine your MVP with minimal effort and technical skill.

Each Portfolio has many stocks - here's an example of Stock page:

A screenshot of the an individual stock page

Optional Step: Add in Security. It’s easy to secure your application here are couple of tutorials that will help you

Step 3: Enhancing Design with Figma (Optional)

Buzzy generates best practices designs, based on a Figma toolkit. The Buzzy Figma toolkit defines reusable building blocks to construct the screens and components needed to build the application. This makes it easy to modify via Figma's own components, styles and variables - change things in one spot, the entire design can be instantly updated.

Note that the latest Buzzy UI kit uses Figma’s new Variables, which allows even more flexibility - for instance, instantly switching between Light and Dark modes, or generating your own new theme.

Note: You can also start in Figma with your own app design or brand-specified design system and avoid AI and Buzzy’s toolkit altogether. However we find that with Figma’s component-based model, it’s easier and faster to start with what Buzzy generates using AI (or one from one of Buzzy's other existing templates).

You can instantly update your web and native applications with a click of a button via the Buzzy Figma Plugin - so going from Figma to your app is NOT a one off, it’s iterative.


  • Export your Buzzy-generated app to Figma for high-fidelity design modifications, if necessary.

  • Utilize Figma's advanced design tools to refine the user interface and experience.

  • Benefit from the seamless integration between Buzzy and Figma, allowing for instant design updates and keeping your application’s look and feel modern and user-friendly.

Step 4: Iteration and Refinement

An MVP is never static. Use Buzzy’s AI integration and Figma to apply changes effortlessly. This phase is about iterating based on user feedback and emerging insights. Buzzy’s adaptability plays a crucial role here, allowing you to modify and enhance your MVP swiftly, ensuring it continually evolves to meet user expectations and market needs.

This is where Buzzy comes into its own, and it's an incredible game changer as you use AI or Figma to easily modify the design.

For the purposes of this article, we’ll leave the design as-is, however have a look at this recent Webinar were we dive into the new design capabilities with Buzzy and Figma - watch the recap here.


  • Use Buzzy’s AI capabilities and Figma integration to implement updates effortlessly.

  • Embrace the iterative nature of MVP development, making continuous improvements based on user feedback and new insights.

  • Use Buzzy for swift modifications, ensuring your MVP evolves effectively in response to real user needs.

Step 5: Integrating AI and External Data Sources

In our example Share Portfolio app, we have the basics of the system designed and working (developed). Now comes the fun stuff:

Getting the stock history

For this functionality, it’s going to be fairly simple, the steps/process will look something like:

  • Get the stock ticker code

  • Call and external stock API to get the data for the specific (variable) stock ticker

  • Represent this as a chart

It’s worth saying that you can actually do this in two ways:

  1. Client side - use a Buzzy Code Widget using an AI Copilot

  2. Server side - write a server side component - eg an AWS Lambda Function, DO Function or similar to periodically fetch the latest data from an external API

  3. Hybrid - mix of client/server side code.

For the scenario here we’ll use option 1, but for a production system option 2 via "Server side" may be a better option.

Watch the video below for a recap of building the application, from the initial prompt and then adding a custom code widget to add the stock history chart. Here's the second prompt we used to add the custom code widget:

I want to add a Code Widget, called stockPriceHistory, to the stock table representing the price history for the stock that uses the following API to fetch the stock prices for the last 12 months: Where "STOCK_SYMBOL" is the ticker code/stock symbol in the current row. In the widget, render a chart showing the data from the API in a line chart. Only show the history for the stock for the last 12 months

Note in this example, we used to get the stock price history, you could replace this with some alternative API, as needed.

Integrating with an AI LLM to get insights & recommendations

Once we have the stock information we can include that in a call to a LLM to get insights and recommendations at both a portfolio level and single stock level. This will follow the same pattern as calling the stock history API above, except we’re call the LLM and dynamically constructing a prompt including the stock ticker, history, portfolio, purchase date and other other parameters that would be useful for returning a better quality result. For example:

Certainly! Here's a sample prompt you could use to ask a large language model (LLM) for a recommendation and insight regarding your stock portfolio, taking into account the current economic market conditions:

"Hello, I have a diversified stock portfolio consisting of <iterate through the stocks in the portfolio including ticker code, quantity , price purchased> .

Given the current economic market conditions, which include [specific details such as interest rate trends, inflation rates, geopolitical situations, etc.], I am seeking insights and recommendations on potential adjustments to my portfolio.

Could you analyze the potential risks associated with my current portfolio composition in the context of the current economic climate?

Based on the latest market trends and economic forecasts, what adjustments would you recommend to optimize my portfolio for both risk management and growth potential?

Are there specific sectors or types of stocks that you would suggest focusing on or avoiding under these conditions?

How can I align my investment strategy with the predicted economic shifts over the next quarter or year?

Please provide any additional insights or considerations that I should be aware of to make informed investment decisions during this period."

Disclaimer: DO NOT USE THIS PROMPT - it's just an example and the LLM should not be relied upon.

When we get the result back use the Buzzy API to put the data into a field in a data table for rendering. Note with Buzzy's mobile applications you can have offline data, so by placing the data into the Buzzy Datatable, this offline capability is handled out of the box.

Again a disclaimer: this is just an illustrative example, don’t use this to make decisions as the LLM may be unreliable ;-)

To keep the article simple, we won't go into the details here, but essentially it's a call to the LLM's (eg OpenAI, Google, LLAMA...) API and getting the result back. You definitely want to do this server-side so as not to expose your LLM API keys via the browser, so for the sake of simplicity we'll exclude that code from this article. That said, it will follow the same pattern: grab some data from Buzzy, call external LLM, get the result and insert back into Buzzy with the Buzzy APIs.


  • Integrate AI services and external APIs to enhance your MVP with additional features like data analytics or user management.

  • Explore the range of functionalities Buzzy supports to add depth and complexity to your MVP as needed.

Step 6: Testing with Real Users

This is where things get real. Remember: all feedback is good feedback, check your ego at the door.

One really useful tool we found with Buzzy was external user testing - tools like have massive cohorts of test users that you can instantly tap into. You will learn heaps from these people and ensure you don't have any embarrassing glaring holes before you start to test with your own cohorts.

Some tips:

  1. keep the tests as simple as possible - keeping each tests objectives simple , don’t try and do too much in one test

  2. Use the qualification/prerequisite screening to find the right testers. Screening criteria include age, location, skill set or some custom prerequisites.

  3. Don’t be over prescriptive - you want to find the gaps in your product, which may not be where you think they are… so give enough leeway to the testers to find the real problems.

Step 7: Continuous Improvement and Scaling

An MVP is never static. Use Buzzy’s AI integration and Figma to apply changes effortlessly. This phase is about iterating based on user feedback and emerging insights. Buzzy’s adaptability plays a crucial role here, allowing you to modify and enhance your MVP swiftly, ensuring it continually evolves to meet user expectations and market needs.

  • Continuously refine your MVP, incorporating user feedback and adapting to market trends.

  • Utilize Buzzy’s flexibility to scale your application, preparing for more extensive development or a full-scale product launch.


Wowza!!! Imagine trying to do this 12+ months ago (from time of publication of this article - before the new wave of AI LLMs)? It would be been a mammoth (near impossible) task, and cost prohibitive.

Today you can get your MVP going faster than you could before.

In summary:

  • Highlight the rapid development and flexibility that Buzzy offers in the context of MVP creation.

  • Reinforce the concept of building and iterating an MVP quickly as essential for modern startups.

  • Motivate readers to embrace these innovative tools to expedite their journey from idea to market-ready product.

Parting Thought: Consider this – Buzzy's AI service is available for around $100 per month. In comparison, hiring a UX Designer and a Full Stack Developer typically costs about $50 per hour for each (probably more), amounting to $100 per hour. If using Buzzy saves you even just one hour, it's already a cost-effective choice. We believe the potential time savings could be much greater.


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