How to create NFT games? – A practical guide

Maciej Zieliński

17 May 2022
How to create NFT games? – A practical guide

NFT games are entertainment products that are based on blockchain technology and tokens. More and more entities use NFT to monetize their ventures in the gaming industry. This allows players to create, sell, or buy tokens of any game-related object while providing financial support to the game's developer. How does it work in practice? How to create an NFT game? We're writing about it below!

Who profits from NFT games?

With NFT, creators can tokenize and sell skins, artifacts, armor, weapons, etc. in a given form. NFT can be used not only by developers, but also by players. For example, they have the ability to sell NFT in-game to other collectors and players, thus earning money and cryptocurrency.

How to start making an NFT game?

In order to design and utilize NFT in-game, developers create smart contacts that automate the use of tokens. An example of this is the most popular blockchain game – CryptoKitties, where several smart contracts create a structure for the entire game! As for smart contracts, a good example is GeneScience, which defines a random mechanic in order to generate new cats. In addition to smart contracts, there are other things to consider when creating an NFT game.

NFT GAMES

NFT game model

There are currently two most popular forms of NFT games:

  1. P2E (play to earn) - gameplay will only start when you purchase the NFT token. This does not change the fact that in the future there will be an opportunity to treat the game as a potential investment.
  2. F2P (free to play) - it's a unique form of entertainment that cuts down on initial costs. You can play it immediately, free of charge. When you create a game in this respect, you may find that potential revenue is lower than P2E. Such games do not have NFT in useable form. Older players teach younger players in order to participate in later profits.

NFT game genre

Select the genre of game that will be targeted at potential users. Keep in mind that an NFT game is very similar to a classic game. The difference will only be the monetization of your product. A number of genres are therefore available for selection:

  • adventure games,
  • RPG’s,
  • story driven games,
  • card games,
  • strategy games,
  • war games and many more.

After choosing a genre, analyze the competition. It may be worthwhile to check out similar games using blockchain technology. Don't copy games that have not been successful. Some choose a solution that takes advantage of the best and most interesting features from the competition’s projects. All information regarding the game should be written down and recorded in the game's design document. This will help you avoid the issue of your team not understanding your vision of the project. Designing proper and transparent stages of game development, including levels, conditions of promotion and monetization, will help to avoid misunderstandings. When you achieve this, move on to designing the visuals.

Application availability

Applications built on blockchain technology have their own dApps name, meaning they are decentralized. This is important because the main code and data of the decentralized application are stored in a peer-to-peer blockchain. This is the opposite of a client-server application where information resides on servers that are easy to hack. Emphasis should be placed on decentralization, as every cryptocurrency is decentralized. In addition, decentralized applications are open source.

Mobile app vs Web browser

Another element to consider is how your customers will use the game. Reactions can be based on a web browser or a mobile application. Both forms are attractive for NFT implementation. The web application is widespread and can be started from almost any device. The mobile app will certainly work better on smartphones and offers many unique features.

Mobile applications – division

Mobile applications can be divided into native and cross-platform forms.

  1. Native form – applications are created for a specific operating system and provide access to a variety of smartphone features: camera, contact list, GPS, and more.
  2. Cross-platform form – Cross-platform options will not have access to smartphone features, but they are much easier, faster, and less expensive to create. This is because you need only one solution that will work on all operating systems.

Whichever feature you choose, consider whether your game can be used on a smartphone. Moreover, AppStore has a number of requirements and restrictions for gaming apps. There is also the hybrid application, which is both a mobile and web application.

Selection of technologies for NFT games

Encorporating NFT into video games is best done using open source. One of the most popular ecosystems for making games with NFT is the dApp "Truffle Suite". It is the best place to develop smart contracts. Truffle Suite is used by entities such as Microsoft, Amazon or VMWare. This solution provides blockchain developers with a standard and schematic environment to test potential smart contracts in gaming. As for the best blockchain to build an NFT game on – that would be Ethereum. It's the most popular platform for creating and running NFT – also in gaming, where it enjoys the greatest popularity.

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Truffle Suite is comprised of three different elements:

  • Truffle – is an environment for developers who use Ethereum as a basis for creating NFT and implementing and using smart contracts.
  • Ganache – is a tool that allows you to configure the local Ethereum blockchain. This ensures that decentralized applications can be deployed, developed and tested in a secure location.
  • Drizzle – is a set of front-end libraries designed to develop and create a transparent interface.

Front-end

This element can be created using Javascript. You will need the right Framework, which will guarantee a set of specific software solutions. This will give us the design, logic and basic functions of the game. In addition, some tasks allow the creator of an NFT game to add their own code to a package created in a Framework. The Front-end can be hosted on Netlify, one of the best platforms for web creation. It's a great solution for small groups making NFT games that don't have the ability to build an infrastructure for their plans by themselves.

Wallet and payments

Let us remember that ordinary money is handled differently than cryptocurrencies. A cryptocurrency is stored in a virtual wallet based on blockchain technology. The crypto portfolio is a space that allows you to store your crypto or NFT without third party intervention. Let us remember that when creating NFT games, we need to guarantee a high level of security for wallets. The best way to choose the appropriate method of storing capital is to go to the web page of the cryptocurrency that interests us, and then check the recommended wallets for storing it.

Each wallet must meet the following requirements:

  • needs to have private and public keys;
  • needs to have several levels of security.

If these conditions are met cumulatively, then everything is done properly.

Smart contracts

Thanks to blockchain technology smart contracts, we have access to programs that run based on fulfilling certain contract terms. Users who want to access the NFT as part of a computer game must follow this procedure:

  1. The Frontend receives the user address from the crypto portfolio.
  2. The Frontend sends the user address to the smart contract.
  3. The smart contract provides the user with a NFT address.

The creation of smart contracts begins by checking the official Ethereum blockchain library, Web3. This allows us to abstract from the internal mechanics of Ethereum and work with networks and intelligent contracts as if they were normal JavaScript objects.

Testing an NFT game

To test an NFT game, it's a good idea to use a particular blockchain for that purpose. For example, Rinkeby. There are several ways to test NFT games, which are as follows:

  • Functionality testing – this is a test to check the overall performance of the game, data transfer, block size etc.
  • Security testing – this is a mandatory test that helps us determine if the blockchain system is in danger of being hacked.
  • Interface testing – when creating an NFT game, keep in mind that you need to make sure that the workflow and functionality work properly.
  • Integration testing – this is the bridge between different programming components.
  • API testing – This checks the software components' communication with the external API, so we can be sure that requests and responses are processed automatically in the proper way.

Summary

Seeing the above requirements you should be aware that creating an NFT game requires a lot of knowledge and dedication. You can create it in various forms. Make sure not to make the gameplay entirely based on monetization. In addition, consider whether the NFT are attractive enough (and the game itself as well) to incentivize players to invest in NFT for the so-called “skins” or other elements of a virtual character. Whether you choose a browser, mobile or hybrid model, it's important to keep in mind that NFT can generate high revenue, but it can also leave a negative impression on players if it is purely finance-focused.

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AI in Real Estate: How Does It Support the Housing Market?

Miłosz Mach

18 Mar 2025
AI in Real Estate: How Does It Support the Housing Market?

The digital transformation is reshaping numerous sectors of the economy, and real estate is no exception. By 2025, AI will no longer be a mere gadget but a powerful tool that facilitates customer interactions, streamlines decision-making processes, and optimizes sales operations. Simultaneously, blockchain technology ensures security, transparency, and scalability in transactions. With this article, we launch a series of publications exploring AI in business, focusing today on the application of artificial intelligence within the real estate industry.

AI vs. Tradition: Key Implementations of AI in Real Estate

Designing, selling, and managing properties—traditional methods are increasingly giving way to data-driven decision-making.

Breakthroughs in Customer Service

AI-powered chatbots and virtual assistants are revolutionizing how companies interact with their customers. These tools handle hundreds of inquiries simultaneously, personalize offers, and guide clients through the purchasing process. Implementing AI agents can lead to higher-quality leads for developers and automate responses to most standard customer queries. However, technical challenges in deploying such systems include:

  • Integration with existing real estate databases: Chatbots must have access to up-to-date listings, prices, and availability.
  • Personalization of communication: Systems must adapt their interactions to individual customer needs.
  • Management of industry-specific knowledge: Chatbots require specialized expertise about local real estate markets.

Advanced Data Analysis

Cognitive AI systems utilize deep learning to analyze complex relationships within the real estate market, such as macroeconomic trends, local zoning plans, and user behavior on social media platforms. Deploying such solutions necessitates:

  • Collecting high-quality historical data.
  • Building infrastructure for real-time data processing.
  • Developing appropriate machine learning models.
  • Continuously monitoring and updating models based on new data.

Intelligent Design

Generative artificial intelligence is revolutionizing architectural design. These advanced algorithms can produce dozens of building design variants that account for site constraints, legal requirements, energy efficiency considerations, and aesthetic preferences.

Optimizing Building Energy Efficiency

Smart building management systems (BMS) leverage AI to optimize energy consumption while maintaining resident comfort. Reinforcement learning algorithms analyze data from temperature, humidity, and air quality sensors to adjust heating, cooling, and ventilation parameters effectively.

Integration of AI with Blockchain in Real Estate

The convergence of AI with blockchain technology opens up new possibilities for the real estate sector. Blockchain is a distributed database where information is stored in immutable "blocks." It ensures transaction security and data transparency while AI analyzes these data points to derive actionable insights. In practice, this means that ownership histories, all transactions, and property modifications are recorded in an unalterable format, with AI aiding in interpreting these records and informing decision-making processes.

AI has the potential to bring significant value to the real estate sector—estimated between $110 billion and $180 billion by experts at McKinsey & Company.

Key development directions over the coming years include:

  • Autonomous negotiation systems: AI agents equipped with game theory strategies capable of conducting complex negotiations.
  • AI in urban planning: Algorithms designed to plan city development and optimize spatial allocation.
  • Property tokenization: Leveraging blockchain technology to divide properties into digital tokens that enable fractional investment opportunities.

Conclusion

For companies today, the question is no longer "if" but "how" to implement AI to maximize benefits and enhance competitiveness. A strategic approach begins with identifying specific business challenges followed by selecting appropriate technologies.

What values could AI potentially bring to your organization?
  • Reduction of operational costs through automation
  • Enhanced customer experience and shorter transaction times
  • Increased accuracy in forecasts and valuations, minimizing business risks
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Want to implement AI in your real estate business?

Nextrope specializes in implementing AI and blockchain solutions tailored to specific business needs. Our expertise allows us to:

  • Create intelligent chatbots that serve customers 24/7
  • Implement analytical systems for property valuation
  • Build secure blockchain solutions for real estate transactions
Schedule a free consultation

Or check out other articles from the "AI in Business" series

AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

Gracjan Prusik

11 Mar 2025
AI-Driven Frontend Automation: Elevating Developer Productivity to New Heights

AI Revolution in the Frontend Developer's Workshop

In today's world, programming without AI support means giving up a powerful tool that radically increases a developer's productivity and efficiency. For the modern developer, AI in frontend automation is not just a curiosity, but a key tool that enhances productivity. From automatically generating components, to refactoring, and testing – AI tools are fundamentally changing our daily work, allowing us to focus on the creative aspects of programming instead of the tedious task of writing repetitive code. In this article, I will show how these tools are most commonly used to work faster, smarter, and with greater satisfaction.

This post kicks off a series dedicated to the use of AI in frontend automation, where we will analyze and discuss specific tools, techniques, and practical use cases of AI that help developers in their everyday tasks.

AI in Frontend Automation – How It Helps with Code Refactoring

One of the most common uses of AI is improving code quality and finding errors. These tools can analyze code and suggest optimizations. As a result, we will be able to write code much faster and significantly reduce the risk of human error.

How AI Saves Us from Frustrating Bugs

Imagine this situation: you spend hours debugging an application, not understanding why data isn't being fetched. Everything seems correct, the syntax is fine, yet something isn't working. Often, the problem lies in small details that are hard to catch when reviewing the code.

Let’s take a look at an example:

function fetchData() {
    fetch("htts://jsonplaceholder.typicode.com/posts")
      .then((response) => response.json())
      .then((data) => console.log(data))
      .catch((error) => console.error(error));
}

At first glance, the code looks correct. However, upon running it, no data is retrieved. Why? There’s a typo in the URL – "htts" instead of "https." This is a classic example of an error that could cost a developer hours of frustrating debugging.

When we ask AI to refactor this code, not only will we receive a more readable version using newer patterns (async/await), but also – and most importantly – AI will automatically detect and fix the typo in the URL:

async function fetchPosts() {
    try {
      const response = await fetch(
        "https://jsonplaceholder.typicode.com/posts"
      );
      const data = await response.json();
      console.log(data);
    } catch (error) {
      console.error(error);
    }
}

How AI in Frontend Automation Speeds Up UI Creation

One of the most obvious applications of AI in frontend development is generating UI components. Tools like GitHub Copilot, ChatGPT, or Claude can generate component code based on a short description or an image provided to them.

With these tools, we can create complex user interfaces in just a few seconds. Generating a complete, functional UI component often takes less than a minute. Furthermore, the generated code is typically error-free, includes appropriate animations, and is fully responsive, adapting to different screen sizes. It is important to describe exactly what we expect.

Here’s a view generated by Claude after entering the request: “Based on the loaded data, display posts. The page should be responsive. The main colors are: #CCFF89, #151515, and #E4E4E4.”

Generated posts view

AI in Code Analysis and Understanding

AI can analyze existing code and help understand it, which is particularly useful in large, complex projects or code written by someone else.

Example: Generating a summary of a function's behavior

Let’s assume we have a function for processing user data, the workings of which we don’t understand at first glance. AI can analyze the code and generate a readable explanation:

function processUserData(users) {
  return users
    .filter(user => user.isActive) // Checks the `isActive` value for each user and keeps only the objects where `isActive` is true
    .map(user => ({ 
      id: user.id, // Retrieves the `id` value from each user object
      name: `${user.firstName} ${user.lastName}`, // Creates a new string by combining `firstName` and `lastName`
      email: user.email.toLowerCase(), // Converts the email address to lowercase
    }));
}

In this case, AI not only summarizes the code's functionality but also breaks down individual operations into easier-to-understand segments.

AI in Frontend Automation – Translations and Error Detection

Every frontend developer knows that programming isn’t just about creatively building interfaces—it also involves many repetitive, tedious tasks. One of these is implementing translations for multilingual applications (i18n). Adding translations for each key in JSON files and then verifying them can be time-consuming and error-prone.

However, AI can significantly speed up this process. Using ChatGPT, DeepSeek, or Claude allows for automatic generation of translations for the user interface, as well as detecting linguistic and stylistic errors.

Example:

We have a translation file in JSON format:

{
  "welcome_message": "Welcome to our application!",
  "logout_button": "Log out",
  "error_message": "Something went wrong. Please try again later."
}

AI can automatically generate its Polish version:

{
  "welcome_message": "Witaj w naszej aplikacji!",
  "logout_button": "Wyloguj się",
  "error_message": "Coś poszło nie tak. Spróbuj ponownie później."
}

Moreover, AI can detect spelling errors or inconsistencies in translations. For example, if one part of the application uses "Log out" and another says "Exit," AI can suggest unifying the terminology.

This type of automation not only saves time but also minimizes the risk of human errors. And this is just one example – AI also assists in generating documentation, writing tests, and optimizing performance, which we will discuss in upcoming articles.

Summary

Artificial intelligence is transforming the way frontend developers work daily. From generating components and refactoring code to detecting errors, automating testing, and documentation—AI significantly accelerates and streamlines the development process. Without these tools, we would lose a lot of valuable time, which we certainly want to avoid.

In the next parts of this series, we will cover topics such as:

Stay tuned to keep up with the latest insights!