How do you choose blockchain technology for your NFT game?

Maciej Zieliński

10 Jun 2022
How do you choose blockchain technology for your NFT game?
  • Is the right technology for your NFT game everything?
  • Blockchain technology for your NFT game - choosing the tools 
  • Choose a forward-thinking technology 
  • Focus on smart contracts 
  • The best blockchains for NFT game development
  • Summary

NFT games are gaining popularity among fans of this type of entertainment, as well as people who are interested in the cryptocurrency and blockchain sector. The creation of the game itself should be based on several factors that will affect its potential success. What to pay special attention to? We write about it in our latest guide! 

Is the right blockchain technology for an NFT game everything?

Nowadays, more and more games based on various blockchain solutions, as well as related to smart contracts, are being developed. Nevertheless, behind this kind of entertainment, some developers know that there is a whole team of right people behind the success of the project. How to choose blockchain technology for your NFT game? This is just one of the questions you need to know the answer to. First of all, create a team of people who are familiar with the following technologies:

  • DApp
  • JavaScript. 
  • HTML 
  • CSS
  • Angular 
  • React.js.

People who have expertise in these industries are programmers, UI designers, graphic designers, and program testers. For this, it's best to choose a company that has professionals in the aforementioned fields, as picking random freelancers will likely make your project chaotic. Moreover, hiring Freelancers makes the responsibility for their actions rest on your shoulders. Choosing a company that specializes in blockchain technology is the best practice, as the corporation in question has structures and employees who will take care of the project and constantly monitor its development. 

Blockchain technology for NFT game - choice of tools 

The most popular blockchain for creating NFT games is Ethereum. Although there are also other solutions on the market that allow you to create an NFT game professionally (more on that later), here are some additional aids that will make the project done with due diligence: 

  • MetaMask - is a type of Ethereum wallet. What should be noted, it can be treated as a browser extension. Many entities running on Ethereum use MetaMask to store Ethers. Moreover, it is used to implement and execute smart contracts. Additionally, MetaMask is a place of communication between developers and the blockchain. MetaMask is considered a secure and standards-based system: 
  1. -ERC-20 
  2. -ERC-721.

  • Ganache - Ganache is a popular program for testing the created application. It is a component provided with Truffle Suite tools.
  • Web3.js - This is one of the more popular JavaScript APIs of Ethereum. It is also a collection of important databases and libraries. It allows developers to interfere with remote or local Ethereum nodes. 
  • Truffle- is a toolkit that has a wide range of applications. It allows you to create and implement smart contracts, which are the basis of a good NFT game. 
  • Remix: Remix is a popular DApp solution that is used to code Solidity smart contracts for Ethereum. 
  • Ropsten Test Network - This is where you will test the smart contracts you have created. 

Choose a technology by thinking ahead 

When looking for the best blockchain technology for your NFT, you need to consider several parameters. Here are the elements you need to evaluate prospectively:  

  • Fork - Remember that it is the uniqueness and rarity of NFTs that makes them so valuable. A hard fork would pose a serious threat to these aspects as the sanctity of NFTs would be questioned in such a case. It is important to note that NFTs in the "old" blockchain could eventually devalue completely. Therefore, it is important to create NFTs on blockchains that are fork-proof. 
  • Smart contracts - The robustness of smart contracts is a key factor when it comes to the overall security of blockchain technology. Therefore, writing bug-free, clean and secure code is crucial. We mentioned the above applications that can analyze them. This is important because smart contracts need to undergo rigorous and complex testing to know that the user is experiencing the highest level of NFT play, performance, and resistance to potential bugs or attacks. 
  • Token Development Costs and Transaction Costs - In addition to the issues we have discussed so far, there is one more issue to consider - cost-effectiveness. When doing NFT-based transactions, you need cost-effective solutions because they don't always involve multi-million dollar transactions. Gaming consists of small items, characters, skins, equipment, etc. Make it safe and profitable to trade them. Microtransactions are king in this case when it comes to settlement. 
  • Security - This is probably the most important factor you need to consider when creating an NFT game. Blockchains are vulnerable to many types of attacks such as man-in-the-middle. How to solve this problem? Note that platforms running with a proof-of-work consensus mechanism are generally more vulnerable to attacks where attackers can control a large portion of the network's computing power. The result of such an action is loss of account access, data, and money. It is worth implementing alternative consensus mechanisms such as proof-of-stake.
  • Speed of transactions - this is the factor behind the success of a well-built NFT game. The transfer of payments between entities should be immediate, transparent, and, above all, secure. 

Focus on smart contracts 

It is worth developing smart contracts for the right front-end functions and cryptocurrency tokens. To code them, follow these steps:

  • Review smart contracts from gaming projects that inspire you. 
  • Use the Remix IDE to code them.
  • Keep it simple. This will make it easier for you to debug them. 
  • Sort smart contracts with tools from Truffle. 

Remember that once you implement smart contracts, you won't be able to make modifications to them. This means that you need to test them well and conduct a robust audit. This is not a simple task, as you need to perform the following steps, among others: 

  • Locking down the source code;
  • Understanding the project and studying the project documentation;
  • Initial code review;
  • Static code analysis;
  • Code quality analysis;
  • Detection of common vulnerabilities;
  • Functionality analysis and many more. 

So, invest in a company that has experts who can analyze the above information as it will save you time and money. 

Best blockchains for NFT game development

When we have seen several different elements to consider when looking for the best blockchain for NFT game development must move on to specific solutions.

Below are the most popular blockchains that will help you succeed in gaming: 

  • FLOW - This is a developer-friendly blockchain, especially when it comes to creating marketplaces and digital assets. The platform strives for scalability with updated smart contracts written in the Cadence programming language. It is worth noting that Flow supports a multi-node architecture for collection, verification, enforcement, and consensus, which greatly streamlines the entire NFT development process. 
  • Ethereum - is currently one of the most popular technologies used in the NFT gaming industry. Many leading NFT marketplaces are using the Ethereum network, including Decentraland, SuperRare, OpenSea, and Rarible. This solution is extremely popular because it is simple and transparent. Basically - you just upload a file and fill in some details.
  • Tezos - The last option to consider is Tezos, which is a blockchain with an NFT marketplace called TRUESA. TRUESA's main goal is to reduce its carbon footprint. According to official information, the platform consumes 2,000,000 times less energy compared to other NFT systems because it optimizes CPU usage. If you are eco, then you can count on Tezos as an important partner in your activities and green approach to NFT development.

Summary

Gaming and cryptocurrencies is an industry that complements each other. Blockchain technology itself is still characterized by a kind of freshness and ongoing discovery. It provides functionality, transparency, and security. However, it is hard to find companies and developers who have years of experience in it. When creating an NFT game, analyze not only your idea in terms of storyline, playability, and graphics but mainly the technology and the team that will help implement and test it. No game, regardless of the storyline, will be able to succeed if it is flawed or fails to provide capital security and account access to its users. This is why it is so important to create it perfectly from start to finish. 

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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!