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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Master UI Component Creation with AI: The Ultimate Guide for Developers

Gracjan Prusik

24 Mar 2025
Master UI Component Creation with AI: The Ultimate Guide for Developers

Introduction

Modern frontend development is evolving rapidly, and creating UI components with AI tools is helping developers save time while enhancing interface quality. With AI, we can not only speed up the creation of UI components but also improve their quality, optimize styles, and ensure better accessibility.

This article explores how creating UI components with AI is transforming frontend development by saving time and improving workflows. Specifically, we will discuss:

  • Generating components from images,
  • AI for style analysis and optimization,
  • Automatic style conversion and code migration,
  • AI in generating UI animations.

Creating UI Components with AI from Images

One of the interesting applications of AI in frontend development is the ability to generate components from an image. AI can recognize the structure of the interface and generate HTML/CSS or JSX code that matches the provided image. One of the most popular tools for UI creation is Lovable.

For testing, let's see how the tool performs in creating a simple contact form from the page you are currently on, which is Nextrope.

Query:

"Recreate the image I've sent you in Next.js using CSS."

Sample image used in the query:

The result received:

Tworzenie komponentów UI - Wygenerowany widok

Lovable did an excellent job transforming the image into code. The view is fully responsive. It’s important to remember that the more precise the request, the better the AI will replicate the expected view. However, even with a simple command, the tool performed surprisingly well.

Of course, AI has its limitations. It still makes quite a few mistakes. The generated code still requires review and fixes from the developer, but in some cases, the entire process is significantly sped up—correcting the code often takes less time than creating the component from scratch.

Optimizing UI Components with AI Tools for Style Improvements

This problem of inaccurate code reproduction by AI can be partially addressed by using it to analyze and improve styles. Tools like ChatGPT, DeepSeek and Claude are capable of not only generating code but also diagnosing CSS errors and suggesting why a particular style might not be working as expected.

Simple example: Why is the div not centered?

Query: "Why is this div not centered?"

AI analyzes the code and provides the following response:

Problem: The parent container does not have a defined width or display: flex.
Solution: Add the appropriate styles to the parent container.

.parent {
  display: flex;
  justify-content: center;
  align-items: center;
  width: 100vw;
  height: 100vh;
}

AI for Automatic Style Conversion and Code Migration in UI Components

AI can assist with style conversion between different technologies, such as transferring code from traditional CSS to Styled Components or Tailwind CSS.

Let's assume we have a style written in traditional CSS:

.button {
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;
}

.button:hover {
  background-color: darkblue;
}

We can use AI for automatic conversion to Styled Components:

import styled from "styled-components";

const Button = styled.button`
  background-color: blue;
  color: white;
  padding: 10px 20px;
  border-radius: 5px;
  transition: background-color 0.3s ease;

  &:hover {
    background-color: darkblue;
  }
`;

export default Button;

AI can also assist in migrating code between frameworks, such as from React to Vue or from CSS to Tailwind.

This makes style migration easier and faster.

How AI Enhances UI Animation Creation

Animations are crucial for enhancing user experience in interfaces, but they are not always provided in the project specification. In such cases, developers have to come up with how the animations should look, which can be time-consuming and require significant creativity. AI, in this context, becomes helpful because it can automatically generate CSS animations or animations using libraries like Framer Motion, saving both time and effort.

Example: Automatically Generated Button Animation

Suppose we need to add a subtle scaling animation to a button but don't have a ready-made animation design. Instead of creating it from scratch, AI can generate the code that meets our needs.

Code generated by AI:

import { motion } from "framer-motion";

const AnimatedButton = () => (
  <motion.button
    whileHover={{ scale: 1.1 }}
    whileTap={{ scale: 0.9 }}
    className="bg-blue-500 text-white px-4 py-2 rounded-lg"
  >
    Press me
  </motion.button>
);

In this way, AI accelerates the animation creation process, providing developers with a simple and quick option to achieve the desired effect without the need to manually design animations from scratch.

Summary

AI significantly accelerates the creation of UI components. We can generate ready-made components from images, optimize styles, transform code between technologies, and create animations in just a few seconds. Tools like ChatGPT, DeepSeek, Claude and Lovable are a huge help for frontend developers, enabling faster and more efficient work.

In the next part of the series, we will take a look at:

If you want to learn more about how AI is impacting the entire automation of frontend processes and changing the role of developers, check out our blog article: AI in Frontend Automation – How It's Changing the Developer's Job?

Follow us to stay updated!

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