A Comprehensive Guide to ERC-4337: Understanding Account Abstraction in Ethereum

Paulina Lewandowska

28 Mar 2023
A Comprehensive Guide to ERC-4337: Understanding Account Abstraction in Ethereum

If you're involved in the world of blockchain and cryptocurrencies, you've probably heard of Ethereum, one of the most popular platforms for developing decentralized applications. Ethereum has been around for a few years now, and while it has been successful in many ways, there are still some limitations to the way it currently operates. That's where ERC-4337 comes in – a proposed Ethereum Improvement Proposal (EIP) that aims to introduce a new feature called "account abstraction" to the Ethereum blockchain. In this article, we'll take a closer look at what ERC-4337 is, how it works, and what it means for users.

Definition of ERC-4337

ERC-4337 is a proposed EIP that aims to introduce account abstraction to the Ethereum blockchain. This would allow smart contracts to directly receive and send funds without the need for an intermediary account.

Overview of Ethereum and its limitations

Before we dive into account abstraction, let's first understand Ethereum and its limitations:

  • Ethereum is a blockchain platform that enables developers to build and deploy decentralized applications, or dApps, on top of it.
  • Ethereum uses a native cryptocurrency called Ether (ETH) to incentivize miners to process transactions and secure the network.
  • Ethereum has some limitations, such as scalability, privacy, and security, that need to be addressed to make it more usable and accessible.

What is Account Abstraction?

Under the current account-based model used in Ethereum, smart contracts cannot directly receive or send funds. Instead, they rely on an intermediary account to execute transactions. Account abstraction, on the other hand, allows smart contracts to have their own unique address, enabling them to directly receive and send funds without an intermediary account. This would enable more complex smart contract interactions and make Ethereum more flexible.

What does ERC-4337 actually mean to you?

If you're looking for a more streamlined and user-friendly experience when it comes to interacting with decentralized apps (dApps) on the Ethereum network, then ERC-4337 might be just what you need. This new standard for contract accounts introduces several benefits that could make your life as a crypto user easier and more efficient.

  • Simplifying Wallet Access: You'll appreciate the simplification of wallet access and logins. With ERC-4337, you won't need to deal with cumbersome private keys or seed phrases when logging in to your wallet. Instead, you can use your Ethereum address as your login ID, making the process much more user-friendly.
  • Recovery Options: You'll have enhanced recovery options in case you lose access to your account. Unlike with traditional Ethereum accounts, ERC-4337 allows you to add recovery addresses to your contract account, giving you more flexibility and security in the event of a lost password or stolen device.
  • Sponsoring Gas Fees:You'll enjoy the option of having your gas fees sponsored, which could save you a significant amount of money in the long run. With ERC-4337, you won't need to worry about paying for gas fees yourself, as a third party can cover them for you in exchange for a small fee.

Benefits of ERC-4337

BenefitsExplanations
Improved user experienceWith account abstraction, users would no longer need to hold and manage multiple accounts for different dApps. Smart contracts would be able to handle their own transactions, simplifying the user experience and making it easier to interact with dApps.
Increased securitySmart contracts would be able to act as account addresses, reducing the risk of hacks and attacks on externally owned accounts, which are currently the only accounts that can initiate transactions in Ethereum. This would enhance the security of the network and protect users' funds.
Easier onboarding for new developersAccount abstraction would make it easier for new developers to build and deploy dApps on Ethereum, as they would no longer need to learn the intricacies of externally owned accounts and gas fees. This would encourage more developers to build on Ethereum and increase the overall growth of the ecosystem.
Interoperability with other blockchainsAccount abstraction would enable Ethereum to be more interoperable with other blockchains that support smart contracts. This would allow for cross-chain interactions and enable developers to build dApps that leverage the strengths of multiple blockchains.

Drawbacks of ERC-4337

Although ERC-4337 offers considerable advantages, adopting it comes with certain risks. First, the added flexibility of this new standard could potentially be exploited. Moreover, compatibility problems with current wallets and applications, along with the necessity for users to trust third parties for their transactions, might present significant challenges. Furthermore, implementing ERC-4337 could demand substantial infrastructure and technical expertise, possibly raising centralization concerns. Lastly, the high expenses of the Ethereum network and the requirement for contract verification may further hinder the adoption of this standard. It is vital that users and developers remain vigilant and conscious of these potential risks while considering the implementation of ERC-4337.

Conclusion

To conclude, ERC-4337 represents a suggested Ethereum Improvement Proposal that incorporates account abstraction into the Ethereum blockchain. This enables smart contracts to directly send and receive funds without requiring an intermediary account. The new feature has the potential to streamline user experience, enhance security, and facilitate the development and deployment of dApps on Ethereum for new developers.

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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?

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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