Account Abstraction in Action: Case Studies

Karolina

06 Dec 2023
Account Abstraction in Action: Case Studies

In the rapidly evolving world of blockchain and cryptocurrencies, one technological advancement stands out for its potential to revolutionize user interaction and operational efficiency: Account Abstraction (AA). This concept, although technical in nature, offers a gateway to a more accessible and versatile experience in the realm of digital assets and decentralized applications.

In this article, we delve into the intricacies of Account Abstraction, exploring its practical applications through various case studies and potential future implementations. Our journey into the world of AA not only highlights its current capabilities but also sheds light on its promising future in shaping the landscape of blockchain technology and cryptocurrency usage.

What is Account Abstraction?

Account Abstraction, at its core, is a concept that seeks to simplify and unify the user experience in the blockchain ecosystem. Traditionally, blockchain accounts are differentiated into two primary types: externally owned accounts (EOAs), controlled by private keys, and contract accounts, governed by their contract code. Account Abstraction blurs this distinction, proposing a more flexible framework where the functionalities of contract accounts can be integrated into user accounts.

The idea of Account Abstraction is not new; it has roots tracing back to the early days of Ethereum, with co-founder Vitalik Buterin being a prominent advocate. The primary goal of AA is to enhance the user experience by providing more control and flexibility, while also bolstering security measures. In a typical blockchain environment, users often face challenges related to key management, transaction complexities, and limited operational functionalities. Account Abstraction addresses these issues by enabling users to execute transactions that are more versatile, secure, and user-friendly.

MUST READ: What is Account Abstraction?

The Timeline of Account Abstraction Adoption

(from Binance Report) 

Source: A Primer on Account Abstraction August 2023 https://research.binance.com/static/pdf/a-primer-on-account-abstraction.pdf 

Case Studies of Account Abstraction

Visa's Paymaster Contracts

Experiment with Paymaster Contracts. Visa explored the use of Paymaster contracts to abstract away basic blockchain interactions, improving the on-chain payment experience through a self-custodial smart contract wallet. This proof of concept aimed to reduce friction and unlock the potential of digital transactions.

Paymaster facilitating the use of ERC-20 tokens for transaction fees, Source

Implementation. The Paymaster contract acts as an intermediary currency conversion service, allowing users to pay in various digital currencies, which are then converted to the blockchain’s native token for gas fees. Alternatively, it can cover the gas fees, offering free transactions through their wallet platform.

Safe (Formerly Gnosis Safe)

Multi-Signature Scheme. Safe stands out for its multi-signature scheme, requiring multiple entities to sign transactions, reducing the risk of malicious attacks.

Integration of AA. Safe has integrated the ERC-4337 standard, allowing users to create smart contract wallets with customizable rules for transaction authorization, such as setting spending limits for enhanced security.

Argent on StarkNet

Social Recovery Feature. Argent, a leading wallet provider on StarkNet, introduced the concept of social recovery, allowing users to recover lost or forgotten private keys.

Innovative Wallet Recovery. Users can nominate “guardians” to help access the wallet if the seed phrase is forgotten, or use their email and phone number for off-chain recovery, introducing a familiar two-factor authentication mechanism.

MUST READ: Account Abstraction on Starknet

Braavos Wallet

Signature Abstraction. Braavos, another wallet provider on StarkNet, has adopted a form of signature abstraction, allowing users to customize their transaction verification process.

Biometric Identity Authentication. Users can access their wallet using their phone’s biometric features, like facial or fingerprint recognition, providing a secure and user-friendly experience.

Visa's Delegable Accounts for Automatic Payments

Auto Payments for Self-Custodial Wallets. Visa demonstrated a solution for automatic payments in self-custodial wallets, enabling recurring payments based on predetermined conditions without manual user approval each time.

Ease of Transaction. This setup allows users to set up programmable payment instructions, highlighting the potential for real-world applications and convenience.

Lens Protocol's Social Media Integration

Dispatcher Wallet. Lens Protocol implemented AA to delegate signing privileges to a dispatcher wallet for functions like posting, commenting, and changing profile metadata.

User-Friendly Interactions. This enables seamless interactions with dApps without constant approval and the dispatcher wallet also covers gas fees, removing the need for users to hold native tokens for in-app interactions.

ERC-6551: Token-Bound Accounts

Enhanced NFT Utility. ERC-6551 empowers NFTs to function as smart contract accounts, enhancing their utility by allowing them to hold assets, manage identities, and participate more actively in the on-chain landscape.

Sapienz Project

Digital Street Culture. The Sapienz project by Stapelverse incorporates ERC-6551, offering customizable characters based on owned NFTs, with various cosmetics attached to the TBA of the characters.


Source: @stapleverse

Conclusion - Account Abstraction Case Studies

Case Study / ImplementationKey FeaturesImpact / Significance
Visa's Paymaster ContractsPaymaster contracts for self-custodial wallets; intermediary for currency conversion and gas fee coverage.Enhances on-chain payment experience, reduces friction, and unlocks digital transaction potential.
Safe (Formerly Gnosis Safe)Multi-signature scheme integrated with ERC-4337 for customizable transaction authorization.Increases security and operational flexibility in wallet transactions.
Argent on StarkNetSocial recovery feature allowing wallet recovery through nominated 'guardians' or off-chain methods.Improves wallet security and user experience through innovative recovery options.
Braavos WalletSignature abstraction enabling customized transaction verification; biometric identity authentication.Provides secure and user-friendly access to wallet functions.
Visa's Delegable Accounts for Automatic PaymentsAutomated payments in self-custodial wallets with programmable payment instructions.Facilitates real-world application of blockchain for convenient, automated transactions.
Lens Protocol's Social Media IntegrationDispatcher wallet for delegating signing privileges; seamless interactions with dApps, covering gas fees.Enhances user experience in social media and dApp interactions.
ERC-6551: Token-Bound AccountsNFTs as smart contract accounts; enhanced utility in holding assets and managing identities.Expands the functionalities and applications of NFTs in the blockchain ecosystem.
Sapienz ProjectERC-6551 utilization for customizable NFT-based characters in digital street culture context.Innovates in digital culture by merging NFTs with character customization and interaction.

These case studies showcase the diverse and impactful applications of Account Abstraction across various sectors. They highlight AA's potential in simplifying user experience, enhancing security, and expanding the functionalities of blockchain technology.

Most viewed


Never miss a story

Stay updated about Nextrope news as it happens.

You are subscribed

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
Nextrope Logo

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