DAO Governance models and use cases

Karolina

16 May 2023
DAO Governance models and use cases

DAO governance models is a crucial aspect of DAOs. It outlines decision-making processes, voting mechanisms, funds management, and stakeholder participation. These models have been used to fund, manage and govern DAOs in the cryptocurrency space for several years. This article will discuss the rise of DAOs and examine the various governance models adopted by these innovative organizations.

Excited about joining the DAO? Check out our guide!

Understanding DAO Governance Models

DAO governance models provide a structure for decentralized decision-making and resource allocation within an organization. These models are designed to promote transparency, inclusivity, and community-driven decision-making. Unlike traditional governance structures, where decisions are made by a select group of individuals or entities, DAOs enable broader participation, allowing stakeholders to contribute and influence decisions. Governance models are critical to the success of decentralized organizations. 

DAO Governance Models - Fundamental Concepts

  • Transparency: Promoting easy access to data and involvement in decision-making.
  • Security: Establishing protective measures against harmful attacks or tampering within the DAO.
  • Flexibility: Facilitating change and growth in response to the DAO's and its ecosystem's development.
  • Inclusivity: Fostering wide-ranging community involvement and engagement of stakeholders.

Main DAO Governance Models

Main DAO governance models

There are four main DAO governance models:

  • ConstitutionDAO, 
  • Friends with Benefits DAO, 
  • JuiceboxDAO,
  • Ethereum Name Service DAO. 

ConstitutionDAO

ConstitutionDAO represents a governing framework that allows users to collectively pool their resources and acquire shared asset ownership through cryptocurrencies. This DAO governance arrangement ensures stability for its members by implementing a clear set of rules that dictate the DAO's operations. 

As one of the first DAO governance structures, ConstitutionDAO has demonstrated the potential of decentralized organizations and the power of collective efforts in achieving shared goals.

Friends with Benefits DAO

FWB, or Friends with Benefits DAO, is a community centered around social tokens that aims to assist creators and forge solid connections between its participants. Utilizing dao governance models, FWB promotes a socially-driven approach where members holding vested tokens can partake in the decision-making process. This method highlights teamwork, repute, and the value of social capital, empowering members to jointly influence the community's path and efforts.

JuiceboxDAO

JuiceboxDAO represents a novel form of dao governance models, integrating aspects of both token-based systems and conviction voting. Within this paradigm, holders of tokens possess voting authority in relation to their stake size, while also being able to demonstrate their dedication by securing their tokens for a certain time frame. As tokens are locked for longer periods, the votes gain more influence. This method encourages lasting engagement and fosters harmony between the motives of stakeholders and the accomplishments of the DAO's projects and endeavors.

Ethereum Name Service DAO

The Ethereum Name Service (ENS) Decentralized Autonomous Organization (DAO) offers a fully distributed domain name system built upon the Ethereum blockchain network. Its governance framework integrates a unique "proof of individuality" process, in which participants establish their distinctiveness through an identity authentication procedure. The ENS DAO employs a quadratic voting mechanism that enables token holders to apportion their voting authority across multiple proposals. In doing so, this model fosters equitable treatment and deters the centralization of power by dispersing influence more evenly among participants.

ENS DAO works on a three-layered approach:

  • Discourse of proposals
  • Off-chain voting used by delegates
  • Voting on the blockchain

Use Cases of DAO Governance Models

1. Decentralized Finance (DeFi)

Decentralized Autonomous Organization (DAO) governance models have significantly impacted the field of decentralized finance (DeFi). DeFi platforms often leverage DAOs to manage key protocol decisions, such as setting interest rates, defining collateral requirements, or introducing new features. Applying a DAO governance structure allows DeFi initiatives to involve community members in the decision-making process, thereby fostering a more inclusive and decentralized financial landscape.

2. Collective Investment and Fund Management

Decentralized Autonomous Organizations (DAOs) have become valuable tools for group investment and the management of funds. With the implementation of DAO governance structures, those who hold tokens can collaboratively make investment choices, resulting in a more equitable and transparent approach to investing. These DAOs enable pooling of resources, empowering participants to team up and invest in various projects, oversee funds, and apportion profits according to predetermined rules.

3. Content Creation and Curation

In the digital content space, DAO governance models offer new opportunities for content creation and curation platforms. Utilizing DAOs allows content creators and curators to obtain rewards through community-driven voting systems and decision-making procedures. This guarantees that the most valuable and high-quality content receives recognition and financial incentives, creating a fairer and more decentralized content ecosystem.

4. Decentralized Governance

Perhaps the most fundamental use case is in decentralized governance itself. DAOs can be created to manage the decision-making processes within communities, organizations, or even entire cities. By giving power back to the people, DAOs facilitate direct democratic participation, allowing individuals to have a say in matters that affect them. This enables greater transparency, accountability, and inclusivity in governance processes.

Conclusion

DAOs have revolutionized traditional management structures, enabling decentralized decision-making and value creation. With the ability to apply different models to different sectors, such as DeFi, content platforms and investments, DAOs are able to transform and revolutionize a variety of industries.

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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