How NOT to Create a DAO: Common Pitfalls You Should Avoid

Kajetan Olas

27 Dec 2024
How NOT to Create a DAO: Common Pitfalls You Should Avoid

Decentralized Autonomous Organizations (DAOs) represent a fundamental shift in how communities, companies, and initiatives can coordinate efforts, funds, and decisions on the blockchain. By leveraging transparent smart contracts and on-chain governance mechanisms, DAOs aim to distribute authority, reduce overhead, and foster a more democratic decision-making process. However, building a successful DAO isn’t just about cutting-edge tech or grand ideas—it also requires a clear vision, well-crafted governance rules, and a strategically engaged community.

In this article, we’ll take a counterintuitive approach by highlighting how not to create a DAO. By focusing on common pitfalls—from legal oversights to governance missteps—we can better understand what truly contributes to a thriving, sustainable DAO. This perspective aligns with the importance of recognizing cognitive biases, such as insensitivity to base rates and the conjunction fallacy, which often lead enthusiastic founders to overlook real-world data and complexity. Avoiding these traps can be the difference between launching a resilient DAO and watching an ambitious project crumble under misaligned structures or unmet expectations.

2. Missing the Governance Threshold Mark

Governance Thresholds Gone Wrong

Governance thresholds dictate how many votes or what percentage of voting power is needed to pass a proposal within a DAO. Striking the right balance here is crucial. Thresholds that are set too high can stifle progress by making it nearly impossible for proposals to succeed, effectively discouraging member participation. On the other hand, thresholds that are too low can lead to frivolous proposals or constant voting spam, making governance more of a burden than a benefit.

When designing your DAO’s thresholds, consider:

  • Community size and engagement levels: Larger communities might handle higher thresholds more comfortably, while smaller groups may benefit from lower requirements to encourage active participation.
  • Type of proposals: Operational decisions may need a lower threshold, whereas critical changes (such as tokenomics or treasury management) often require more consensus.
  • Voter fatigue: The more frequently members are asked to vote—and if it’s too easy to put forward proposals—the greater the risk of apathy or disengagement.

Over-Complex vs. Over-Simplified Governance

It’s tempting to either pile on complicated governance rules or oversimplify them to keep decision-making quick. However, both extremes can be problematic. Simplicity in governance is key to enhancing clarity and participation. Overly complex smart contracts and procedural layers can dissuade newcomers from getting involved, while an oversimplified model might fail to address potential conflicts or security vulnerabilities.

Some issues to watch out for:

  • Complex Smart Contracts: More code means more potential bugs and greater difficulty in auditing or updating governance logic.
  • Opaque Voting Processes: If members can’t easily understand how votes are tallied or how proposals are introduced, engagement drops.
  • Excessive Centralization in “Simple” Models: In trying to streamline governance, some DAOs inadvertently concentrate power in the hands of a few decision-makers.

Ultimately, aiming for a balanced governance framework—one that is easy enough for members to participate in but comprehensive enough to protect the DAO from abuse—is central to avoiding the pitfalls of governance threshold mismanagement.

3. Underestimating Legal and Regulatory Aspects

Legal Wrappers and Compliance

Building a DAO without considering legal and regulatory frameworks is a common recipe for disaster. While decentralization is a powerful concept, it doesn’t absolve projects from potential liabilities and compliance obligations. Assigning your DAO a formal legal wrapper—whether it’s a foundation, a cooperative, an LLC, or another entity type—can help mitigate personal risks for contributors and align your organization with existing regulatory regimes.

Failing to think through these details often leads to:

  • Personal Liability for Founders: Without a proper legal entity, core contributors might become personally responsible for any legal disputes or financial mishaps involving the DAO.
  • Regulatory Crackdowns: Governing bodies worldwide are actively monitoring DAOs for compliance with securities laws, anti-money laundering (AML) regulations, and tax obligations. Ignoring these can lead to penalties, fines, or forced shutdowns.

Non-Existent or Inadequate Documentation

Equally problematic is the lack of clear documentation outlining the DAO’s legal structure and operational protocols. From voting procedures to treasury management, every aspect of the DAO’s lifecycle should be properly documented to reduce ambiguity and help new members understand their responsibilities. Inadequate documentation or outright neglect can create:

  • Confusion Over Roles and Responsibilities: Without explicit definitions, it’s easy for tasks to fall through the cracks or for disagreements to escalate.
  • Inability to Enforce Rules: DAOs rely on both smart contracts and social consensus. Formalizing rules in documentation helps ensure consistent enforcement and prevents unwelcome surprises.

In short, underestimating the legal dimension of DAO creation can derail even the most innovative projects. By proactively addressing legal and regulatory considerations—and maintaining thorough documentation—you not only protect core contributors but also fortify trust within your community and with external stakeholders.

Overlooking Community Building

The Importance of Community Engagement

A DAO, at its core, is nothing without an active and supportive community. Driving grassroots enthusiasm and participation is often the deciding factor between a thriving DAO and one that fizzles out. Yet, it’s surprisingly easy to underestimate just how vital it is to nurture community trust and engagement—especially during the early stages.

Some common pitfalls include:

  • Treating Community Members as Passive Observers
    Instead of viewing your community as a dynamic force, you might slip into a one-way communication style. This discourages members from taking initiative or contributing fresh ideas.
  • Lack of Clear Roles and Channels
    Without well-defined roles and open communication channels—like forums, Discord servers, or governance platforms—members can feel confused about where to participate or how to add value.
  • Ignoring Early Feedback
    In a DAO, the “wisdom of the crowd” can be a powerful asset. Overlooking or trivializing user feedback can lead to missed opportunities for innovation and improvement.

Failing to Incentivize Properly

Well-structured incentives lie at the heart of any successful DAO. Whether you’re offering governance tokens, staking rewards, or recognition badges, these incentives must be aligned with the DAO’s long-term goals. Misalignment often causes short-sighted behavior, where participants chase quick rewards rather than contributing meaningfully.

  • Overemphasis on Token Speculation
    If the primary draw for community members is the promise of quick token price gains, you risk attracting speculators instead of builders. This can lead to fleeting participation and sell-offs at the first sign of trouble.
  • Neglecting Non-Monetary Rewards
    Recognition, social standing, and meaningful collaboration can be just as powerful as financial incentives. When a DAO fails to provide pathways for skill development or leadership, member engagement wanes.
  • Cognitive Bias Traps
    Biases such as the conjunction fallacy can mislead founders into believing that if multiple positive outcomes are possible (e.g., rising token prices, active participation, mainstream adoption), then all those outcomes will inevitably happen together. This wishful thinking can blind DAOs to the need for thoughtful, data-driven incentive models.

To avoid these pitfalls, DAO creators must actively foster a culture of transparency, collaboration, and mutual respect. By setting clear expectations, leveraging diverse incentive structures, and consistently involving community feedback, you ensure members are motivated to contribute more than just their votes—they become co-creators in the DAO’s shared vision.

5. Ignoring Technical Considerations

Token Standards and Governance Frameworks

A solid technical foundation is essential when you create a DAO, particularly if it involves on-chain governance. Selecting the appropriate token standards and governance frameworks can significantly impact your DAO’s security, efficiency, and scalability.

Some pitfalls to watch out for include:

  • Choosing Incompatible Token Standards
    If your DAO relies on a token that isn’t easily integrated with governance contracts or lacks upgradeability, you might face roadblocks when implementing new features or patching vulnerabilities.
  • Underestimating Smart Contract Complexity
    Even “simple” governance tokens can hide complex logic behind the scenes. Overlooking these complexities may result in bugs, lockouts, or exploits that harm the DAO’s reputation and finances.
  • Ignoring Off-Chain vs. On-Chain Dynamics
    Governance strategies often combine on-chain decisions with off-chain discussions (e.g., using platforms like Discord or forums). Failing to synchronize these two spheres can fracture community engagement and hamper decision-making.

Poor Architecture and Security

Robust security isn’t just about preventing hacks—it's about building an architecture that can adapt to evolving threats and changing community needs.

Key oversights include:

  • Inadequate Auditing
    Smart contracts require thorough reviews, both automated and manual. Rushing to mainnet deployment without proper audits can lead to major losses—financial, reputational, or both.
  • No Contingency Plans
    If a vulnerability is discovered, how will you respond? Lacking emergency procedures or fallback governance mechanisms can leave a DAO paralyzed when critical decisions must be made quickly.
  • Over-Engineered Solutions
    While security is paramount, over-complicating the DAO’s architecture can create unintended vulnerabilities. Keeping your setup as simple as possible reduces attack surfaces and makes it easier for community members to understand and trust the system.

In short, technical considerations form the bedrock of a functional DAO. Choosing appropriate token standards, thoroughly auditing contracts, and designing for both present-day and future needs are non-negotiable steps in avoiding costly pitfalls.

Best Practices and Lessons

When studying successful DAOs, certain themes emerge time and again. According to Aragon the most robust DAOs share a commitment to simplicity, iteration, and transparent governance. Instead of rolling out overly sophisticated models from day one, they evolve and adapt based on community feedback and real-world performance.

Here are a few best practices worth emulating:

  • Iterative Approach to Governance
    Start small and build up. Launch a Minimal Viable DAO (MVD) to test voting processes, incentive mechanisms, and proposal management. Gather community feedback and refine before taking bigger steps.
  • Simple, Transparent Rules and Processes
    Ensure proposals are easy to understand and that the voting process is accessible to all token holders. Overly complicated frameworks can dissuade new members from participating.
  • Clear Roles and Shared Responsibilities
    Define contributor and community member roles early on. Whether you rely on working groups, committees, or elected leaders, clarity prevents power vacuums and fosters collaboration.
  • Open Communication and Education
    From Discord channels to public documentation, keep conversation and learning at the heart of your DAO. Encourage members to ask questions, propose improvements, and take leadership roles.

Academic Perspectives

Beyond practical experience, a growing body of research offers theoretical insights that can strengthen DAO governance. The discusses emerging patterns in DAOs, including how incentives and on-chain rules interact with off-chain social dynamics. By examining these findings, DAO creators can better anticipate challenges—like voter apathy, whale influence, or collusion—and integrate solutions from the outset.

Incorporating academic perspectives can help:

  • Validate Governance Assumptions
    Empirical data and rigorous analyses can confirm or challenge the assumptions behind your DAO’s architecture, preventing costly mistakes.
  • Stay Ahead of Regulatory and Social Shifts
    Academics often explore how upcoming policies or societal trends might impact DAOs, offering a forward-looking lens that day-to-day builders might miss.
  • Establish Credibility
    Aligning your DAO’s structure and operations with recognized research signals professionalism and thoroughness, potentially attracting more serious contributors, partners, and investors.

Conclusion

As you can see, creating a DAO involves more than just deploying a smart contract and distributing tokens. By examining these common pitfalls—from poor governance thresholds to inadequate legal structures, from neglecting community engagement to disregarding technical complexities—you gain a clearer picture of what not to do when you set out to create a DAO. Failing to address these areas often leads to compromised security, stalled decision-making, regulatory headaches, or outright community collapse

At Nextrope, we specialize in tailored blockchain and cryptocurrency solutions, including DAO creation and tokenomics design. If you’re looking to avoid these common pitfalls and build a thriving DAO that stands the test of time, feel free to contact us or explore more resources on our blog.

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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!

The Ultimate Web3 Backend Guide: Supercharge dApps with APIs

Tomasz Dybowski

04 Mar 2025
The Ultimate Web3 Backend Guide: Supercharge dApps with APIs

Introduction

Web3 backend development is essential for building scalable, efficient and decentralized applications (dApps) on EVM-compatible blockchains like Ethereum, Polygon, and Base. A robust Web3 backend enables off-chain computations, efficient data management and better security, ensuring seamless interaction between smart contracts, databases and frontend applications.

Unlike traditional Web2 applications that rely entirely on centralized servers, Web3 applications aim to minimize reliance on centralized entities. However, full decentralization isn't always possible or practical, especially when it comes to high-performance requirements, user authentication or storing large datasets. A well-structured backend in Web3 ensures that these limitations are addressed, allowing for a seamless user experience while maintaining decentralization where it matters most.

Furthermore, dApps require efficient backend solutions to handle real-time data processing, reduce latency, and provide smooth user interactions. Without a well-integrated backend, users may experience delays in transactions, inconsistencies in data retrieval, and inefficiencies in accessing decentralized services. Consequently, Web3 backend development is a crucial component in ensuring a balance between decentralization, security, and functionality.

This article explores:

  • When and why Web3 dApps need a backend
  • Why not all applications should be fully on-chain
  • Architecture examples of hybrid dApps
  • A comparison between APIs and blockchain-based logic

This post kicks off a Web3 backend development series, where we focus on the technical aspects of implementing Web3 backend solutions for decentralized applications.

Why Do Some Web3 Projects Need a Backend?

Web3 applications seek to achieve decentralization, but real-world constraints often necessitate hybrid architectures that include both on-chain and off-chain components. While decentralized smart contracts provide trustless execution, they come with significant limitations, such as high gas fees, slow transaction finality, and the inability to store large amounts of data. A backend helps address these challenges by handling logic and data management more efficiently while still ensuring that core transactions remain secure and verifiable on-chain.

Moreover, Web3 applications must consider user experience. Fully decentralized applications often struggle with slow transaction speeds, which can negatively impact usability. A hybrid backend allows for pre-processing operations off-chain while committing final results to the blockchain. This ensures that users experience fast and responsive interactions without compromising security and transparency.

While decentralization is a core principle of blockchain technology, many dApps still rely on a Web2-style backend for practical reasons:

1. Performance & Scalability in Web3 Backend Development

  • Smart contracts are expensive to execute and require gas fees for every interaction.
  • Offloading non-essential computations to a backend reduces costs and improves performance.
  • Caching and load balancing mechanisms in traditional backends ensure smooth dApp performance and improve response times for dApp users.
  • Event-driven architectures using tools like Redis or Kafka can help manage asynchronous data processing efficiently.

2. Web3 APIs for Data Storage and Off-Chain Access

  • Storing large amounts of data on-chain is impractical due to high costs.
  • APIs allow dApps to store & fetch off-chain data (e.g. user profiles, transaction history).
  • Decentralized storage solutions like IPFS, Arweave and Filecoin can be used for storing immutable data (e.g. NFT metadata), but a Web2 backend helps with indexing and querying structured data efficiently.

3. Advanced Logic & Data Aggregation in Web3 Backend

  • Some dApps need complex business logic that is inefficient or impossible to implement in a smart contract.
  • Backend APIs allow for data aggregation from multiple sources, including oracles (e.g. Chainlink) and off-chain databases.
  • Middleware solutions like The Graph help in indexing blockchain data efficiently, reducing the need for on-chain computation.

4. User Authentication & Role Management in Web3 dApps

  • Many applications require user logins, permissions or KYC compliance.
  • Blockchain does not natively support session-based authentication, requiring a backend for handling this logic.
  • Tools like Firebase Auth, Auth0 or Web3Auth can be used to integrate seamless authentication for Web3 applications.

5. Cost Optimization with Web3 APIs

  • Every change in a smart contract requires a new audit, costing tens of thousands of dollars.
  • By handling logic off-chain where possible, projects can minimize expensive redeployments.
  • Using layer 2 solutions like Optimism, Arbitrum and zkSync can significantly reduce gas costs.

Web3 Backend Development: Tools and Technologies

A modern Web3 backend integrates multiple tools to handle smart contract interactions, data storage, and security. Understanding these tools is crucial to developing a scalable and efficient backend for dApps. Without the right stack, developers may face inefficiencies, security risks, and scaling challenges that limit the adoption of their Web3 applications.

Unlike traditional backend development, Web3 requires additional considerations, such as decentralized authentication, smart contract integration, and secure data management across both on-chain and off-chain environments.

Here’s an overview of the essential Web3 backend tech stack:

1. API Development for Web3 Backend Services

  • Node.js is the go-to backend runtime good for Web3 applications due to its asynchronous event-driven architecture.
  • NestJS is a framework built on top of Node.js, providing modular architecture and TypeScript support for structured backend development.

2. Smart Contract Interaction Libraries for Web3 Backend

  • Ethers.js and Web3.js are TypeScript/JavaScript libraries used for interacting with Ethereum-compatible blockchains.

3. Database Solutions for Web3 Backend

  • PostgreSQL: Structured database used for storing off-chain transactional data.
  • MongoDB: NoSQL database for flexible schema data storage.
  • Firebase: A set of tools used, among other things, for user authentication.
  • The Graph: Decentralized indexing protocol used to query blockchain data efficiently.

4. Cloud Services and Hosting for Web3 APIs

When It Doesn't Make Sense to Go Fully On-Chain

Decentralization is valuable, but it comes at a cost. Fully on-chain applications suffer from performance limitations, high costs and slow execution speeds. For many use cases, a hybrid Web3 architecture that utilizes a mix of blockchain-based and off-chain components provides a more scalable and cost-effective solution.

In some cases, forcing full decentralization is unnecessary and inefficient. A hybrid Web3 architecture balances decentralization and practicality by allowing non-essential logic and data storage to be handled off-chain while maintaining trustless and verifiable interactions on-chain.

The key challenge when designing a hybrid Web3 backend is ensuring that off-chain computations remain auditable and transparent. This can be achieved through cryptographic proofs, hash commitments and off-chain data attestations that anchor trust into the blockchain while improving efficiency.

For example, Optimistic Rollups and ZK-Rollups allow computations to happen off-chain while only submitting finalized data to Ethereum, reducing fees and increasing throughput. Similarly, state channels enable fast, low-cost transactions that only require occasional settlement on-chain.

A well-balanced Web3 backend architecture ensures that critical dApp functionalities remain decentralized while offloading resource-intensive tasks to off-chain systems. This makes applications cheaper, faster and more user-friendly while still adhering to blockchain's principles of transparency and security.

Example: NFT-based Game with Off-Chain Logic

Imagine a Web3 game where users buy, trade and battle NFT-based characters. While asset ownership should be on-chain, other elements like:

  • Game logic (e.g., matchmaking, leaderboard calculations)
  • User profiles & stats
  • Off-chain notifications

can be handled off-chain to improve speed and cost-effectiveness.

Architecture Diagram

Below is an example diagram showing how a hybrid Web3 application splits responsibilities between backend and blockchain components.

Hybrid Web3 Architecture

Comparing Web3 Backend APIs vs. Blockchain-Based Logic

FeatureWeb3 Backend (API)Blockchain (Smart Contracts)
Change ManagementCan be updated easilyEvery change requires a new contract deployment
CostTraditional hosting feesHigh gas fees + costly audits
Data StorageCan store large datasetsLimited and expensive storage
SecuritySecure but relies on centralized infrastructureFully decentralized & trustless
PerformanceFast response timesLimited by blockchain throughput

Reducing Web3 Costs with AI Smart Contract Audit

One of the biggest pain points in Web3 development is the cost of smart contract audits. Each change to the contract code requires a new audit, often costing tens of thousands of dollars.

To address this issue, Nextrope is developing an AI-powered smart contract auditing tool, which:

  • Reduces audit costs by automating code analysis.
  • Speeds up development cycles by catching vulnerabilities early.
  • Improves security by providing quick feedback.

This AI-powered solution will be a game-changer for the industry, making smart contract development more cost-effective and accessible.

Conclusion

Web3 backend development plays a crucial role in scalable and efficient dApps. While full decentralization is ideal in some cases, many projects benefit from a hybrid architecture, where off-chain components optimize performance, reduce costs and improve user experience.

In future posts in this Web3 backend series, we’ll explore specific implementation details, including:

  • How to design a Web3 API for dApps
  • Best practices for integrating backend services
  • Security challenges and solutions

Stay tuned for the next article in this series!