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Different Token Release Schedules

Kajetan Olas

15 Mar 2024
Different Token Release Schedules

As simple as it may sound, the decision on the release schedule of tokens is anything but that. It's a strategic choice that can have significant consequences. A well-thought-out token release schedule can prevent market flooding, encourage steady growth, and foster trust in the project. Conversely, a poorly designed schedule may lead to rapid devaluation or loss of investor confidence.

In this article, we will explore the various token release schedules that blockchain projects may adopt. Each type comes with its own set of characteristics, challenges, and strategic benefits. From the straightforwardness of linear schedules to the incentive-driven dynamic releases, understanding these mechanisms is crucial for all crypto founders.

Table of Contents

Linear Token Release Schedule

The linear token release schedule is perhaps the most straightforward approach to token distribution. As the name suggests, tokens are released at a constant rate over a specified period until all tokens are fully vested. This approach is favored for its simplicity and ease of understanding, which can be an attractive feature for investors and project teams alike.

Characteristics

  • Predictability: The linear model provides a clear and predictable schedule that stakeholders can rely on. This transparency is often appreciated as it removes any uncertainty regarding when tokens will be available.
  • Implementation Simplicity: With no complex rules or conditions, a linear release schedule is relatively easy to implement and manage. It avoids the need for intricate smart contract programming or ongoing adjustments.
  • Neutral Incentives: There is no explicit incentive for early investment or late participation. Each stakeholder is treated equally, regardless of when they enter the project. This can be perceived as a fair distribution method, as it does not disproportionately reward any particular group.

Implications

  • Capital Dilution Risk: Since tokens are released continuously at the same rate, there's a potential risk that the influx of new tokens into the market could dilute the value, particularly if demand doesn't keep pace with the supply.
  • Attracting Continuous Capital Inflow: A linear schedule may face challenges in attracting new investors over time. Without the incentive of increasing rewards or scarcity over time, sustaining investor interest solely based on project performance can be a test of the project's inherent value and market demand.
  • Neutral Impact on Project Commitment: The lack of timing-based incentives means that commitment to the project may not be influenced by the release schedule. The focus is instead placed on the project's progress and delivery on its roadmap.

In summary, a linear token release schedule offers a no-frills, equal-footing approach to token distribution. While its simplicity is a strength, it can also be a limitation, lacking the strategic incentives that other models offer. In the next sections, we will compare this to other, more dynamic schedules that aim to provide additional strategic advantages.

Growing Token Release Schedule

A growing token release schedule turns the dial up on token distribution as time progresses. This schedule is designed to increase the number of tokens released to the market or to stakeholders with each passing period. This approach can often be associated with incentivizing the sustained growth of the project by rewarding long-term holders.

Characteristics

  • Incentivized Patience: A growing token release schedule encourages stakeholders to remain invested in the project for longer periods, as the reward increases over time. This can be particularly appealing to long-term investors who are looking to maximize their gains.
  • Community Reaction: Such a schedule may draw criticism from those who prefer immediate, high rewards and may be viewed as unfairly penalizing early adopters who receive fewer tokens compared to those who join later. The challenge is to balance the narrative to maintain community support.
  • Delayed Advantage: There is a delayed gratification aspect to this schedule. Early investors might not see an immediate substantial benefit, but they are part of a strategy that aims to increase value over time, aligning with the project’s growth.

Implications

  • Sustained Capital Inflow: By offering higher rewards later, a project can potentially sustain and even increase its capital inflow as the project matures. This can be especially useful in supporting long-term development and operational goals.
  • Potential for Late-Stage Interest: As the reward for holding tokens grows over time, it may attract new investors down the line, drawn by the prospect of higher yields. This can help to maintain a steady interest in the project throughout its lifecycle.
  • Balancing Perception and Reality: Managing the community's expectations is vital. The notion that early participants are at a disadvantage must be addressed through clear communication about the long-term vision and benefits.

In contrast to a linear schedule, a growing token release schedule adds a strategic twist that favors the longevity of stakeholder engagement. It's a model that can create a solid foundation for future growth but requires careful communication and management to keep stakeholders satisfied. Up next, we will look at the shrinking token release schedule, which applies an opposite approach to distribution.

Shrinking Token Release Schedule

The shrinking token release schedule is characterized by a decrease in the number of tokens released as time goes on. This type of schedule is intended to create a sense of urgency and reward early participants with higher initial payouts.

Characteristics

  • Early Bird Incentives: The shrinking schedule is crafted to reward the earliest adopters the most, offering them a larger share of tokens initially. This creates a compelling case for getting involved early in the project's lifecycle.
  • Fear of Missing Out (FOMO): This approach capitalizes on the FOMO effect, incentivizing potential investors to buy in early to maximize their rewards before the release rate decreases.
  • Decreased Inflation Over Time: As fewer tokens are released into circulation later on, the potential inflationary pressure on the token's value is reduced. This can be an attractive feature for investors concerned about long-term value erosion.

Implications

  • Stimulating Early Adoption: By offering more tokens earlier, projects may see a surge in initial capital inflow, providing the necessary funds to kickstart development and fuel early-stage growth.
  • Risk of Decreased Late-Stage Incentives: As the reward diminishes over time, there's a risk that new investors may be less inclined to participate, potentially impacting the project's ability to attract capital in its later stages.
  • Market Perception and Price Dynamics: The market must understand that the shrinking release rate is a deliberate strategy to encourage early investment and sustain the token's value over time. However, this can lead to challenges in maintaining interest as the release rate slows, requiring additional value propositions.

A shrinking token release schedule offers an interesting dynamic for projects seeking to capitalize on early market excitement. While it can generate significant early support, the challenge lies in maintaining momentum as the reward potential decreases. This necessitates a robust project foundation and continued delivery of milestones to retain stakeholder interest.

Dynamic Token Release Schedule

A dynamic token release schedule represents a flexible and adaptive approach to token distribution. Unlike static models, this schedule can adjust the rate of token release based on specific criteria. Example criteria are: project’s milestones, market conditions, or the behavior of token holders. This responsiveness is designed to offer a balanced strategy that can react to the project's needs in real-time.

Characteristics

  • Adaptability: The most significant advantage of a dynamic schedule is its ability to adapt to changing circumstances. This can include varying the release rate to match market demand, project development stages, or other critical factors.
  • Risk Management: By adjusting the flow of tokens in response to market conditions, a dynamic schedule can help mitigate certain risks. For example: inflation, token price volatility, and the impact of market manipulation.
  • Stakeholder Alignment: This schedule can be structured to align incentives with the project's goals. This means rewarding behaviors that contribute to project's longevity, such as holding tokens for certain periods or participating in governance.

Implications

  • Balancing Supply and Demand: A dynamic token release can fine-tune the supply to match demand, aiming to stabilize the token price. This can be particularly effective in avoiding the boom-and-bust cycles that plague many cryptocurrency projects.
  • Investor Engagement: The flexibility of a dynamic schedule keeps investors engaged, as the potential for reward can change in line with project milestones and success markers, maintaining a sense of involvement and investment in the project’s progression.
  • Complexity and Communication: The intricate nature of a dynamic schedule requires clear and transparent communication with stakeholders to ensure understanding of the system. The complexity also demands robust technical implementation to execute the varying release strategies effectively.

Dynamic token release schedule is a sophisticated tool that, when used judiciously, offers great flexibility in navigating unpredictable crypto markets. It requires a careful balance of anticipation, reaction, and communication but also gives opportunity to foster project’s growth.

Conclusion

A linear token release schedule is the epitome of simplicity and fairness, offering a steady and predictable path. The growing schedule promotes long-term investment and project loyalty, potentially leading to sustained growth. In contrast, the shrinking schedule seeks to capitalize on the enthusiasm of early adopters, fostering a vibrant initial ecosystem. Lastly, the dynamic schedule stands out for its intelligent adaptability, aiming to strike a balance between various stakeholder interests and market forces.

The choice of token release schedule should not be made in isolation; it must consider the project's goals, the nature of its community, the volatility of the market, and the overarching vision of the creators.

FAQ

What are the different token release schedules?

  • Linear, growing, shrinking, and dynamic schedules.

How does a linear token release schedule work?

  • Releases tokens at a constant rate over a specified period.

What is the goal of a shrinking token release schedule?

  • Rewards early adopters with more tokens and decreases over time.

Tagi

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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!

Tagi

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!

Tagi