Token Engineering Process

Kajetan Olas

13 Apr 2024
Token Engineering Process

Token Engineering is an emerging field that addresses the systematic design and engineering of blockchain-based tokens. It applies rigorous mathematical methods from the Complex Systems Engineering discipline to tokenomics design.

In this article, we will walk through the Token Engineering Process and break it down into three key stages. Discovery Phase, Design Phase, and Deployment Phase.

Discovery Phase of Token Engineering Process

The first stage of the token engineering process is the Discovery Phase. It focuses on constructing high-level business plans, defining objectives, and identifying problems to be solved. That phase is also the time when token engineers first define key stakeholders in the project.

Defining the Problem

This may seem counterintuitive. Why would we start with the problem when designing tokenomics? Shouldn’t we start with more down-to-earth matters like token supply? The answer is No. Tokens are a medium for creating and exchanging value within a project’s ecosystem. Since crypto projects draw their value from solving problems that can’t be solved through TradFi mechanisms, their tokenomics should reflect that. 

The industry standard, developed by McKinsey & Co. and adapted to token engineering purposes by Outlier Ventures, is structuring the problem through a logic tree, following MECE.
MECE stands for Mutually Exclusive, Collectively Exhaustive. Mutually Exclusive means that problems in the tree should not overlap. Collectively Exhaustive means that the tree should cover all issues.

In practice, the “Problem” should be replaced by a whole problem statement worksheet. The same will hold for some of the boxes.
A commonly used tool for designing these kinds of diagrams is the Miro whiteboard.

Identifying Stakeholders and Value Flows in Token Engineering

This part is about identifying all relevant actors in the ecosystem and how value flows between them. To illustrate what we mean let’s consider an example of NFT marketplace. In its case, relevant actors might be sellers, buyers, NFT creators, and a marketplace owner. Possible value flow when conducting a transaction might be: buyer gets rid of his tokens, seller gets some of them, marketplace owner gets some of them as fees, and NFT creators get some of them as royalties.

Incentive Mechanisms Canvas

The last part of what we consider to be in the Discovery Phase is filling the Incentive Mechanisms Canvas. After successfully identifying value flows in the previous stage, token engineers search for frictions to desired behaviors and point out the undesired behaviors. For example, friction to activity on an NFT marketplace might be respecting royalty fees by marketplace owners since it reduces value flowing to the seller.

source: https://www.canva.com/design/DAFDTNKsIJs/8Ky9EoJJI7p98qKLIu2XNw/view#7

Design Phase of Token Engineering Process

The second stage of the Token Engineering Process is the Design Phase in which you make use of high-level descriptions from the previous step to come up with a specific design of the project. This will include everything that can be usually found in crypto whitepapers (e.g. governance mechanisms, incentive mechanisms, token supply, etc). After finishing the design, token engineers should represent the whole value flow and transactional logic on detailed visual diagrams. These diagrams will be a basis for creating mathematical models in the Deployment Phase. 

Token Engineering Artonomous Design Diagram
Artonomous design diagram, source: Artonomous GitHub

Objective Function

Every crypto project has some objective. The objective can consist of many goals, such as decentralization or token price. The objective function is a mathematical function assigning weights to different factors that influence the main objective in the order of their importance. This function will be a reference for machine learning algorithms in the next steps. They will try to find quantitative parameters (e.g. network fees) that maximize the output of this function.
Modified Metcalfe’s Law can serve as an inspiration during that step. It’s a framework for valuing crypto projects, but we believe that after adjustments it can also be used in this context.

Deployment Phase of Token Engineering Process

The Deployment Phase is final, but also the most demanding step in the process. It involves the implementation of machine learning algorithms that test our assumptions and optimize quantitative parameters. Token Engineering draws from Nassim Taleb’s concept of Antifragility and extensively uses feedback loops to make a system that gains from arising shocks.

Agent-based Modelling 

In agent-based modeling, we describe a set of behaviors and goals displayed by each agent participating in the system (this is why previous steps focused so much on describing stakeholders). Each agent is controlled by an autonomous AI and continuously optimizes his strategy. He learns from his experience and can mimic the behavior of other agents if he finds it effective (Reinforced Learning). This approach allows for mimicking real users, who adapt their strategies with time. An example adaptive agent would be a cryptocurrency trader, who changes his trading strategy in response to experiencing a loss of money.

Monte Carlo Simulations

Token Engineers use the Monte Carlo method to simulate the consequences of various possible interactions while taking into account the probability of their occurrence. By running a large number of simulations it’s possible to stress-test the project in multiple scenarios and identify emergent risks.

Testnet Deployment

If possible, it's highly beneficial for projects to extend the testing phase even further by letting real users use the network. Idea is the same as in agent-based testing - continuous optimization based on provided metrics. Furthermore, in case the project considers airdropping its tokens, giving them to early users is a great strategy. Even though part of the activity will be disingenuine and airdrop-oriented, such strategy still works better than most.

Time Duration

Token engineering process may take from as little as 2 weeks to as much as 5 months. It depends on the project category (Layer 1 protocol will require more time, than a simple DApp), and security requirements. For example, a bank issuing its digital token will have a very low risk tolerance.

Required Skills for Token Engineering

Token engineering is a multidisciplinary field and requires a great amount of specialized knowledge. Key knowledge areas are:

  • Systems Engineering
  • Machine Learning
  • Market Research
  • Capital Markets
  • Current trends in Web3
  • Blockchain Engineering
  • Statistics

Summary

The token engineering process consists of 3 steps: Discovery Phase, Design Phase, and Deployment Phase. It’s utilized mostly by established blockchain projects, and financial institutions like the International Monetary Fund. Even though it’s a very resource-consuming process, we believe it’s worth it. Projects that went through scrupulous design and testing before launch are much more likely to receive VC funding and be in the 10% of crypto projects that survive the bear market. Going through that process also has a symbolic meaning - it shows that the project is long-term oriented.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to contact@nextrope.com. Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.

FAQ

What does token engineering process look like?

  • Token engineering process is conducted in a 3-step methodical fashion. This includes Discovery Phase, Design Phase, and Deployment Phase. Each of these stages should be tailored to the specific needs of a project.

Is token engineering meant only for big projects?

  • We recommend that even small projects go through a simplified design and optimization process. This increases community's trust and makes sure that the tokenomics doesn't have any obvious flaws.

How long does the token engineering process take?

  • It depends on the project and may range from 2 weeks to 5 months.

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Nextrope Launches “AI-Powered Smart Contract Auditing” Project

Miłosz Mach

03 Mar 2025
Nextrope Launches “AI-Powered Smart Contract Auditing” Project

Next Enterprises Sp. z o.o. is implementing a project co-financed by the European Funds, titled "Smart Contract Auditing with Artificial Intelligence". The goal of the project is to develop and deploy an advanced AI model that enables efficient analysis, vulnerability detection, and security auditing of smart contracts, taking into account their complexity and uniqueness.

Planned Project Tasks:

  • Development of an AI model trained on Solidity keywords;
  • Creation of an effective model in simulated conditions;
  • Analysis of the unpredictability of compiled code execution within the Ethereum Virtual Machine (EVM) in the context of the developed model in a controlled environment;
  • Validation of the model in real-world conditions.

Target Groups:

  • Specialized audit firms focused on smart contract security;
  • Companies developing and/or deploying smart contracts on various platforms;
  • Exchanges, wallet providers, and decentralized applications (dApps) in the blockchain sector;
  • Government agencies or industry compliance bodies responsible for blockchain technology regulation;
  • Smart contract security specialists and developers.

The implementation of the developed tool will enable automated and efficient auditing of smart contracts. The model will provide detailed insights and recommendations for optimizing transaction costs and improving contract performance. As a result, users will be able to make informed decisions, enhancing security and operational efficiency within the blockchain ecosystem. Key benefits stem from the model’s training on smart contract code, audit data, and detected vulnerabilities. Additionally, the incorporation of chaos theory principles will allow for more precise risk and anomaly forecasting.

By deploying this advanced AI model, the project will enhance the security, efficiency, and accessibility of blockchain technology for end users. This will translate into tangible social and economic benefits, including:

  1. Economic Security
  2. Business and Financial Security
  3. Increased Public Trust
  4. Optimization of Transaction Costs
  5. Support for Innovation and Entrepreneurship
  6. Education and Public Awareness

Project Value: 4,173,953.24 PLN
European Funds Contribution: 3,090,156.39 PLN

#EUFunds #EuropeanFunds

Challenges in Smart Contract Auditing

Smart contracts have become a fundamental component of blockchain technology, eliminating intermediaries, and automating processes. However, their growing significance also introduces new challenges, particularly in ensuring security and compliance with industry standards.

Traditional smart contract audits rely heavily on manual code reviews, which are expensive, time-consuming, and prone to human error. As cyber threats continue to evolve, the use of advanced technologies to support the auditing process is imperative.

The Role of AI in Data Analysis

Artificial intelligence (AI) introduces a new paradigm in smart contract security assessment by leveraging its capability to process vast amounts of data and identify patterns that may go unnoticed with traditional auditing methods. AI enables:

  • Automated code analysis and real-time detection of potential vulnerabilities,
  • Optimization of auditing processes by reducing human errors and improving threat identification efficiency,
  • Better adaptation to evolving regulatory requirements and emerging threats within the blockchain ecosystem,
  • Rapid analysis of large datasets, allowing for quick insights and the detection of non-obvious dependencies in smart contract code.

By utilizing AI, the auditing process becomes more comprehensive, precise, and scalable, enabling continuous risk monitoring and adaptation to new attack vectors.

A New Era of Smart Contract Security with AI

With the support of European Funds under the European Funds for a Modern Economy (FENG) program, we are conducting research on next-generation blockchain auditing methods, reinforcing Nextrope’s position as a leader in innovative technology solutions.

The "Smart Contract Auditing with Artificial Intelligence (AI)" project contributes to key aspects of blockchain security by:

  • Automating smart contract audits, accelerating verification processes, and improving their accuracy,
  • Optimizing costs, making professional audits more accessible to a broader range of entities,
  • Raising security standards and enhancing regulatory compliance,
  • Increasing trust in smart contracts, fostering broader technology adoption.

Interested in learning more about our project or discovering how to utilize AI in your company? 📩 Contact us at contact@nextrope.com for further details!

Tagi

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.