The Fundamentals of Token Engineering

Kajetan Olas

06 Mar 2024
The Fundamentals of Token Engineering

As the blockchain space evolves, the complexity of creating sustainable, efficient, and fair systems increases. Token Engineering provides a structured framework to address these challenges. It ensures that tokenomics is designed with a clear understanding of its potential impact on user behavior and system dynamics. This is particularly important in decentralized projects, where traditional control mechanisms are replaced by algorithmic governance.

Understanding Token Engineering

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. 

The Basis of Token Engineering

The foundation of Token Engineering lies in the realization that tokens are not merely digital assets but pivotal elements that facilitate governance, incentivize desired behaviors, and enable new forms of economic interactions. The discipline draws upon:

  • Complex Systems Science: Understanding the behavior of complex systems is essential for designing token economies that are resilient and adaptable. This involves studying network effects, feedback loops, and emergent behaviors within token ecosystems.
  • Behavioral Economics: Integrating insights from behavioral economics allows for the creation of token models that align with human behaviors and motivations, ensuring that token mechanisms encourage beneficial actions within the network.
  • Cryptoeconomic Protocols: These protocols are the backbone of decentralized networks, securing transactions and interactions without the need for centralized authorities. Token Engineering involves designing these protocols to ensure they are robust against attacks and manipulations.

The Objectives of Token Engineering

The primary objectives of Token Engineering include:

  • Sustainability: Ensuring that the token economy can sustain itself over the long term, through mechanisms that promote balance, reduce volatility, and encourage growth.
  • Security: Designing token systems that are secure against speculative attacks, protecting the integrity of the network and its participants.
  • Efficiency: Creating token economies that facilitate efficient transactions, interactions, and governance processes, minimizing costs and maximizing benefits for all participants.

The Process of Token Engineering

The process of Token Engineering is a methodical approach to designing, implementing, and refining token-based systems. It involves several stages, from the initial conceptualization of a token economy to its deployment and ongoing management. Each stage requires careful consideration of the economic, technical, and social aspects of the system.

Ideation and Objective Setting

The first step in the Token Engineering process is to clearly define the goals and objectives of the token system. This involves identifying the specific behaviors the tokens are meant to incentivize, the roles they will play within the ecosystem, and the values they represent. Objectives might include creating a more efficient payment system, facilitating decentralized governance, or incentivizing certain behaviors among network participants.

Model Development and Simulation

Once the objectives are set, the next step is to develop a model of the token economy. This model should include the mechanisms by which tokens will be issued, distributed, and exchanged, as well as how they will interact with other elements of the ecosystem. The model also needs to account for potential external influences and the behavior of participants. Simulations are then run to test the model under various conditions, allowing engineers to identify potential issues and make adjustments.

Testing and Refinement

After modeling and simulation, the proposed token system enters the testing phase. This can involve both virtual testing environments and real-world pilots or beta tests. During this phase, the focus is on identifying and fixing bugs, assessing the system's resilience to attacks, and ensuring that it behaves as intended under a wide range of conditions. Feedback from these tests is used to refine the model and improve the system's design.

Deployment and Monitoring

With testing and refinement complete, the token system is ready for deployment. This involves launching the token within the intended environment, whether it be a blockchain network, a specific platform, or a broader ecosystem. After deployment, continuous monitoring is crucial to ensure the system operates as expected, to manage any unforeseen issues, and to make necessary adjustments based on evolving conditions and objectives.

Iterative Improvement

Token Engineering is an iterative process. Even after deployment, the system is continually analyzed and improved based on real-world performance and changing conditions. This might involve adjusting token issuance rates, changing incentive mechanisms, or introducing new features to adapt to users' needs and market dynamics.

Different Approaches to Modelling

In the realm of Token Engineering, various modeling techniques are employed to analyze and predict the behavior of the protocol under a multitude of scenarios. Two of the most common models utilized are Monte Carlo simulations and agent-based simulations. These models serve as critical tools for engineers and researchers aiming to design efficient, resilient, and sustainable token-based systems.

Monte Carlo Simulations in Token Engineering

Monte Carlo simulations are a class of computational algorithms that rely on repeated random sampling to obtain numerical results. Within the context of Token Engineering, these simulations are used to model the probability of different outcomes in a token economy. The approach is particularly useful for assessing risk and uncertainty in complex systems where analytical solutions may be unattainable.

Token engineers run thousands or even millions of scenarios, each with a set of randomly generated variables. This allows them to study where all the extreme outputs come from and makes them aware of all unwanted interactions.

Agent-Based Simulations in Token Engineering

Agent-based simulations represent another powerful modeling technique, focusing on the interactions of individual agents within a token economy. These agents, which can represent users, smart contracts, or other entities, operate based on a set of rules and can adapt their behavior in response to the changing state of the system.

This type of simulation is particularly adept at capturing the emergent properties of decentralized systems. By simulating the interactions of multiple agents, token engineers can observe how local behaviors scale up to global system dynamics. Agent-based models are invaluable for studying phenomena related to spreading information. For example, the spread of adoption of new token functionalities, or the resilience of the system against coordinated attacks

Conclusion

Token Engineering is pivotal for the advancement of blockchain and decentralized systems, blending disciplines like economics, game theory, and complex systems science to design robust token economies. Through a detailed process from conception to deployment and beyond, it ensures these economies are adaptable and sustainable amidst the dynamic blockchain landscape.

Rigorous testing holds the promise of making decentralized systems more transparent and secure. As regulations roll out, it might be fundamental in proving the long-term viability of crypto projects to the general public.

If you're looking to design a sustainable tokenomics model for your DeFi project, please reach out to contact@nextrope.com. Our team is ready to help you create a tokenomics structure that aligns with your project's long-term growth and market resilience.

FAQ

What is Token Engineering?

  • It's a field focused on the systematic design and analysis of token-based systems. It integrates engineering principles to ensure that token economies are sustainable and secure.

How does Token Engineering contribute to sustainability and security in token economies?

  • Through modelling and simulations, it makes sure that a project is resilient even to the toughest conditions.

What are the stages involved in the Token Engineering process?

  • The process includes ideation and objective setting, model development and simulation, testing and refinement, deployment and monitoring, and iterative improvement.

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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.

What is Berachain? 🐻 ⛓️ + Proof-of-Liquidity Explained

Karolina

18 Mar 2024
What is Berachain? 🐻 ⛓️ + Proof-of-Liquidity Explained

Enter Berachain: a high-performance, EVM-compatible blockchain that is set to redefine the landscape of decentralized applications (dApps) and blockchain services. Built on the innovative Proof-of-Liquidity consensus and leveraging the robust Polaris framework alongside the CometBFT consensus engine, Berachain is poised to offer an unprecedented blend of efficiency, security, and user-centric benefits. Let's dive into what makes it a groundbreaking development in the blockchain ecosystem.

What is Berachain?

Overview

Berachain is an EVM-compatible Layer 1 (L1) blockchain that stands out through its adoption of the Proof-of-Liquidity (PoL) consensus mechanism. Designed to address the critical challenges faced by decentralized networks. It introduces a cutting-edge approach to blockchain governance and operations.

Key Features

  • High-performance Capabilities. Berachain is engineered for speed and scalability, catering to the growing demand for efficient blockchain solutions.
  • EVM Compatibility. It supports all Ethereum tooling, operations, and smart contract languages, making it a seamless transition for developers and projects from the Ethereum ecosystem.
  • Proof-of-Liquidity.This novel consensus mechanism focuses on building liquidity, decentralizing stake, and aligning the interests of validators and protocol developers.

MUST READ: Docs

EVM-Compatible vs EVM-Equivalent

EVM-Compatible

EVM compatibility means a blockchain can interact with Ethereum's ecosystem to some extent. It can interact supporting its smart contracts and tools but not replicating the entire EVM environment.

EVM-Equivalent

An EVM-equivalent blockchain, on the other hand, aims to fully replicate Ethereum's environment. It ensures complete compatibility and a smooth transition for developers and users alike.

Berachain's Position

Berachain can be considered an "EVM-equivalent-plus" blockchain. It supports all Ethereum operations, tooling, and additional functionalities that optimize for its unique Proof-of-Liquidity and abstracted use cases.

Berachain Modular First Approach

At the heart of Berachain's development philosophy is the Polaris EVM framework. It's a testament to the blockchain's commitment to modularity and flexibility. This approach allows for the easy separation of the EVM runtime layer, ensuring that Berachain can adapt and evolve without compromising on performance or security.

Proof Of Liquidity Overview

High-Level Model Objectives

  • Systemically Build Liquidity. By enhancing trading efficiency, price stability, and network growth, Berachain aims to foster a thriving ecosystem of decentralized applications.
  • Solve Stake Centralization. The PoL consensus works to distribute stake more evenly across the network, preventing monopolization and ensuring a decentralized, secure blockchain.
  • Align Protocols and Validators. Berachain encourages a symbiotic relationship between validators and the broader protocol ecosystem.

Proof-of-Liquidity vs Proof-of-Stake

Unlike traditional Proof of Stake (PoS), which often leads to stake centralization and reduced liquidity, Proof of Liquidity (PoL) introduces mechanisms to incentivize liquidity provision and ensure a fairer, more decentralized network. Berachain separates the governance token (BGT) from the chain's gas token (BERA) and incentives liquidity through BEX pools. Berachain's PoL aims to overcome the limitations of PoS, fostering a more secure and user-centric blockchain.

Berachain EVM and Modular Approach

Polaris EVM

Polaris EVM is the cornerstone of Berachain's EVM compatibility, offering developers an enhanced environment for smart contract execution that includes stateful precompiles and custom modules. This framework ensures that Berachain not only meets but exceeds the capabilities of the traditional Ethereum Virtual Machine.

CometBFT

The CometBFT consensus engine underpins Berachain's network, providing a secure and efficient mechanism for transaction verification and block production. By leveraging the principles of Byzantine fault tolerance (BFT), CometBFT ensures the integrity and resilience of the Berachain blockchain.

Conclusion

Berachain represents a significant leap forward in blockchain technology, combining the best of Ethereum's ecosystem with innovative consensus mechanisms and a modular development approach. As the blockchain landscape continues to evolve, Berachain stands out as a promising platform for developers, users, and validators alike, offering a scalable, efficient, and inclusive environment for decentralized applications and services.

Resources

For those interested in exploring further, a wealth of resources is available, including the Berachain documentation, GitHub repository, and community forums. It offers a compelling vision for the future of blockchain technology, marked by efficiency, security, and community-driven innovation.

FAQ

How is Berachain different?

  • It integrates Proof-of-Liquidity to address stake centralization and enhance liquidity, setting it apart from other blockchains.

Is Berachain EVM-compatible?

  • Yes, it supports Ethereum's tooling and smart contract languages, facilitating easy migration of dApps.

Can it handle high transaction volumes?

  • Yes, thanks to the Polaris framework and CometBFT consensus engine, it's built for scalability and high throughput.