What is Arbitrum?


19 Sep 2023
What is Arbitrum?

As the blockchain technology landscape continues to expand and evolve, two major challenges remain prominent, particularly within the Ethereum network: scalability and transaction cost. In response to these issues, we find Arbitrum as a promising solution. So, what is Arbitrum?

Arbitrum is a Layer 2 scaling solution designed exclusively for the Ethereum network. Its core function involves processing the majority of transactions off the primary Ethereum chain (off-chain) and submitting a summarized version, or 'rollup,' of these transactions to the main chain. This approach significantly alleviates the burden on the main Ethereum chain, leading to faster transaction times and considerably reduced gas fees.

Analysis of Arbitrum

In today's dynamic blockchain environment, continuous development and growth are imperative. As platforms like Ethereum become increasingly popular, scalability emerges as a considerable challenge. This is where Arbitrum comes into play - a Layer 2 scaling solution aimed at addressing many of the limitations Ethereum currently experiences. So, what is Arbitrum, and why is it garnering such attention within the blockchain sphere?

The Origin Story

Arbitrum, created by Offchain Labs, emerged due to the rising need for a more efficient transaction process on the Ethereum blockchain. As user adoption and decentralized applications on Ethereum began to surge, it became evident that the existing network structure could not efficiently manage high volumes without exorbitant transaction fees or delayed transaction times.

Fundamental Idea and Methodology

At its foundation, Arbitrum employs something referred to as "Optimistic Rollups." What does this entail? Generally, rollups involve consolidating or "rolling up" numerous transactions into one which gets recorded on the main chain. This translates to less on-chain data, leading to faster and more affordable transactions.

The "Optimistic" component of Optimistic Rollups stems from its mechanism. Rather than verifying every individual transaction (a burdensome and time-consuming effort), Optimistic Rollups operate based on trust by presuming each transaction is legitimate. There's a catch though - if any transaction is discovered to be invalid, mechanisms exist to penalize those involved. This approach effectively maintains a balance between trust and validation while enabling faster transaction times without sacrificing security.

Arbitrum's Enhancement of Ethereum

Ethereum boasts a strong and groundbreaking foundation; however, its shortcomings in scalability are apparent. This is where Arbitrum steps in. By processing the bulk of transactions off-chain and only submitting crucial data to Ethereum's main chain, it substantially eases the burden on Ethereum in the following ways:

  • Faster Transactions: No more lengthy waits for transaction confirmations.
  • Lower Fees: Reduced on-chain data processing leads to substantially lower transaction costs.
  • Improved Scalability: this layer 2 solution can accommodate a greater volume of transactions simultaneously, making it suitable for extensive dApps and platforms.

Essentially, Arbitrum serves as a connection point, maximizing Ethereum's advantages while concurrently offering solutions to its limitations. As the cryptocurrency community progresses and expands, innovative technologies like Arbitrum will take center stage in shaping the decentralized landscape of the future.

Features and Advantages of Arbitrum

Promising Layer 2 solution introduces a suite of features that cater to the prevailing issues of blockchain scalability and cost. Here’s a closer look at its main features and inherent advantages:

Enhanced Scalability

Higher Transaction Throughput: this layer 2 solution can process a multitude of transactions simultaneously, considerably enhancing the speed of operations.

Parallel Execution: With the ability to handle multiple transactions in tandem, Arbitrum reduces the backlog that's often witnessed on Ethereum’s main chain.

Cost Efficiency

Lower Gas Fees: Transactions on it are processed off-chain, resulting in significantly reduced gas fees on Ethereum.

Optimized Data Storage: With only essential data being recorded on the main chain, Arbitrum optimizes storage and, consequently, costs.


Seamless Ethereum Integration: Arbitrum is designed to be fully compatible with Ethereum's smart contracts, requiring little to no changes for developers to migrate their dApps.

Interoperable Tooling: Developers can employ familiar Ethereum tools and frameworks when working with Arbitrum.

Security Measures

Secure Consensus Mechanism: Leveraging Ethereum's security, Arbitrum benefits from the same trust and decentralization.

Fraud Proofs: The Optimistic Rollup design ensures that any fraudulent activity can be quickly detected and penalized.

Potential Use Cases for Arbitrum

Arbitrum’s unique feature set positions it as a sought-after Layer 2 solution for various applications.

Decentralized Finance (DeFi)

High-frequency Trading: With reduced transaction costs and faster speeds, Arbitrum can enable efficient high-frequency trading platforms in the DeFi space.

Yield Farming: Users and protocols can achieve better operational efficiency, making yield farming strategies more effective and lucrative.


Real-time Gameplay: it can facilitate real-time, on-chain gaming experiences.

In-game Asset Trading: Speedier and cheaper transactions could revolutionize how in-game assets are traded and monetized.

NFT Marketplaces

Cost-efficient Trades: Reduced transaction fees can potentially lower the barriers for trading NFTs, encouraging a more vibrant marketplace.

Fast Auctions: Quicker transaction times can facilitate real-time bidding wars and instantaneous auction results.

The Future of Arbitrum

Recent Developments

Strategic Partnerships: Many projects and platforms are beginning to integrate to leverage its advantages. Highlighting some key partnerships can showcase its growing influence.

Tech Upgrades: As with any technology, this layer 2 solution continues to evolve. Future updates might introduce even more optimizations and features.

Expected Growth and Adoption

Mainstreaming Layer 2: As more entities recognize the importance of Layer 2 solutions, Arbitrum's adoption is poised to grow exponentially.

Potential Beyond Ethereum: While currently focused on Ethereum, the technology behind this layer 2 solution has the potential to be adapted for other blockchains, broadening its horizons and influence.

As the blockchain ecosystem continues its march towards mainstream adoption, solutions like Arbitrum will be pivotal in addressing the challenges of today and shaping the decentralized platforms of tomorrow.

Conclusion - What is Arbitrum?

Arbitrum's introduction into the blockchain domain stands as a testament to the industry's drive towards innovation and optimization. As Ethereum continues to serve as a foundational layer for countless decentralized applications, the need for solutions like Arbitrum becomes ever more apparent. With its ability to drastically improve transaction speeds while concurrently slashing costs, Arbitrum not only addresses some of Ethereum's current limitations but also paves the way for a more scalable and cost-effective decentralized future. As we continue to push the boundaries of what's possible in the blockchain sphere, tools like Arbitrum will undeniably play a central role in shaping that journey.


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Applying Game Theory in Token Design

Kajetan Olas

16 Apr 2024
Applying Game Theory in Token Design

Blockchain technology allows for aligning incentives among network participants by rewarding desired behaviors with tokens.
But there is more to it than simply fostering cooperation. Game theory allows for designing incentive-machines that can't be turned-off and resemble artificial life.

Emergent Optimization

Game theory provides a robust framework for analyzing strategic interactions with mathematical models, which is particularly useful in blockchain environments where multiple stakeholders interact within a set of predefined rules. By applying this framework to token systems, developers can design systems that influence the emergent behaviors of network participants. This ensures the stability and effectiveness of the ecosystem.

Bonding Curves

Bonding curves are tool used in token design to manage the relationship between price and token supply predictably. Essentially, a bonding curve is a mathematical curve that defines the price of a token based on its supply. The more tokens that are bought, the higher the price climbs, and vice versa. This model incentivizes early adoption and can help stabilize a token’s economy over time.

For example, a bonding curve could be designed to slow down price increases after certain milestones are reached, thus preventing speculative bubbles and encouraging steadier, more organic growth.

The Case of Bitcoin

Bitcoin’s design incorporates game theory, most notably through its consensus mechanism of proof-of-work (PoW). Its reward function optimizes for security (hashrate) by optimizing for maximum electricity usage. Therefore, optimizing for its legitimate goal of being secure also inadvertently optimizes for corrupting natural environment. Another emergent outcome of PoW is the creation of mining pools, that increase centralization.

The Paperclip Maximizer and the dangers of blockchain economy

What’s the connection between AI from the story and decentralized economies? Blockchain-based incentive systems also can’t be turned off. This means that if we design an incentive system that optimizes towards a wrong objective, we might be unable to change it. Bitcoin critics argue that the PoW consensus mechanism optimizes toward destroying planet Earth.

Layer 2 Solutions

Layer 2 solutions are built on the understanding that the security provided by this core kernel of certainty can be used as an anchor. This anchor then supports additional economic mechanisms that operate off the blockchain, extending the utility of public blockchains like Ethereum. These mechanisms include state channels, sidechains, or plasma, each offering a way to conduct transactions off-chain while still being able to refer back to the anchored security of the main chain if necessary.

Conceptual Example of State Channels

State channels allow participants to perform numerous transactions off-chain, with the blockchain serving as a backstop in case of disputes or malfeasance.

Consider two players, Alice and Bob, who want to play a game of tic-tac-toe with stakes in Ethereum. The naive approach would be to interact directly with a smart contract for every move, which would be slow and costly. Instead, they can use a state channel for their game.

  1. Opening the Channel: They start by deploying a "Judge" smart contract on Ethereum, which holds the 1 ETH wager. The contract knows the rules of the game and the identities of the players.
  2. Playing the Game: Alice and Bob play the game off-chain by signing each move as transactions, which are exchanged directly between them but not broadcast to the blockchain. Each transaction includes a nonce to ensure moves are kept in order.
  3. Closing the Channel: When the game ends, the final state (i.e., the sequence of moves) is sent to the Judge contract, which pays out the wager to the winner after confirming both parties agree on the outcome.

A threat stronger than the execution

If Bob tries to cheat by submitting an old state where he was winning, Alice can challenge this during a dispute period by submitting a newer signed state. The Judge contract can verify the authenticity and order of these states due to the nonces, ensuring the integrity of the game. Thus, the mere threat of execution (submitting the state to the blockchain and having the fraud exposed) secures the off-chain interactions.

Game Theory in Practice

Understanding the application of game theory within blockchain and token ecosystems requires a structured approach to analyzing how stakeholders interact, defining possible actions they can take, and understanding the causal relationships within the system. This structured analysis helps in creating effective strategies that ensure the system operates as intended.

Stakeholder Analysis

Identifying Stakeholders

The first step in applying game theory effectively is identifying all relevant stakeholders within the ecosystem. This includes direct participants such as users, miners, and developers but also external entities like regulators, potential attackers, and partner organizations. Understanding who the stakeholders are and what their interests and capabilities are is crucial for predicting how they might interact within the system.

Stakeholders in blockchain development for systems engineering

Assessing Incentives and Capabilities

Each stakeholder has different motivations and resources at their disposal. For instance, miners are motivated by block rewards and transaction fees, while users seek fast, secure, and cheap transactions. Clearly defining these incentives helps in predicting how changes to the system’s rules and parameters might influence their behaviors.

Defining Action Space

Possible Actions

The action space encompasses all possible decisions or strategies stakeholders can employ in response to the ecosystem's dynamics. For example, a miner might choose to increase computational power, a user might decide to hold or sell tokens, and a developer might propose changes to the protocol.

Artonomus, Github

Constraints and Opportunities

Understanding the constraints (such as economic costs, technological limitations, and regulatory frameworks) and opportunities (such as new technological advancements or changes in market demand) within which these actions take place is vital. This helps in modeling potential strategies stakeholders might adopt.

Artonomus, Github

Causal Relationships Diagram

Mapping Interactions

Creating a diagram that represents the causal relationships between different actions and outcomes within the ecosystem can illuminate how complex interactions unfold. This diagram helps in identifying which variables influence others and how they do so, making it easier to predict the outcomes of certain actions.

Artonomus, Github

Analyzing Impact

By examining the causal relationships, developers and system designers can identify critical leverage points where small changes could have significant impacts. This analysis is crucial for enhancing system stability and ensuring its efficiency.

Feedback Loops

Understanding feedback loops within a blockchain ecosystem is critical as they can significantly amplify or mitigate the effects of changes within the system. These loops can reinforce or counteract trends, leading to rapid growth or decline.

Reinforcing Loops

Reinforcing loops are feedback mechanisms that amplify the effects of a trend or action. For example, increased adoption of a blockchain platform can lead to more developers creating applications on it, which in turn leads to further adoption. This positive feedback loop can drive rapid growth and success.

Death Spiral

Conversely, a death spiral is a type of reinforcing loop that leads to negative outcomes. An example might be the increasing cost of transaction fees leading to decreased usage of the blockchain, which reduces the incentive for miners to secure the network, further decreasing system performance and user adoption. Identifying potential death spirals early is crucial for maintaining the ecosystem's health.

The Death Spiral: How Terra's Algorithmic Stablecoin Came Crashing Down
the-death-spiral-how-terras-algorithmic-stablecoin-came-crashing-down/, Forbes


The fundamental advantage of token-based systems is being able to reward desired behavior. To capitalize on that possibility, token engineers put careful attention into optimization and designing incentives for long-term growth.


  1. What does game theory contribute to blockchain token design?
    • Game theory optimizes blockchain ecosystems by structuring incentives that reward desired behavior.
  2. How do bonding curves apply game theory to improve token economics?
    • Bonding curves set token pricing that adjusts with supply changes, strategically incentivizing early purchases and penalizing speculation.
  3. What benefits do Layer 2 solutions provide in the context of game theory?
    • Layer 2 solutions leverage game theory, by creating systems where the threat of reporting fraudulent behavior ensures honest participation.

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


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.


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.