Developing Blockchain Interoperability Solutions with Cosmos and Polkadot


02 Jun 2023
Developing Blockchain Interoperability Solutions with Cosmos and Polkadot

The development of blockchain interoperability solutions has taken center stage in the ongoing advancement of decentralized technologies. The limitations imposed by isolated blockchain networks have heightened the importance of interoperable systems, paving the way for increased collaboration and innovation. In this article, we delve into the creation of such solutions using Cosmos and Polkadot. With their distinctive approaches to achieving blockchain interoperability, these platforms facilitate smooth communication and information transfer among diverse chains. Harnessing the power of Cosmos and Polkadot presents an array of opportunities for businesses and developers within the decentralized domain.

Understanding Blockchain Interoperability Solutions:

The term "blockchain interoperability" denotes the capacity of various blockchain networks to interact and exchange data effortlessly. Conventional blockchain configurations operate in a standalone manner, leading to isolated ecosystems that impede cooperation and restrict innovative potential.

By instituting a framework that enables differing blockchains to communicate with one another, blockchain interoperability solutions seek to surmount these constraints. These solutions augment the effectiveness, expandability, and utility of decentralized applications by allowing data and asset exchanges between chains.

The absence of interoperability presents considerable obstacles for organizations and developers. Enclosed networks obstruct information flow, impede cross-chain transactions, and constrict the generation of substantial decentralized applications. Blockchain interoperability solutions tackle these issues by setting up standards, protocols, and infrastructure that support communication among diverse blockchain networks.

Multiple advantages arise from implementing blockchain interoperability solutions, such as heightened flexibility, superior scalability, augmented liquidity, and diversified use cases. These solutions pave the way for cooperative opportunities, enable smooth asset transitions between chains, and encourage the growth of harmonious decentralized ecosystems.

Cosmos and Polkadot: Pioneers in Blockchain Interoperability

Blockchain technology has been hailed as revolutionary, offering transformative potential across a multitude of industries. But as with any disruptive technology, achieving its full potential requires overcoming certain technical obstacles, chief among them being the issue of interoperability. This is where Cosmos and Polkadot come into the picture, as they are leading pioneers in promoting blockchain interoperability.

The Internet of Blockchains - Cosmos

Cosmos, often referred to as the "Internet of Blockchains", is a decentralized network of independent parallel blockchains, each powered by classical Byzantine Fault Tolerance (BFT) consensus algorithms like Tendermint.

It was designed from the ground up to solve the "hard" problems of the blockchain ecosystem, and interoperability stands at the forefront of these issues. To enable the seamless transfer of data and assets across different blockchains, Cosmos developed the Inter-Blockchain Communication (IBC) protocol. This protocol allows various blockchains in the Cosmos network, known as zones, to communicate with each other, thereby fostering an ecosystem of interoperability.

Polkadot: Enabling a Multichain Universe

Polkadot, on the other hand, is another innovative platform that is built to connect private and consortium chains, public and permissionless networks, oracles, and future technologies that are yet to be created in the Web3 ecosystem.

At the heart of Polkadot's interoperability solution is its multichain technology. This technology is underpinned by Substrate, a blockchain development framework, and it employs a number of unique components such as Parachains and the Cross-Chain Message Passing (XCMP) protocol. Polkadot's structure allows for multiple blockchains to interoperate while maintaining their own unique consensus algorithms and governance models.

In essence, both Cosmos and Polkadot are at the forefront of blockchain interoperability. They offer unique solutions to allow for seamless communication and transfer of data and assets across different blockchain networks. Developers interested in building cross-chain applications would do well to understand the strengths and capabilities of these pioneering platforms.

Developing Blockchain Interoperability Solutions: A Comparative Analysis

When it comes to developing interoperable blockchain solutions, both Cosmos and Polkadot are often the platforms of choice. While they share the common goal of connecting disparate blockchain networks, their approach, underlying technology, and features differ significantly. A comparative analysis of these two platforms can offer valuable insights for developers looking to leverage their capabilities for cross-chain applications.

Similarities between Cosmos and Polkadot

Despite their differences, Cosmos and Polkadot share several similarities in their approach to blockchain interoperability:

  • Shared Vision: Both platforms aim to create an internet of blockchains that can communicate and interact seamlessly with each other.
  • Security: Both Cosmos and Polkadot place a high priority on security, leveraging innovative consensus mechanisms and cryptography to ensure the security and integrity of transactions across blockchains.
  • Scalability: Both platforms are designed to address the scalability issues plaguing traditional blockchains. They achieve this by allowing multiple blockchains to operate concurrently, sharing the workload and improving the overall throughput of the network.
  • Governance: Both platforms have inbuilt governance mechanisms that enable network participants to propose and vote on changes to the network, fostering a democratic and decentralized ecosystem.

Differences between Cosmos and Polkadot

While they share similar goals, there are key differences in the design philosophy and architecture of Cosmos and Polkadot:

  1. Consensus Mechanisms. Both platforms use a form of Byzantine Fault Tolerance (BFT) for consensus, Cosmos uses Tendermint BFT. Polkadot uses a hybrid consensus mechanism combining elements of BFT and Proof-of-Stake (PoS).
  2. Communication Protocol. Cosmos uses the Inter-Blockchain Communication (IBC) protocol to facilitate communication between different blockchains. Polkadot, on the other hand, uses the Cross-Chain Message Passing (XCMP) protocol for inter-blockchain communication.
  3. Network Structure. Cosmos operates as a network of independent blockchains called zones, each powered by Tendermint BFT. Polkadot’s multichain network consists of a main relay chain and multiple parachains, each operating potentially different consensus mechanisms.
  4. Security Model. In Cosmos, each blockchain is responsible for its own security. Polkadot, however, follows a shared security model. The security of all parachains is pooled and maintained by the validators of the relay chain.

Understanding these similarities and differences can guide developers in choosing the right platform based on their specific requirements and objectives for interoperability. Both Cosmos and Polkadot offer powerful tools and frameworks for creating interoperable blockchain solutions, and the choice between them will often depend on the specifics of the use case at hand.

Practical Applications: Blockchain Interoperability Solutions in Action

Use Cases of Cosmos

Cosmos is a highly popular choice for developing decentralized applications (dApps) due to its scalability, modularity, and interoperability. Its architecture is designed to facilitate seamless cross-chain communication, making it ideal for a range of applications:

Decentralized Exchanges (DEXs): Cosmos is well-suited for building decentralized exchanges to support trading across multiple blockchains. The Gravity DEX, for instance, is a DEX built on the Cosmos network that allows users to trade tokens across different blockchains​1​.

Gaming: The scalability and modularity of the Cosmos network make it an ideal platform for blockchain-based games that require high performance and interoperability. ChainGuardian, a game built on the Cosmos network, allows players to battle each other using different characters and weapons​1​.

Cross-Chain Payments: The Cosmos network’s interoperability can facilitate cross-chain payments, allowing users to send and receive payments across different blockchain networks. This functionality reduces friction and increases efficiency in cross-border payments​1​.

Use Cases of Polkadot

Polkadot, on the other hand, offers developers a shared platform to create decentralized applications. It employs a combination of parachains, Proof of Stake protocols, and Virtual Machine-based technologies to address the scalability issues faced by other blockchains like Ethereum. Here are some of its notable use cases:

Interoperability Through Parachains: Polkadot's parachains enable other projects to build their networks and applications on Polkadot, allowing all these networks to interact with each other without the need for additional coding. Parachains are more customizable and give developers more flexibility than competitors like Ethereum. They are connected to the overall Polkadot infrastructure via a 'Relay Chain,' ensuring cross-chain interoperability through a set of robust governance protocols​2​.

Use in DeFi Platforms: Polkadot's parachains are also being used by decentralized finance platforms like Acala. Acala, the first parachain slot winner, acts as a liquidity pool from which Polkadot finances further projects within the network. This financing method is a crucial first step for Polkadot, as it creates launch momentum for even more projects​2​.

Connecting to Ethereum: Polkadot also enables seamless cross-chain operability with Ethereum, as evidenced by the second parachain slot winner, Moonbeam. Moonbeam acts as a bridge for Ethereum developers to extend the use of Ethereum Solidity code, Ethereum Virtual Machine, and its various other tools over to Polkadot. This integration expands the scope of Polkadot's cross-chain ambitions and provides a new level of connectivity between the two blockchains​2​.


The advancement of decentralized technologies is significantly supported by blockchain interoperability solutions, such as those provided by Cosmos and Polkadot. Known as the "Internet of Blockchains," Cosmos employs the IBC protocol to facilitate smooth communication between parallel blockchains. On the other hand, Polkadot utilizes its multichain technology, including parachains and XCMP protocol, to establish connectivity while preserving unique consensus and governance models.

Interoperability solutions have numerous advantages like flexibility, scalability, liquidity, and a wide range of use cases. Both Cosmos and Polkadot serve distinctive requirements; hence it is essential for developers to comprehend their differences.

Practical implementations encompass decentralized exchanges, gaming, and cross-chain payments provided by Cosmos, while Polkadot offers parachains, DeFi platforms, and Ethereum integration. Through embracing blockchain interoperability solutions like Cosmos and Polkadot, businesses and developers have the opportunity to foster collaborative innovation and construct powerful decentralized applications that will shape the future of decentralization.

Would you like to create your own project on blockchain and be an innovator in your industry? Contact us!

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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.


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 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.