Chainlink vs Polkadot


08 Feb 2024
Chainlink vs Polkadot

Chainlink aims to securely bridge the gap between blockchains and real-world data through its Decentralized Oracle network. On the other hand, Polkadot focuses on enabling different blockchains to transfer messages and value trust-free, enhancing interoperability. This article delves into the distinctions between Chainlink and Polkadot, shedding light on their purposes, technologies, and the potential impacts they have on the blockchain ecosystem.

What is Chainlink?


Chainlink is a decentralized oracle network designed to provide external data to smart contracts on any blockchain. Recognizing the limitation that smart contracts cannot natively access external data, Chainlink offers a solution by acting as a reliable bridge. Oracles in the Chainlink network collect and verify external data from various sources, ensuring the data's integrity before feeding it into smart contracts. This mechanism enables smart contracts to execute based on real-world events, data, and API information, which is crucial for the development of dynamic and responsive blockchain applications. Chainlink's key features include:

  • Decentralization. Ensuring data integrity and reducing reliance on any single point of failure by utilizing a network of independent node operators.
  • Security. Advanced cryptographic techniques and a robust reputation system safeguard the network against manipulation and ensure the reliability of data.
  • Flexibility. Compatibility with any blockchain allows seamless integration across diverse ecosystems.

Chainlink's use cases span across finance, insurance, gaming, and many other sectors, where access to accurate and timely external data is critical.

MUST READ: "What is Chainlink"

What is Polkadot?


Polkadot is a multi-chain framework that facilitates the cross-chain transfer of any data or asset types, not just tokens, thereby enabling interoperability among blockchains. It consists of a main network called the Relay Chain and multiple parachains are individual blockchains that connect to and secured by the Relay Chain. This unique architecture allows for a high degree of customization and scalability, as each parachain can be tailored to specific use cases or workloads while benefiting from the shared security of the Relay Chain.

Polkadot's key features include:

  • Interoperability. Enables different blockchains to communicate and transfer data or assets in a trust-free environment, opening up cross-chain applications and services.
  • Scalability. Parachains operate in parallel, allowing for significant scalability improvements over traditional blockchain architectures.
  • Shared Security. Parachains share the security model of the Relay Chain, ensuring that they benefit from a collective security mechanism rather than having to create their own.

The vision behind Polkadot is to create a fully interoperable and scalable web of blockchains, facilitating the seamless exchange of information and transactions across previously siloed networks. This approach not only enhances efficiency and scalability but also encourages innovation by allowing developers to focus on building specialized solutions on parachains.

MUST READ: "Polkadot – Blockchain to change the rules of the game?"

Chainlink vs Polkadot: Understanding the Differences

Purpose and Focus

Chainlink's Purpose

Chainlink focuses enhancing the functionality of smart contracts by providing them with access to real-world data. This is achieved through its decentralized oracle network, which ensures that the data smart contracts rely on for their execution is accurate and reliable. Chainlink's aim is to bridge the gap between the on-chain and off-chain worlds, enabling smart contracts to interact with external data feeds, web APIs, and traditional bank payment systems securely.

Polkadot, on the other hand, solves the problem of blockchain interoperability and scalability. Its unique multi-chain framework allows different blockchains to communicate and share information without sacrificing their sovereignty. By enabling the transfer of data and value between previously incompatible networks, Polkadot seeks to create a web of interconnected blockchains, facilitating a new level of interoperability and scalability.

Chainlink's Focus

Technology and Infrastructure

Chainlink's infrastructure revolves around its decentralized network of oracles, which independently collect, verify, and deliver external data to blockchain smart contracts. This setup ensures that the data is not only accurate but also resistant to manipulation, providing a secure and trustworthy environment for smart contracts to operate in.

Polkadot's architecture is based on a central Relay Chain and multiple parachains (parallel chains). The Relay Chain is responsible for the network's shared security, consensus, and interoperability, while parachains are individual blockchains that can have their own tokens and be optimized for specific use cases. This design allows for a high degree of customization and scalability across the Polkadot network.

MUST READ: "Developing Blockchain Interoperability Solutions with Cosmos and Polkadot"

Use Cases - Chainlink vs Polkadot

Chainlink's oracles are critical for any application that requires real-world data to trigger smart contract execution. This includes, but is not limited to, decentralized finance (DeFi) platforms that need up-to-date price feeds, insurance contracts that depend on real-world events, and gaming platforms that utilize external data for in-game mechanics.

Polkadot focuses on enabling different blockchains to work together seamlessly. Its use cases are broad and include cross-chain transfers of data or assets, interoperable applications that can operate over multiple blockchains, and the creation of new types of services that leverage the strengths of various networks without being limited by the weaknesses of any single chain.

Chainlink vs Polkadot

SecuritySecures data pipeline with decentralized oracles and cryptographic proofs.Shared security model through the Relay Chain, benefiting all parachains.
ScalabilityEnhances application scalability by off-chain data interaction.Handles high transaction volumes with parallel processing of parachains.
GovernanceDecentralized governance involving community, node operators, and Chainlink team.On-chain governance model allowing token holder proposals and voting.
AdoptionWidespread in DeFi and various industries for real-time data needs.Adopted for diverse use cases across its growing number of parachains.
EcosystemComprises independent node operators, data providers, and developers.Includes projects developing on parachains, infrastructure providers, and a supportive community.
Chainlink vs Polkadot


  • Chainlink emphasizes securing the data pipeline between external data sources and blockchain smart contracts. It uses a decentralized network of oracles to prevent single points of failure and ensure data integrity.
  • Polkadot focuses on the security of its multi-chain architecture through shared security. This means that all parachains benefit from the collective security of the Polkadot network, provided by the Relay Chain. This shared security model ensures that individual blockchains do not need to establish their own security measures, which can be resource-intensive and less effective.


  • Chainlink makes smart contracts smarter. It connects them to the real world without slowing down. This means more complex apps can run smoothly.
  • Polkadot uses many chains at once. It’s like opening more lanes on a highway. This lets more data flow quickly. Each chain does its part, keeping things fast.


  • In Chainlink, decisions come from many. The community, those running nodes, and the Chainlink team all have a voice. This way, changes benefit everyone.
  • Polkadot's governance is hands-on. Token holders vote on proposals. They shape Polkadot's future directly. It’s democracy in action, ensuring the network evolves as a true community.

Chainlink vs Polkadot - Conclusion

Chainlink and Polkadot are at the forefront of blockchain innovation, each serving distinct yet complementary roles. Chainlink's secure data integration expands the utility of smart contracts, while Polkadot's focus on interoperability and scalability fosters a more connected blockchain ecosystem. Their unique approaches contribute significantly to the blockchain community, driving growth and attracting a wide range of stakeholders.

If you are interested in utilizing Chainlink or other blockchain-based solutions for your project, please reach out to


How does Chainlink ensure data reliability for smart contracts?

  • Chainlink employs a decentralized oracle network to verify external data before feeding it into smart contracts.

What's the architectural difference between Chainlink and Polkadot?

  • Chainlink uses a network of oracles, whereas Polkadot consists of a Relay Chain and parachains for shared security and scalability.

What additional use cases can Chainlink and Polkadot serve?

  • Chainlink: Supply chain verification, weather insurance, prediction markets.
  • Polkadot: Cross-border payments, IoT device connectivity.

How do Chainlink and Polkadot handle governance?

  • Chainlink involves community, node operators, and the Chainlink team.
  • Polkadot employs on-chain governance, allowing token holders to vote on proposals directly.

More about this Topic on Nextrope Blog

  1. What is Chainlink?
  2. NFT and Gaming: Chainlink Use Cases
  3. Chainlink in DeFi: Use Cases
  4. Chainlink vs. Avalanche: Exploring the Blockchain Frontier
  5. Authorization and Identity: Chainlink Use Cases
  6. Chainlink and On-Chain Finance Use Cases


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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.