Building Decentralized Oracles: A Comprehensive Guide for Developers


01 Jun 2023
Building Decentralized Oracles: A Comprehensive Guide for Developers

In the realm of blockchain technology, decentralized oracles play a crucial role by facilitating secure and trustworthy connections between real-world data and blockchain networks. Acting as a conduit, these oracles enable the seamless integration of off-chain information into decentralized applications (DApps) and smart contracts. Utilizing such oracles allows developers to expand on the potential of blockchain technology by tapping into verifiable and resistant data from a variety of sources. We will delve into the complexities of constructing decentralized oracles in this guide, addressing their advantages, obstacles, recommended approaches, and available frameworks for crafting inventive blockchain solutions.

Understanding Oracles in the Blockchain Context

Understanding Oracles

Specialized systems known as oracles facilitate the connection between blockchain networks and external data sources. Serving as intermediaries, they supply off-chain data to on-chain applications like smart contracts and DApps, allowing blockchain applications to access real-world information, events, and data feeds securely and reliably.

Types of Oracles

Centralized Oracles:

When it comes to providing data inputs for blockchains, centralized oracles depend on a single authority or entity. Though their implementation is relatively simple, they create a single point of failure and potential vulnerabilities, which can compromise the data's trustworthiness and security.

Decentralized Oracles:

In contrast, decentralized oracles use the principles of blockchain technology to offer a more secure and dependable method. They distribute the tasks of data retrieval, validation, and aggregation among multiple participants to ensure consensus while minimizing manipulation or tampering risks. Decentralized oracles enhance trust and verifiability in blockchain applications.

Decentralized oracles are prominent due to their capability to deliver reliable and tamper-proof data inputs that align with the core concepts of decentralization and trustlessness in blockchain technology. By comprehending the various oracle types and their implications, developers can make well-informed decisions when incorporating oracles into their blockchain endeavors.

Components of a Decentralized Oracle

A decentralized oracle is not a simple, single entity, but rather a combination of several components that work together to connect blockchain-based smart contracts with the external world. Understanding these components is vital for any developer who wishes to construct a decentralized oracle. Let's delve into the core components:

Oracle Node

Oracle nodes are the workhorses of a decentralized oracle network. They are responsible for retrieving and validating real-world data from external data sources. Oracle nodes are also responsible for reporting the retrieved data back to the blockchain. A decentralized oracle network includes multiple oracle nodes to ensure data accuracy and prevent manipulation.

Data Providers

Data providers are the external sources from which oracle nodes retrieve the necessary real-world information. They can be anything from APIs of web services, data feeds, databases, to IoT devices. The choice of data providers is critical as they directly affect the accuracy and reliability of the data used in smart contracts.

Aggregation Contract

Once oracle nodes retrieve and validate data, it must be processed and formatted in a way that's useful for the smart contract requesting the data. This is where the aggregation contract comes in. It takes the data from multiple oracle nodes, processes it (often by calculating a median or average), and then feeds the aggregated data to the requesting smart contract.

Reputation System

In a decentralized oracle network, a reputation system is typically used to incentivize honest behavior and discourage malicious activity. Oracle nodes are rewarded or penalized based on their performance. Nodes that consistently provide accurate and timely data are rewarded, while those found to be unreliable or dishonest are penalized.

Request and Response Model

The request and response model is a core component of how a decentralized oracle functions. When a smart contract needs data from the outside world, it sends a request to the oracle. The oracle nodes then fetch the required data from the chosen data providers, validate it, and send it back to the smart contract.

Security Mechanisms

Security is a paramount concern for any component interfacing with a blockchain. Decentralized oracles often incorporate various security measures to protect against attacks. These might include cryptographic proofs for data integrity, multi-signature confirmations for critical transactions, and secure data transmission protocols.

In summary, building a decentralized oracle involves constructing and connecting these components in a way that ensures the reliable, secure, and timely delivery of real-world data to smart contracts. Each component plays a crucial role in the overall functioning of the decentralized oracle. Understanding these components and their interactions is a prerequisite for creating a robust decentralized oracle.

Building a Decentralized Oracle - The Process

Creating a decentralized oracle is a challenging but rewarding process. It involves careful planning, thoughtful design, meticulous coding, rigorous testing, and effective deployment. Here is a step-by-step guide to building a decentralized oracle. 

Step 1: Setting up the Environment

The first step in building a decentralized oracle is setting up the development environment. This typically involves:

  • Choosing a blockchain platform: The choice of blockchain platform depends on various factors like the target audience, security requirements, scalability needs, and the type of data to be handled. Ethereum is a popular choice due to its extensive developer support and robust smart contract capabilities, but other platforms like Binance Smart Chain, Polkadot, or Cosmos might be more suitable depending on your specific needs.
  • Setting up the development tools: Depending on the chosen blockchain platform, you will need to install and configure the appropriate development tools. For Ethereum, this would include tools like Truffle, Ganache, and the Solidity programming language.

Step 2: Developing the Oracle Smart Contract

The next step is to write the oracle smart contract. This contract will handle requests from other contracts, fetch data from the external world, and return the retrieved data. This process involves:

  • Designing the contract: Before you start coding, you should design the contract's interface and determine how it will interact with other contracts and external data sources.
  • Writing the contract: Using your chosen programming language (such as Solidity for Ethereum), write the smart contract code. Be sure to follow best practices for security and efficiency.
  • Debugging: Debugging is a critical part of the development process. Test your contract thoroughly to ensure it behaves as expected and doesn't contain any vulnerabilities.

Step 3: Integrating Data Providers

Once your oracle smart contract is ready, you'll need to connect it to external data providers. This involves:

  • Selecting data providers: Choose reliable and accurate data providers that can supply the type of data you need. This could be anything from financial data feeds, weather APIs, IoT devices, or other web services.
  • Writing the integration code: Write the necessary code to fetch data from your chosen data providers and feed it into your oracle contract.

Step 4: Testing and Deploying the Oracle

The final step is to test your oracle thoroughly and then deploy it on your chosen blockchain. This includes:

  • Testing: Conduct thorough testing to ensure that your oracle works correctly and securely. This should include unit tests, integration tests, and stress tests. Consider using testing frameworks and tools to automate this process.
  • Deployment: Once you're confident that your oracle is ready, deploy it on the blockchain. Be sure to follow best practices for contract deployment, and consider using a deployment tool to make the process easier and more reliable.
  • Building a decentralized oracle is a complex but rewarding process. By following these steps, you'll be well on your way to creating a powerful tool that can bridge the gap between the blockchain and the outside world.

While it's entirely possible to build a decentralized oracle from scratch, leveraging existing oracle platforms can significantly ease the development process. These platforms offer tools, services, and frameworks that simplify the creation of secure, reliable, and efficient decentralized oracles. Let's explore some popular platforms:

Chainlink is one of the most well-known and widely used decentralized oracle platforms. It provides a flexible framework for connecting smart contracts with real-world data, APIs, and other off-chain resources. Developers can use Chainlink to create custom oracle networks, choose their own data sources, and define aggregation strategies.

Band Protocol

Band Protocol offers a decentralized data oracle that allows smart contracts to access external data in a secure and scalable manner. The Band Protocol is known for its efficient design, which reduces the amount of data stored on-chain, leading to faster transactions and lower costs.

Provable (formerly Oraclize)

Provable provides reliable oracle services for various blockchains, including Ethereum, Bitcoin, and EOS. It focuses on data transport, authenticity proofs, and easy integration. Provable's technology allows developers to fetch data from any web API, ensuring a wide range of potential use cases.

Challenges and Potential Solutions

Building decentralized oracles comes with a set of unique challenges. Here are some of the most common ones, along with potential solutions:

Data Accuracy and Reliability

Challenge: Ensuring the accuracy and reliability of data from external sources

Solution: Using multiple data sources for cross-verification and choosing reputable and reliable data providers. Implementing a consensus mechanism for data validation can also help.

Timeliness of Data

Challenge: Providing real-time or near-real-time data to smart contracts, as fetching data from external sources can introduce latency

Solution: Optimizing the data retrieval process, using fast and reliable data providers, and implementing predictive algorithms to anticipate future data needs.


Challenge: Protecting against potential attacks such as man-in-the-middle attacks, Sybil attacks, or direct attacks on the data source

Solution: Implementing robust security measures like cryptographic proofs for data integrity, secure data transmission protocols, and utilizing additional security services from oracle platforms, if available.

Complexity of Development

Challenge: Navigating the complex process of building a decentralized oracle, which requires deep knowledge of blockchain technology and the specific oracle platform

Solution: Leveraging existing oracle platforms that offer tools and frameworks to simplify the development process, and utilizing educational resources and developer communities around these platforms.

Despite these challenges, with the right approach and tools, it's entirely possible to build effective and secure decentralized oracles to bridge the gap between blockchain networks and the real world.


Decentralized oracles play a crucial role in connecting blockchain networks with real-world data, facilitating secure and dependable interactions. By leveraging these oracles, developers can tap into verified data from diverse sources, extending blockchain technology's reach across numerous sectors. In this exhaustive guide, we have delved into the concept of oracles, making a distinction between centralized and decentralized varieties while shedding light on their advantages and drawbacks. Additionally, we have explored the fundamental elements of a decentralized oracle, the procedure for constructing one, and well-known platforms that streamline oracle development. Equipped with this information, developers can seamlessly incorporate decentralized oracles into their blockchain ventures, uncovering new potential and transforming how blockchain engages with the real world.


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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.