ERC721 vs. ERC721A

Maciej Zieliński

29 Mar 2022
ERC721 vs. ERC721A

Technology can be a great solution for many businesses and companies. Unfortunately, one of the unfortunate side effects is the amount of various technical jargon, which may be unintelligible to the average person. For the end-user, NFT often means little more than a decentralized collectors' item or a work of digital art. You can enjoy this industry without understanding how it works. But the trends in blockchain technology can be fascinating even for those who are not involved with creating it. Why are ERC721 and ERC721A so important in NFT? What makes it special and why should we learn about this technology? We're writing about this below!

What is ERC721?

Although blockchain technology is decentralized, we need a common language which will allow us to understand the data contained within it. As such, token standards like ERC721 become essential. It is a standard which works in a similar way to how all ports or plugs on various devices work. It is worth noting, for example, that formats such as PNG i JPEG, which are commonly associated with NFT, are by themselves image standards.
ERC721 is an extremely popular token standard for creating non-fungible tokens – NFT – on blockchains, such as Ethereum and Polygon. The letter ‘E’ in ‘ERC721’ stands for ‘Ethereum’ and is not the NFT standard that runs on blockchains that are incompatible with Ethereum portfolios such as Solana and Tezos.

​What makes ERC721 compliant tokens useful?

Below we outline some of the advantages of this solution:

  • Each token is unique (previously mentioned non-fungibility)
  • Each token can be transferred or sold
  • Owners can authorize other smart contracts to manage tokens

In addition, each of them is crucial to ensuring that NFT markets, such as OpenSea and LooksRare, can operate as intended. It should be pointed out that smart contracts are simply applications that live within blockchain technology. Seems complicated? It can be described in an even simpler way: ERC721 is a standardized way of creating unique blockchain tokens, which can be traded at markets.

​What is ERC721A?

Software developers in crypto typically use existing code libraries to simplify the development process of a project. When you write a code that's in the blockchain, there's even more pressure to use a battle-proven, existing code wherever possible, because blockchain technology prevents any code editing! In the NFT sector, a single open source code was widely accepted in order to enable the use of ERC721. Then there was the “Azuki” project, which quickly gained recognition in the NFT sector. In addition to the NFT issue itself, the project has created a new implementation of ERC721A.
The implementation of ERC721A is not meant to change the token standard. Its main purpose is to fit the token perfectly, but this task requires a number of other standards to be met, as opposed to ERC721 which has been used to date.
This has led to the reduction of the amount of gas needed to mint new NFT (especially those that are minted in batches).
The gas costs incurred in transferring NFT based on ERC721A to other persons at the original owner's prices are slightly higher. Overall, the gas savings that ERC721A can provide compared to ERC721 are excellent, but this solution cannot be implemented everywhere. For example, entities that do not mint NFT in bulk will still spend a significant amount of gas if we consider the transfer costs.

Let us remember that NFT provides many limitless possibilities not only for art, music, or sports. It is important to know and understand ERC721 and ERC721A, as this allows us to understand what NFT really is from its very basics. This makes us more aware of the direction in which this sector is developing. It is worth noting that while both implementations are important, they are neither the first nor last elements of NFT. They are the benchmark to follow.

How does ERC721A work?

ERC721A adopts specific conditions which then affect the smart contract project. This impact makes the following things happen:

  • Token IDs should always grow steadily – starting from zero. Currently, many NFT projects fulfill this condition.
  • The reduction of the gas costs related to minting NFT is the most important part of NFT production.

With these assumptions, ERC721A makes the following optimization of contracts:

  • Reduces the unused space, which is used to store metadata from tokens.
  • Limits ownership to one coin from the entire NFT batch.

Why is ERC721A so important?

Because it allows us to understand how high the gas charges really are, and what they result from! Reducing your work to sending transactions saves energy. At this point, we should emphasize that blockchain generates 2 types of transactions – reads and writes.

  • Write – occurs when we are doing something in a blockchain and its condition changes (for example, we sell NFT).
  • Read – it can be said that this is a review of the transaction file.

Users who use blockchain technology incur higher write costs than read costs. Therefore, if we reduce the pool of write information or transaction transfer requirements, we will reduce the cost of minting NFT.

What risks are involved with using ERC721A contracts for generating multiple NFT transactions?

TransferFrom and safeTransferFrom transactions cost more gas, which means that NFT can cost more from the moment of its minting. We should emphasize that using ERC721A leads to an increase in performance without the need to set owners of particular token ID.

For example, in the picture below there are two calls to mint a batch, one by Marcus to mint chips #100, #101, and #102 in one call, and the other by Brutus to mint chips #103 and #104

The above diagram shows that ERC721A must set up the property metadata twice, instead of 5 times – once for the Marcus package and once for the Brutus package. This is not so easy because by transferring a tokenID that does not have an owner address, the contract must create actions that include all tokenID’s in order to verify the original NFT owner. This is because the original owner has the right to move the token and set it to a new entity. Below we present a graph associated with this:


The method of reading this chart is as follows: first move to the x-axis and then to the y-axis, for example:

  • „Mint a batch of 1 NFT, and then transfer tokenID 0”,
  • „Mint a batch 3 of NFT, and then transfer tokenID 1”
  • „Mint a batch 5 of NFT, and then transfer tokenID 4”

The above results indicate that moving token IDs in the middle of a larger mint batch (i.e. t1, t2) costs more than moving token IDs at the end of the batch (i.e. t0, t4).

How to minimize the cost of transferring an entire batch of NFT?

You can minimize costs if you are always minting the maximum allowed number of NFT when releasing an entire batch. In addition – when moving a batch, it is important to start a cycle with tokens of an ODD number in an ascending manner.
Examples of NFT projects using the ERC721A contract
Here is a list of projects, which are currently using the ERC721A contract:

  • @AzukiZen
  • @cerealclubnft
  • @TheLostGlitches
  • @standardweb3
  • @KittyCryptoGang
  • @XRabbitsClub
  • @WhaleTogether
  • @pixelpiracynft
  • @dastardlyducks
  • @MissMetaNFT
  • @StarcatchersNFT
  • @LivesOfAsuna
  • @richsadcatnft
  • @themonkeypoly
  • @womenofcrypto_
  • @TravelToucans
  • @HuhuNFT

Are ERC721A contracts still considered to be NFT transactions?

Of course. ERC721A contracts are NFT. Any contract that implements the ERC721 token standard, or the ERC1155 interfaces is seen as non-fungible or semi-fungible tokens. To put it simply, ERC721A is an extension and optimization of the previous version, the ERC721. The ERC721A contract is a very good idea which allows for saving money on gas in a given community, while at the same time protecting the Ethereum network from unnecessary workload.

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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.