Common Mistakes in Tokenomics - Tokenomics Design Course (Part 3)

9 Biggest Mistakes in Tokenomics Design

Introduction to Tokenomics Mistakes

• This video discusses the nine major mistakes builders make regarding tokenomics, emphasizing that the content is for educational purposes only and not legal or financial advice.

• The focus will be on avoiding these mistakes while going through a seven-step process for designing tokens. Previous videos covered best practices to consider during this process.

Key Mistakes in Tokenomics

1. Not Knowing Why You Need a Token

• Builders often launch tokens without understanding their purpose, similar to starting a company just to be an entrepreneur. There are significant costs and downsides involved in launching a token.

• Development takes longer than anticipated, and once launched, developers face pressure from community members about features and price changes that may be out of their control. A clear problem-solving rationale is essential before launching a token.

2. Not Planning Ahead for a Token

• Launching a product first and then introducing a token can work but requires foresight into how the token will enhance the product post-launch. It’s crucial to consider how it benefits holders and rewards contributors from the outset.

• An example cited is Uniswap, which released its product without planning for its token, resulting in missed opportunities for revenue capture compared to other AMMs like Curve Finance that distribute revenues effectively to holders.

3. Not Knowing What Type of Token You're Issuing

• Builders must honestly assess what type of utility their token provides rather than claiming it as a means of exchange or store of value without justification; most tokens serve specific functions rather than broad uses like Bitcoin or Ethereum do.

• Misunderstanding this can lead to launching tokens with unrealistic expectations about their market role, potentially harming both the project and its holders if they fail to deliver on those expectations.

4. Relying on Always Increasing Price

• Many projects mistakenly assume continuous price growth; however, even successful products experience slow growth periods which can lead to collapse if reliance on price increases is too strong (e.g., Terra and Steemit).

• Projects that depend solely on rising prices resemble Ponzi schemes rather than sustainable businesses; resilience against volatility is critical for survival in unpredictable markets.

5. Underestimating Collateral Risks

• Using collateral can be necessary (as seen with MakerDAO's DAI), but builders often underestimate associated risks when relying heavily on collateralized systems; failing to account for these risks can jeopardize project stability over time.

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Understanding Collateral Risks in Market Crashes

The Nature of Collateral and Market Conditions

• Collateral risks intensify during market crashes, contrary to normal conditions where they may appear manageable. Liquidity decreases significantly when collateral is most needed.

• Assets that are typically uncorrelated can become highly correlated during market downturns, reducing the expected diversification benefits.

Case Study: FTX and Correlation Issues

• The FTX example illustrates how collateral tied to a protocol (like the FTT token) can exacerbate problems when the protocol itself is underperforming, leading to a vicious cycle of dependency.

• In market crashes, market capitalization becomes a poor indicator of collateral value; selling large quantities often results in significant price slippage.

Misconceptions About Token Success

Product Usage vs. Token Value

• There’s a common misconception that increased product usage directly translates into token success. Without mechanisms for value capture, this assumption can be misleading.

• For instance, Uniswap's UNI token lacks intrinsic value accrual from protocol usage, relying instead on speculation.

High Token Velocity Concerns

• High token velocity—where tokens change hands frequently—does not necessarily correlate with an increase in token value or metrics.

Common Mistakes in Tokenomics

Focus on Supply Over Demand

• Many discussions around tokenomics focus solely on supply aspects like allocation and inflation rates while neglecting demand-side factors such as use cases and incentive mechanisms.

Importance of Modeling and Stress Testing

• Not conducting adequate modeling or stress testing is a critical oversight. Proper quantitative analysis helps ensure robust design parameters for protocols.

Regulatory Risks Ignored