1. The Core Idea

Every Web3 protocol is a system of incentives.

Users do not act randomly. They respond to:

• Rewards

• Risks

• Opportunities

  
  

Key Insight

2. What is Game Theory in Web3?

Game theory studies how participants make decisions based on incentives.

In Web3:

• Users seek maximum returns

• Protocols design reward structures

• Outcomes depend on collective behavior

  
  

Simple Principle

3. Types of Incentive Models

1. Emission-Based Incentives

How it works

• Tokens are distributed as rewards

• Users earn yield

  
  

Goal

• Attract users

• Bootstrap liquidity

  
  

Problem

• Creates inflation

• Encourages short-term behavior

  
  

2. Revenue-Based Incentives

How it works

• Rewards come from protocol revenue

• Users earn from real activity

  
  

Goal

• Align incentives

• Create sustainability

  
  

Advantage

• Long-term viability

  
  

3. Hybrid Models

How it works

• Combine emissions + revenue

  
  

Goal

• Early growth + later sustainability

  
  

4. Game Theory Dynamics

Cooperation vs Extraction

Protocols aim for cooperation:

• Users provide liquidity

• Users contribute value

  
  

Users often optimize for extraction:

• Maximize rewards

• Minimize risk

• Exit quickly

  
  

Insight

5. The “(3,3)” Concept

Popularized by Olympus DAO:

• If everyone cooperates → system grows

• If users defect → system collapses

  
  

Problem

In reality:

• Users act individually

• Not collectively

  
  

Result

• Cooperation fails

• Selling begins

  
  

6. Incentive Misalignment

Common Issue

Protocols reward behaviors that:

• Do not create value

• Extract value instead

  
  

Example

Liquidity mining:

• Users deposit funds

• Earn tokens

• Sell tokens

  
  

Outcome

• Short-term liquidity

• Long-term collapse

  
  

7. Sustainable Incentive Design

What Works

1. Value Creation

• Users contribute to the system

  
  

2. Aligned Rewards

• Rewards tied to real activity

  
  

3. Long-Term Incentives

• Encourage holding

• Encourage participation

  
  

Example

GMX:

• Rewards from trading fees

• Incentives aligned with usage

  
  

8. The Incentive Trap

High APY Systems

• Attract rapid growth

• Create unsustainable pressure

  
  

Cycle

1. High rewards attract users

2. Token supply increases

3. Selling pressure rises

4. Price drops

5. Users leave

   
   

Insight

9. Operator Framework

When evaluating incentive models, ask:

1. Where do rewards come from?

2. Are users contributing or extracting value?

3. What happens when rewards decrease?

4. Is behavior aligned with system growth?

10. Common Mistakes

Mistake 1

Assuming incentives guarantee success

Mistake 2

Ignoring token inflation

Mistake 3

Overvaluing short-term growth

11. Real Insight

12. Final Takeaway

Strong incentive models:

• Align user behavior with system growth

• Reward value creation

• Encourage long-term participation

  
  

Weak incentive models:

• Reward extraction

• Depend on emissions

• Collapse over time

  
  

The key question:

“Does this system reward the behavior it actually needs?”