Ending the Zero-Sum Game: An In-Depth Research Report on Web3 Incentive Engineering and Odyssey Behavioral Dynamics

1. Preface — The “Singularity” of Odyssey

Web3 incentive mechanisms are at a pivotal moment, transitioning from the “traffic illusion” back to the “essence of value.” Over the past few years, the Odyssey model has experienced peaks and bottlenecks. We have found that simple replication of the pattern no longer stirs ripples in the overloaded information chain world.

1.1 Paradigm Shift: Why Do Most Odyssey Projects Yield Little?

Although the Odyssey model has created many wealth-building myths, by 2026, developers have realized that merely copying top projects is unlikely to generate a “breakout effect.” The core issue is a deep disconnect between incentive logic and user ecosystems.

• Increased Incentive Entropy Causes Homogenization and Internal Competition
  When 90% of projects demand users to repeatedly “cross-chain, stake, share” to earn nearly identical “Points,” the marginal returns on user attention plummet. This mimicry leads to rising incentive entropy—the scarcity of rewards is diluted by countless homogeneous projects. For example, in Linea’s “The Surge” and subsequent L2 point wars, users find themselves moving liquidity across dozens of similar protocols, only to receive shrinking inflationary points. Fatigue turns into apathy, and incentive effects are exhausted in endless internal competition.

• Lack of Game Mechanics and “Witch-Hunt” Growth Creates Fake Prosperity
  Many projects only learn the superficial “task wall” but ignore the deeper anti-witch game theory, resulting in most incentives being siphoned off by professional farms using automation scripts. The experience of zkSync Era is a warning: despite over 6 million active addresses on paper, data reveals most are automated interactions for arbitrage. This “paper prosperity” caused governance crises during TGE and, more critically, 90% of addresses went to zero after airdrops. Projects paid high customer acquisition costs but failed to build real ecosystems.

• Disconnection Between Product Logic and Incentive Interaction Makes Participation Mechanical
  Breakout effects often stem from deep coupling between core product features and reward mechanisms. If Odyssey tasks become unrelated “on-chain labor” (e.g., privacy protocol users shouting on Twitter), users cannot develop brand loyalty. Early projects that forcibly bundled social tasks on platforms like Galxe attracted tens of thousands of followers, but this “misaligned demand” drew low-net-worth task hunters. Larger capital users, annoyed by Web2-style forced interactions, left. Once tasks end, TVL often crashes within 24 hours, unable to generate emotional resonance or competitive barriers.

1.2 Defining Win-Win: Protocol Unit Economics

To break the deadlock of “poor results,” a win-win logic must shift from “buy traffic” to “build ecosystems.” We need to find a balance mathematically:

1.2.1 Marginal Unit Revenue at the Protocol Level
Project teams should realize that the essence of Odyssey is precise customer acquisition cost (CAC):

Unit Margin = LTVuser − CACincentive

Only when the long-term fees, liquidity stickiness, or governance contributions (LTV) generated within the protocol exceed the rewards (Incentive) does Odyssey evolve from mere “money printing” to sustainable capital expansion.

1.2.2 Total Utility Capture for Users
Future Odyssey participants will become more rational. Instead of chasing “potentially zero” points, they will calculate comprehensive returns:

• Airdrops: Immediately liquidatable token shares.
• Utility: Long-term rights within the protocol (e.g., lifetime fee discounts, RWA income shares).
• Reputation: On-chain credit assets, the core credential for access to top-tier projects in the future.

1.3 Core Assumption: Incentives Are More Than Tokens — They Are Credit, Privileges, and Revenue Rights

In deep incentive design, we overthrow the old assumption that “ERC-20 tokens are the sole driver.” A successful Odyssey must have value support across three dimensions:

• Credit (Identity)
  Binding user contributions permanently via Soulbound Tokens (SBT) or on-chain identity systems. Credit is more than a badge; it’s an efficiency multiplier: high-credit users can unlock “no-deposit loans” or “task weight bonuses,” giving genuine contributors advantages over scripts.

• Privileges (Utility)
  Embedding rewards into product usage rights. For example, Odyssey winners could earn “veto power medals” in governance or priority access to new projects within the ecosystem. Privileges turn transient users into long-term holders.

• Revenue Rights (RWA)
  As compliance advances, the most attractive Odyssey projects in 2026 will incorporate underlying revenue-sharing logic. Rewards are no longer just inflationary air but anchored to real income streams (e.g., RWA bonds, DEX fee shares). This real yield injection is the ultimate card for projects to stand out and truly break through.

2. Spectrum of User Behavior: From “Profit Seekers” to “On-Chain Citizens”

In future on-chain ecosystems, the traditional definition of “users” dissolves. With chain abstraction and AI agents becoming prevalent, the “soul” (or algorithm) behind addresses shows high differentiation. Understanding this spectrum is key to designing win-win incentive mechanisms.

2.1 User Layering Model: Deep Portrait Based on Motivation and Contribution

We categorize Odyssey participants into three representative Greek-letter tiers, based on behavioral entropy and protocol loyalty, not just TVL.

2.1.1 Player Tiers

Gamma — Arbitrageurs (AI Bounty Hunters)

• Role: Pursuing maximum efficiency.
• Motivation: Purely rational. They care little about project vision; their only reference points are “risk-free rate” and “certain returns.”
• Behavior: Script-driven, low-latency interactions, often in gas fee valleys. Their paths are highly standardized and homogeneous.

Beta — Explorers (Hardcore Users)

• Role: Deep ecosystem participants.
• Motivation: Resonance-driven. They value product depth, community identity, and long-term rights.
• Behavior: Engage in deep beta testing, pride in earning rare badges (SBT). They provide high-quality feedback, with personal and subjective interaction patterns.

Alpha — Builders (Ecosystem Pillars)

• Role: Core supporters and stakeholders.
• Motivation: Sovereignty-driven. They seek long-term governance rights, dividends, and a secure moat.
• Behavior: Large, long-term lockups, submitting core proposals, running validators. As noted, “They produce no noise, only credit.”

2.1.2 Behavioral Traits and Quantitative Models

• Gamma’s Survival Law: Cold cost estimation
  For Gamma arbitrageurs, Odyssey is a game of precise calculation. They ignore project vision, focusing solely on capital efficiency per unit time.

• Alpha’s Moat Effect: Power dynamics
  Alpha players disdain social media likes; their Odyssey contribution is sovereignty. Their large asset holdings and node operations determine the protocol’s market cap ceiling and resilience.

2.1.3 Identity Collapse and “Consensus Alchemy”
Identity is not static but a dynamic spectrum. In well-designed Odyssey systems, user identity can undergo “quantum leaps”:

• From “Arbitrage” to “Exploration”: A Gamma user initially motivated by profit may, through deep interaction, be moved by excellent product experience or robust logic. When long-term gains surpass immediate profits, they experience “identity collapse” — shifting from “profit-taker” to “deep holder.”
• Project “Consensus Capture”: This is essentially a form of “alchemy” by the project. Low-quality projects only attract arbitrageurs, eventually collapsing as incentives fade; high-quality projects generate centripetal force, turning bounty hunters into “guardians.”

Key insight: Incentive mechanisms are no longer rigid divide-and-conquer tools but a process of screening, filtering, and transformation. They recognize Gamma’s value but aim to leverage incentives to induce users to evolve from profit-driven retail to value partners.

2.2 Behavioral Heatmap Analysis: Nonlinear Paths of Mainstream Layer 2 Tasks

Before 2024, Odyssey task paths were linear (e.g., follow Twitter → cross-chain → swap). But future designs centered on “intent” will produce heatmaps with significant nonlinear, network-like features.

2.2.1 From “Task-Driven” to “Intent-Driven” Pathways
Data from Arbitrum, Optimism, and Base shows:

• Path Uncertainty: The same Odyssey task can be completed via different routes—e.g., user A via “lending → staking → mint,” user B via “aggregator → auto-strategy pool.”
• Cross-Chain Hotspots: Behavior is no longer confined to a single chain. Actions on Layer 2 often trigger immediate feedback on Layer 3 specialized chains. For example, after 10 minutes of Layer 2 interaction, heatmaps show users triggering auto-reward scripts on related AI chains.

2.2.2 Behavioral Entropy Distribution
Data indicates high-quality users (Beta and Alpha tiers) exhibit higher “complex entropy” in heatmaps.

• Gamma — Arbitrageurs: Highly mechanical, with interactions concentrated in minimal loops, short and repetitive paths.
• On-Chain Citizens: Dispersed and long-tail, exploring secondary pages, reading on-chain documents, or interacting with other dApps.

Insight: The most successful Odyssey projects have heatmaps that resemble a gravitational field, attracting users to stay within the ecosystem for “unplanned” interactions after completing initial tasks.

Users no longer see themselves merely as “wallet addresses.” In Odyssey 3.0, the end of the behavioral spectrum is “On-Chain Citizenship,” representing not just rewards but a form of identity endorsement across multiple chains.

3. Mechanism Design: Ensuring “Win-Win” with Mathematical Models and Game Balance

Early Web3 Odyssey projects often fell into “Ponzi deadlocks,” trading future inflation for short-term false prosperity. Escaping this cycle requires incentive compatibility—ensuring that users’ pursuit of self-interest aligns with the protocol’s long-term health through rigorous mathematical modeling.

3.1 Incentive Compatibility Equation (The IC Constraint): Rebuilding Cost-Reward Game

In traditional airdrops, Sybil attacks have near-zero marginal cost. To protect genuine contributors, future Odyssey designs incorporate game-theoretic IC constraints.

Core Game Model:
Let R© be the total reward for honest, genuine interaction, and C© the associated costs (gas, slippage, capital lock-up).
Let E[R(s)] be the expected reward for a Sybil attacker using automation scripts, and C(s) the attack cost (servers, IP pools, detection algorithms, sunk costs).

Achieving Nash Equilibrium for Win-Win:
The system must satisfy:

C(s) ≥ E[R(s)] — Attack costs outweigh gains, deterring malicious scripts.
Simultaneously, R© must be attractive enough to incentivize honest participation.

Evolution and Intervention in the 2.0 Era:

1. Increase C(s) (attack resistance):
   Implement AI-based behavioral entropy detection, analyzing interaction timing, fund flow entropy, and “human-like” patterns. Suspicious accounts face dynamic gas penalties, destroying script profitability.

2. Optimize R© (reward structure):
   Shift from pure governance tokens to “hybrid rights packages,” including:

• Cash flow rights: share of protocol fees (Real Yield).
• Privilege assets: permanent fee discounts or cross-protocol interest bonuses.
• Governance leverage: weightings for long-term holders, turning participation into power.

3.2 Dynamic Difficulty Adjustment (DDA)

Future Odyssey projects will adopt a dynamic difficulty mechanism, inspired by Bitcoin’s adjustment algorithm.

Logic:
When total addresses and TVL surge rapidly, the system detects “overheating” and automatically raises difficulty:

• Funding Thresholds: Higher amounts of liquidity or longer lock-up periods are required for equivalent points.
• Task Complexity: Transition from simple swaps to multi-protocol strategies (e.g., lending, staking, hedging).

Win-Win Effect:

• Protocols: DDA acts as a safety valve, preventing liquidity crashes caused by speculative surges.
• Alpha Citizens: It filters out “wool hunters,” ensuring rewards flow to genuine, high-net-worth users.

3.3 Proof of Value (PoV) Model

In Odyssey 3.0, “address count” becomes a vanity metric. Projects shift to a PoV model centered on contribution density:

Contribution Density Formula:
D = ∑(Liquidity × Time) + γ × Governance_Activity / Total_Reward

• Liquidity: Duration funds are locked in the ecosystem.
• γ: Community contribution factor, boosting rewards for active governance, documentation, or positive social impact.
• Total Rewards: Normalization denominator to control inflation.

Win-Win Deep Dive:
PoV yields a map of genuine ecosystem participants, not just wallet addresses. Users’ labor and engagement, amplified by γ, lead to higher returns, harmonizing capital efficiency with human creativity. This ensures Odyssey becomes a true value co-creation process rather than a mere “digital game.”

4. Underlying Technology: Behavior-Aware Zero-Knowledge Incentive Protocols

In future paradigms, Odyssey evolves from a front-end “task wall” to an underlying protocol that automatically captures, analyzes, and transforms user behavior via ZK tech and chain abstraction, creating a closed loop from behavior perception to precise incentives.

4.1 Behavior Sensing Engine: From “Passive Check-in” to “Full-Chain Behavior Tracking”

This protocol functions as a chain data crawler and indexer, recording deep interactions without manual input:

• Multi-Dimensional Behavior Modeling:
  Real-time capture of liquidity flows, transaction frequency, governance participation, and even on-site dwell time (via zk proofs).
• Dynamic Weighting:
  Analyzing these behaviors to classify users as “long-term holders,” “high-frequency liquidity providers,” or “deep governance participants,” turning mechanical tasks into behavior medals.

4.2 ZK-Proof Driven Privacy Analysis and Filtering

Post data collection, the protocol employs ZK proofs to verify user attributes without revealing PII:

• ZK Credentials: Users can prove high-net-worth or active governance participation without exposing assets or identities.
• Anti-Witchcraft Measures: Set thresholds (e.g., 180-day non-repetitive interactions) verified via ZK-STARKs, generating “unique human proofs” that lock out automation scripts, ensuring incentives flow only to genuine high-quality actors.

4.3 Intent-Centric Chain Abstraction Incentives

The protocol records behavior and simplifies participation via an intent engine:

• Intent-Driven Automation: Users express “I want to participate in this liquidity incentive,” and the system automatically manages cross-chain transfers, gas balancing, and contract calls.
• Instant Conversion & Win-Win: Seamless, “perception-free” interactions increase conversion rates; projects capture authentic user intent, restoring product value to the core.

5. Future Evolution — From “Marketing Campaigns” to “Persistent Incentive Protocols”

Future Odyssey will shed “time-limited” features, evolving into a protocol-native, always-on growth layer.

5.1 Embedded Incentives (GaaS: Growth-as-a-Service)

Odyssey becomes embedded in smart contracts, with dynamic reward logic:

• Evolution: As users generate positive value (reducing slippage, providing long-term liquidity), contracts automatically recognize and distribute rewards, turning Odyssey into an “autonomous driving” mode.

5.2 Cross-Protocol “Credit Lego” (Interoperable Incentives)

Odyssey points will become portable. Performance in A’s Odyssey can be proven via ZK to unlock initial status in B’s social protocol.

• Ultimate Form: A universal “on-chain contribution score” across ecosystems replaces fragmented points, fostering a Web3 from “inter-ecosystem fragmentation” to “incremental co-creation” and a true global on-chain republic.

6. Practical Playbook (The Executive Guide)

Odyssey is no longer a “drop and run” money-printing game but a precise ecosystem growth and capital consolidation project. Success hinges on balancing “traffic explosion” with “system resilience.” Here are 10 key principles and operational frameworks:

6.1 Paradigm Shift in Core KPIs: From Vanity to Hardcore

Avoid being misled by Twitter followers or address counts. In an era where intent engines can simulate millions of addresses cheaply, these metrics are easily faked.

• Indicator A: Sticking TVL (sticky funds ratio):
  Retention Ratio = TVL T+90 / Peak TVL
  If below 20%, the incentive design is flawed.

• Indicator B: Net Contribution Score:
  Total protocol fees generated by an address divided by its incentive cost.

• Indicator C: Governance Activity Entropy:
  Measures genuine participation depth in snapshots or on-chain proposals, not just voting volume.

6.2 Modular Task Design: Building a Laddered Funnel

Top Odyssey projects often adopt a “three-tier” architecture to convert massive traffic into core citizens.

Basic Layer (L1) — Icebreaker & Reach

• Target: Newcomers / Web3 novices
• Core Tasks: Simple interactions (swap, share)
• Incentives: SBT badges, future airdrop points
• Retention: Minimize barriers, establish first touchpoints via SBTs, leaving digital footprints.

Growth Layer (L2) — Liquidity Engine

• Target: Active traders / LPs
• Core Tasks: Deep liquidity provision, position management, cross-chain staking
• Incentives: Protocol tokens, fee discounts
• Retention: Yield maximization, increasing opportunity costs of withdrawal.

Ecosystem Layer (L3) — Core Sovereignty

• Target: Key contributors / developers / governance reps
• Core Tasks: Write docs, submit code, propose governance
• Incentives: Governance weight, RWA dividends, whitelist access
• Retention: Grant “citizenship,” long-term stake, making contributors ecosystem owners.

6.3 Risk Control & “Circuit Breakers”

Market volatility and loopholes can lead to “arbitrage raids.”

• Dynamic Incentive Adjustment:
  Set on-chain congestion-based adjustments. When daily interactions exceed thresholds (e.g., 500%), temporarily lower point coefficients to prevent script abuse.

• Anti-Witchcraft Pre-emptive Measures:
  On launch day, use AI fingerprinting to shadow-tag suspicious addresses, allowing them to participate at lower rewards, deterring bots.

• Liquidity Relief Mechanisms:
  Reward unlocks are smoothed over 6-12 months, based on ongoing activity, ensuring long-term incentive compatibility.

6.4 Community Governance “Pre-Deployment” Experiments

Don’t wait until token launch to start DAO governance.

• Simulated Voting Tasks:
  Set high-weight tasks for proposing protocol improvements during Odyssey phase.
• Purpose: Filter genuine stakeholders, cultivate governance culture early, reduce future coordination costs.

6.5 Deployment Checklist (Pre-Launch Must-Do)

1. Value Loop Check: Are rewards derived from protocol revenue (Real Yield)?
2. Anti-Witchcraft Depth: Is there ZK-ID or real identity verification (e.g., World ID, Gitcoin Passport)?
3. Capital Stickiness: Do tasks require funds to stay in protocol >14 days?
4. Technical Redundancy: Can the contract handle 100x load during spikes?
5. Emotional Value: Is the task narrative shareable, not just “digital labor”?

Conclusion — From “Game of Opponents” to “Value Coexistence”

Odyssey fundamentally revolutionizes filtering efficiency. By integrating “Incentive Compatibility” and “Behavior Entropy” analysis, the goal is not only to defend against witch attacks but to establish a precise value metric in a decentralized anonymous network.

This new paradigm recognizes that project and user are no longer zero-sum opponents. Through dynamic difficulty adjustment (DDA) and PoV models, we transform simple capital interactions into quantifiable contribution density. The key byproduct is on-chain credit—an accumulation of trust built through high-entropy interactions, long-term locking, and governance participation.

In this ecosystem, credit is not arbitrary; it’s the residual of genuine effort. Future incentives will go beyond token distribution, forging trust as a core asset. Every real contribution is etched into code, making “credibility” a more scarce and valuable passport than capital itself.

Ultimately, the Odyssey journey does not end with airdrops but marks the beginning of protocol-citizen relationships. By dispelling flow bubbles with math and technology, the solid credit foundation we build is the fundamental guarantee for Web3’s transition from “speculative wilderness” to “value civilization.”