> For the complete documentation index, see [llms.txt](https://aiw3.gitbook.io/aiw3/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://aiw3.gitbook.io/aiw3/token-economics/point.md).

# Point

### **Incentive & Growth System**

AIW3 introduces a unified incentive system designed to align user behavior with platform growth across trading, strategy creation, prediction markets, and ecosystem participation.

Unlike traditional point systems, AIW3 incentives are structured as a **multi-loop contribution mechanism**, where users are rewarded for participating in both capital activities and intelligence generation activities within the AI-native execution ecosystem.

#### **AI Prediction & Market Participation Layer**

Users are incentivized to participate in AI-driven prediction and forecasting workflows:

* AI-generated market prediction tasks (e.g. event outcome forecasting)
* Participation in prediction market execution flows (including external venues)
* Sharing and distribution of AI-generated prediction results

This layer connects **AI reasoning → market participation → social distribution**, forming the early-stage intelligence feedback loop of the system.

#### **Growth & Referral Liquidity Layer**

The platform incentivizes user acquisition and liquidity expansion through structured referral mechanisms:

* New user onboarding rewards
* Trading user invitation incentives
* Volume-based referral rebates tied to downstream trading activity
* Network expansion rewards based on active capital participation

This creates a **self-expanding liquidity network driven by user distribution and capital inflow**.

#### **Strategy Intelligence Layer Incentives**

AIW3 directly incentivizes the creation and participation of trading strategies as core system assets:

* Strategy creation and publication rewards
* Strategy education and learning participation incentives
* Strategy subscription and capital allocation tracking
* Live performance-based reward mechanisms (pre-TGE metrics tracking)

Key tracked system metrics include:

* Total Strategy Subscription AUM
* Valid Strategy Capital Allocation
* Real Trading Performance Return

This layer transforms strategies into **monetized intelligence units within the ecosystem**.

#### **Transaction & Execution Incentives**

To stimulate onchain execution activity, AIW3 introduces direct trading participation incentives:

* Trading volume-based rewards
* Consecutive trading activity incentives
* Execution consistency rewards
* Beginner onboarding and trading education rewards

This ensures continuous **execution-level engagement and liquidity activity** within the system.

#### **Points-Based Unified Incentive System (Pre-TGE Layer)**

All user activities across prediction, trading, strategy, and referrals are unified into a points system prior to token generation (TGE).

Users can earn points through:

* Prediction participation
* Trading volume contribution
* Strategy creation and subscription
* Referral and network expansion
* Educational engagement (Academy system)

Key modules include:

* Prediction Tasks System
* Strategy Marketplace Incentives
* Transaction Incentive Engine
* Learning & Academy Rewards

These points represent **pre-token contribution weighting**, aligning early users with long-term ecosystem value distribution.

#### **System Design Logic**

The incentive system is designed around a closed-loop growth structure:

**Prediction → Strategy → Execution → Liquidity → Distribution → Back to Prediction**

This loop ensures that:

* Intelligence (AI predictions & strategies) generates engagement
* Engagement drives liquidity and execution
* Execution feeds back into data and prediction systems

#### **Final Outcome**

The AIW3 incentive system is not a reward layer, but a **behavioral coordination mechanism for an AI-native execution network**, aligning users, capital, and intelligence into a unified growth engine for Web3 markets.