7.1 Smart Contract Architecture
7.1 Smart Contract Architecture
Overview
The MonadAI ecosystem is powered by a robust smart contract architecture designed to ensure secure, transparent, and decentralized AI Agent execution. Smart contracts govern critical aspects of the ecosystem, including:
✅ AI Agent tokenomics – Managing the bonding curve model, liquidity migration, and DEX integration.
✅ Governance contracts – Facilitating community-driven decision-making, staking, and AI optimizations.
✅ Security mechanisms – Implementing access control, execution validation, and Sybil resistance measures.
By leveraging smart contracts as the core infrastructure, MonadAI ensures autonomous AI operations, verifiable governance, and on-chain AI economy management.
1. AI Agent Tokenization & Liquidity Management
AI Agents in MonadAI are tokenized entities that operate with a bonding curve model, ensuring fair and automated price discovery.
Bonding Curve Mechanism
AI Agents launch on a bonding curve where their tokens are initially paired against $MONAI.
As users buy an AI Agent’s token, liquidity accumulates within the bonding curve, ensuring deep liquidity for trading.
Each transaction incurs a 2.5% fee in $MONAI, distributed to governance participants and the ecosystem treasury.
📌 Example Use Case:
A DeFi trading AI Agent launches with a $MONAI-paired bonding curve.
As more users acquire the AI Agent’s token, its liquidity increases, stabilizing its market presence.
A portion of transaction fees funds governance and ecosystem expansion, ensuring long-term sustainability.
✅ This model enables AI Agents to gain adoption while ensuring sustainable liquidity provisioning.
Liquidity Migration to DEXs
When an AI Agent reaches a predefined market cap, its liquidity is migrated from the bonding curve to a decentralized exchange (DEX).
The AI Agent’s token is then traded freely against $MONAI, ensuring continued market depth.
Smart contracts ensure this migration happens automatically and securely, preventing liquidity manipulation.
📌 Example Use Case:
An AI Agent reaches its graduation threshold, triggering a liquidity transition from the bonding curve to a DEX.
Users can now trade the AI Agent’s token in open markets, while the bonding curve mechanism is deactivated.
✅ This ensures AI Agents seamlessly transition from early-stage growth to fully decentralized token economies.
2. Governance Smart Contracts & Decentralized Control
Governance within MonadAI is managed via staking-based smart contracts, ensuring that AI updates, optimizations, and funding allocations are governed by $MONAI holders.
AI Governance Execution
Staking contracts enable token holders to propose, vote, and implement AI training updates, execution refinements, and risk adjustments.
Voting power is proportional to staked $MONAI, ensuring that governance decisions reflect the interests of long-term participants.
Proposals must pass multi-stage validation to prevent governance takeovers and Sybil attacks.
📌 Example Use Case:
A proposed AI upgrade requires adding a new risk analysis module for a DeFi AI Agent.
Stakers vote on the proposal, ensuring the upgrade is implemented only if governance consensus is reached.
✅ This model ensures AI Agents remain adaptive while preventing centralized control over their execution models.
3. AI Agent Execution & Security Protocols
On-Chain AI Execution Contracts
AI Agents must interact with blockchain environments, smart contracts, and real-time data sources while ensuring:
✅ Only pre-approved functions are executed, preventing unauthorized AI behavior.
✅ AI Agents cannot alter governance rules, ensuring community-driven AI evolution.
✅ Data integrity is maintained, preventing tampered or manipulated AI-driven transactions.
📌 Example Use Case:
An AI Agent responsible for automated lending can only execute pre-approved risk assessments, ensuring it cannot arbitrarily allocate capital without governance approval.
✅ This prevents unauthorized AI actions while allowing decentralized AI execution.
AI Smart Contract Security Measures
AI Agent smart contracts must pass a security validation process before deployment.
Governance-approved security thresholds prevent AI Agents from executing non-verified functions.
Fail-safe mechanisms ensure that if an AI Agent executes an invalid action, it is automatically flagged for governance review.
📌 Example Use Case:
A trading AI Agent detects a potential arbitrage opportunity but its action exceeds the risk threshold set by governance.
The transaction is held for review before execution, ensuring risk-managed AI decision-making.
✅ This creates a secure AI execution framework while allowing AI Agents to operate autonomously.
Key Takeaways
Smart contracts govern AI Agent tokenomics, governance, and execution security.
Bonding curve mechanisms ensure fair AI Agent price discovery, while DEX migration supports long-term liquidity.
Governance contracts prevent centralized AI control, ensuring community-driven AI optimizations.
Security contracts enforce AI execution integrity, preventing unauthorized behaviors.
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