3.5 AI Agent Marketplace Launching an AI Agent
3.5 Launching an AI Agent
Overview
Launching an AI Agent in the MonadAI ecosystem is a permissionless, decentralized, and developer-friendly process. Creators can build AI Agents using MIND (MonadAI Intelligent Neural Dynamics) or other agentic frameworks such as Zerepy, Eliza, Swarm, or custom AI architectures.
The process ensures that Creative Intelligence Agents (CI Agents) and Operational Intelligence Agents (OI Agents) can be deployed, governed, and monetized seamlessly, allowing developers and communities to create autonomous, evolving AI-driven solutions.
Step-by-Step Guide to Launching an AI Agent
1. Choosing the AI Framework
Before launching, developers must select the best AI framework for their agent’s functionality:
MIND (MonadAI Intelligent Neural Dynamics) – The native framework optimized for on-chain AI execution.
External AI frameworks such as Zerepy, Eliza, Swarm, or other custom-built architectures.
Custom AI Models that integrate through MonadAI’s SDK and APIs for added flexibility.
Developers can also access the AI Agent Training Terminal to test and refine their models before deployment.
2. Defining AI Agent Capabilities
Once the framework is selected, developers must define the AI Agent’s functional components:
For Creative Intelligence Agents (CI Agents)
Content Generation: AI-driven art, music, storytelling, and digital personalities.
Interactive Engagement: Virtual assistants, metaverse influencers, and AI-powered NPCs.
For Operational Intelligence Agents (OI Agents)
Data Processing & Analytics: AI models for real-time decision-making, risk assessment, and automation.
Smart Contract Execution: Agents that integrate with DeFi protocols, automate trading, and execute complex financial operations.
This modular approach allows AI Agents to expand their capabilities dynamically as their governance community evolves.
3. Smart Contract Deployment & Tokenization
After defining the AI Agent’s core functionality, it is deployed as a smart contract, ensuring:
✅ Autonomous execution – AI Agents operate independently on-chain.
✅ Transparent governance – Token holders can vote on upgrades, training, and optimizations.
✅ Permissionless accessibility – AI Agents can be used and interacted with without restrictions.
Each AI Agent is tokenized, meaning:
A governance token is created, allowing holders to influence the agent’s evolution.
Tokenized AI Agents can integrate fee structures for monetization, rewarding both developers and contributors.
4. Activating the AI Agent
Once deployed, the AI Agent is activated for real-world use, allowing:
✅ Users to interact with the agent in DeFi, gaming, content creation, or AI automation.
✅ Governance mechanisms to go live, enabling decentralized decision-making.
✅ Monetization to begin, allowing token holders to stake, fine-tune, or participate in revenue models.
5. Continuous Evolution & Fine-Tuning
AI Agents in MonadAI do not remain static—they learn, evolve, and improve over time through:
Community-driven governance, where token holders vote on improvements.
Upgradable smart contracts, enabling expansion of AI capabilities.
Data-driven optimization, allowing AI Agents to refine their decision-making.
This ensures that AI Agents stay relevant, competitive, and continuously enhance their performance.
Key Takeaways
Developers can launch AI Agents using MIND, external AI frameworks, or custom architectures.
AI Agents are modular, adaptable, and tokenized, ensuring governance-driven evolution.
Smart contract deployment enables decentralized execution and monetization.
Continuous learning and governance fine-tuning allow AI Agents to improve over time.
MonadAI’s permissionless deployment model ensures that anyone can build and launch AI-driven solutions.
Last updated