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Duration 21 hours (3 days)
Course Outline
Introduction to X402 and Decentralized AI
- Foundational overview of Coinbase’s X402 protocol
- Driving factors: Securing AI agents through on-chain identity
- System architecture and essential components
Preparing the Development Environment
- Installation of the X402 SDK and necessary dependencies
- Configuration of wallets and identity layers
- Setting up Node.js and Python for cross-language workflows
Deep Dive into the X402 Protocol
- Fundamental principles of agent-wallet interactions
- Data signing, verification processes, and privacy safeguards
- Patterns for secure communication and authorization
Integrating AI Models within X402 Applications
- Connecting to OpenAI, DeepSeek, Qwen, and Mistral Small
- Overseeing model inference and token consumption
- Building autonomous, wallet-aware AI agents
Implementing Smart Contracts for AI Interaction
- Defining agent permissions using Solidity
- Managing blockchain transactions driven by LLMs
- Testing and debugging the behavior of decentralized AI
Security, Compliance, and Data Sovereignty
- Regulatory considerations impacting AI and cryptocurrency
- Data ownership and privacy-preserving computational methods
- Auditing and securing agent interactions
Advanced Architectures and Enterprise Integration
- Aligning X402 with corporate identity infrastructure
- Designing scalable, multi-agent systems
- Case studies: AI-driven payments, analytics, and automation
Deployment and Operational Management
- Running decentralized AI agents in production environments
- Monitoring and maintaining X402-based ecosystems
- Optimizing performance metrics and cost efficiency
Summary and Future Directions
Requirements
- Familiarity with core blockchain concepts
- Practical experience in API integration and smart contract development
- Fundamental understanding of large language models and prompt engineering techniques
Target Audience
- Software engineers creating AI-integrated blockchain solutions
- Enterprise architects evaluating decentralized AI frameworks
- Engineering leads responsible for developing secure, compliant AI agents within on-chain ecosystems
Testimonials (1)
- like the blockchain introduction. For a blockchain newbie like me, its englighten me. - Like the technical workshop, also interesting
