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 Duration 21 hours

Course Outline

Foundations of X402 and Decentralized AI

  • Introduction to Coinbase’s X402 protocol
  • Drivers for secure AI agents with on-chain identity
  • System architecture and essential components

Preparing the Development Workspace

  • Installing the X402 SDK and required dependencies
  • Setting up wallets and identity layers
  • Implementing Node.js and Python for cross-language workflows

Comprehending the X402 Protocol

  • Fundamental principles of agent-wallet interaction
  • Techniques for data signing, verification, and privacy
  • Patterns for secure communication and authorization

Embedding AI Models within X402 Applications

  • Linking OpenAI, DeepSeek, Qwen, and Mistral Small
  • Overseeing model inference and token consumption
  • Building autonomous, wallet-aware AI agents

Developing Smart Contracts for AI Engagement

  • Specifying agent permissions using Solidity
  • Processing LLM-driven blockchain transactions
  • Testing and debugging decentralized AI behaviors

Security, Regulatory Compliance, and Data Sovereignty

  • Regulatory implications for AI and cryptocurrency
  • Ensuring data ownership and privacy-preserving computation
  • Auditing and fortifying agent interactions

Advanced Architectures and Enterprise Integration

  • Aligning X402 with corporate identity frameworks
  • Designing scalable, multi-agent infrastructures
  • Case studies: AI-led payments, analytics, and automation

Deployment and Operational Management

  • Executing decentralized AI agents in production environments
  • Monitoring and maintaining X402-based systems
  • Enhancing performance and cost efficiency

Conclusion and Future Directions

Requirements

  • A solid grasp of blockchain fundamentals
  • Practical experience in API integration and smart contract development
  • Familiarity with large language models and prompt engineering techniques

Target Audience

  • Software engineers focused on AI-integrated blockchain applications
  • Enterprise architects investigating decentralized AI frameworks
  • Engineering leads developing secure, compliant AI agents utilizing on-chain systems

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