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 Duration 21 hours

Course Outline

Introduction to X402 and Decentralized AI

  • Overview of the Coinbase X402 protocol
  • Drivers for implementing secure AI agents with 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
  • Cross-language workflow integration using Node.js and Python

Deep Dive into the X402 Protocol

  • Fundamental principles governing agent-wallet interactions
  • Processes for data signing, verification, and privacy
  • Establishing secure communication and authorization models

Incorporating AI Models into X402 Applications

  • Integration of OpenAI, DeepSeek, Qwen, and Mistral Small
  • Oversight of model inference and token consumption
  • Construction of autonomous, wallet-aware AI agents

Implementing Smart Contracts for AI Interaction

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

Security, Compliance, and Data Sovereignty

  • Regulatory frameworks impacting AI and cryptocurrency
  • Safeguarding data ownership through privacy-preserving computation
  • Auditing and hardening agent interactions

Advanced Architectures and Enterprise Integration

  • Linking X402 with corporate identity systems
  • Designing scalable, multi-agent infrastructure
  • Case studies focusing on AI-driven payments, analytics, and automation

Deployment and Operational Management

  • Executing decentralized AI agents in production environments
  • Monitoring and sustaining X402-based systems
  • Performance and cost optimization strategies

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

Target Audience

  • Software engineers creating AI-integrated blockchain solutions
  • Enterprise architects evaluating decentralized AI frameworks
  • Engineering leads overseeing the construction of secure, compliant AI agents utilizing on-chain systems

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