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Course Outline

Introduction to X402 and Decentralized AI

  • Overview of Coinbase’s X402 protocol.
  • Motivation: Building secure AI agents with on-chain identity.
  • Architecture and key components.

Setting Up the Development Environment

  • Installing the X402 SDK and dependencies.
  • Configuring wallets and identity layers.
  • Integrating Node.js and Python for cross-language workflows.

Understanding the X402 Protocol

  • Core principles governing agent-wallet interactions.
  • Data signing, verification, and privacy measures.
  • Secure communication and authorization patterns.

Integrating AI Models into X402 Applications

  • Connecting OpenAI, DeepSeek, Qwen, and Mistral Small.
  • Managing model inference and token usage.
  • Creating autonomous, wallet-aware AI agents.

Implementing Smart Contracts for AI Interaction

  • Defining agent permissions in Solidity.
  • Handling blockchain transactions driven by LLMs.
  • Testing and debugging decentralized AI behavior.

Security, Compliance, and Data Sovereignty

  • Regulatory considerations for AI and cryptocurrency.
  • Data ownership and privacy-preserving computation.
  • Auditing and securing agent interactions.

Advanced Architectures and Enterprise Integration

  • Integrating X402 with corporate identity systems.
  • Designing scalable, multi-agent infrastructures.
  • Case studies: AI-driven payments, analytics, and automation.

Deployment and Operations

  • Running decentralized AI agents in production environments.
  • Monitoring and maintaining X402-based systems.
  • Optimizing performance and cost.

Summary and Next Steps

Requirements

  • A foundational understanding of blockchain principles.
  • Practical experience with API integration and smart contract development.
  • Basic familiarity with large language models and prompt engineering.

Target Audience

  • Software engineers working on AI-integrated blockchain applications.
  • Enterprise architects exploring decentralized AI structures.
  • Engineering leads tasked with building secure, compliant AI agents using on-chain systems.
 21 Hours

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