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 Duration 21 hours (3 days)

Course Outline

Introduction to X402 and Decentralized AI

  • Overview of the Coinbase X402 protocol.
  • Why secure AI agents with on-chain identity matter.
  • Exploring architecture and core components.

Configuring the Development Environment

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

Deep Dive into the X402 Protocol

  • Core principles governing agent-wallet interactions.
  • Processes for data signing, verification, and privacy.
  • Patterns for secure communication and authorization.

Embedding AI Models in X402 Applications

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

Developing Smart Contracts for AI Interaction

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

Security, Compliance, and Data Sovereignty

  • Addressing regulatory frameworks for AI and crypto assets.
  • Ensuring data ownership and privacy-preserving computation.
  • Auditing and hardening agent interactions.

Advanced Architectures and Enterprise Adoption

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

Deployment and Operational Management

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

Wrap-Up and Future Directions

Requirements

  • Familiarity with core blockchain concepts.
  • Practical experience in API integration and smart contract development.
  • Fundamental knowledge of Large Language Models and prompt engineering.

Target Audience

  • Software engineers creating AI-integrated blockchain solutions.
  • Enterprise architects evaluating decentralized AI frameworks.
  • Engineering leaders tasked with building secure, compliant AI agents on on-chain infrastructure.

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