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 Duration 21 hours

Course Outline

Introduction to X402 and Decentralized AI

  • An overview of the Coinbase X402 protocol
  • The rationale behind secure AI agents with on-chain identity
  • Key architectural elements and components

Preparing the Development Environment

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

Comprehending the X402 Protocol

  • Foundational principles of agent-wallet interactions
  • Techniques for data signing, verification, and privacy protection
  • Patterns for secure communication and authorization

Integrating AI Models into X402 Applications

  • Connecting models such as OpenAI, DeepSeek, Qwen, and Mistral Small
  • Managing model inference processes and token consumption
  • Building autonomous, wallet-aware AI agents

Developing Smart Contracts for AI Engagement

  • Specifying agent permissions using Solidity
  • Processing blockchain transactions driven by LLMs
  • Testing and troubleshooting decentralized AI behaviors

Security, Compliance, and Data Sovereignty

  • Regulatory aspects concerning AI and cryptocurrency
  • Data ownership rights and privacy-preserving computation
  • Auditing and securing interactions between agents

Advanced Architectures and Enterprise Adoption

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

Deployment and Operations

  • Managing decentralized AI agents in production environments
  • Monitoring and maintaining X402-based systems
  • Optimizing system performance and operational costs

Conclusion and Future Directions

Requirements

  • A solid grasp of blockchain fundamentals
  • Hands-on experience with API integration and smart contract development
  • Familiarity with large language models and prompt engineering concepts

Target Audience

  • Software engineers creating blockchain applications integrated with AI
  • Enterprise architects evaluating decentralized AI frameworks
  • Engineering leads constructing secure, compliant AI agents utilizing on-chain technologies

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