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 Duration 21 hours

Course Outline

Foundations of X402 and Decentralized AI

  • An introduction to Coinbase’s X402 protocol
  • Understanding the need for secure AI agents backed by on-chain identity
  • Examining the architecture and primary components

Preparing the Development Workspace

  • Setting up the X402 SDK and necessary dependencies
  • Establishing wallet configurations and identity layers
  • Connecting Node.js and Python to facilitate cross-language workflows

Deep Dive into the X402 Protocol

  • Core principles governing agent-wallet interactions
  • Processes for data signing, verification, and privacy protection
  • Establishing secure communication and authorization patterns

Incorporating AI Models into X402 Ecosystems

  • Linking OpenAI, DeepSeek, Qwen, and Mistral Small
  • Overseeing model inference and managing token consumption
  • Building autonomous AI agents with wallet awareness

Coding Smart Contracts for AI Interactions

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

Addressing Security, Compliance, and Data Sovereignty

  • Navigating regulatory frameworks for AI and cryptocurrency
  • Safeguarding data ownership and employing privacy-preserving computation
  • Conducting audits and securing agent engagements

Advanced Architectures and Enterprise-Level Integration

  • Merging X402 with existing corporate identity infrastructures
  • Architecting scalable, multi-agent systems
  • Reviewing case studies involving AI-driven payments, analytics, and automation

Deployment Strategies and Operational Management

  • Executing decentralized AI agents in production environments
  • Monitoring and sustaining X402-based infrastructures
  • Enhancing performance and optimizing cost efficiency

Requirements

  • A solid grasp of fundamental blockchain concepts
  • Practical experience in API integration and smart contract development
  • Foundational knowledge of Large Language Models and prompt engineering

Target Audience

  • Software engineers crafting AI-integrated blockchain solutions
  • Enterprise architects investigating decentralized AI frameworks
  • Engineering leaders constructing secure, compliant AI agents leveraging on-chain systems

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