Build with AI: Create Deterministic MCP Agents

Explore the intricacies of building deterministic model context protocol (MCP) agents in this comprehensive course. Start with foundational topics such as PMAT and the Toyota Way before delving into the complexities of certainty-scope tradeoffs and field service management (FSM) quality metrics. Learn about the MCP protocol architecture and gain insight into survivorship-adjusted language popularity. Master the six essential quality metrics and test types needed for creating robust agents. Engage with agentic AI for property testing and fuzz testing to ensure your agents perform as expected. Discover how to utilize tools like Claude with PMAT for enhanced testing practices. To solidify your learning, review project examples that showcase practical implementations of these concepts. This advanced level course is tailored for individuals passionate about AI, specifically those who want to deepen their understanding of MCP agents and their applications.