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Course Outline
Introduction to Mastra
- Survey of AI frameworks for TypeScript
- Core features and benefits of Mastra
- Installation procedures and project initialization
Understanding the Mastra Architecture
- Essential components and system design
- Architecture of agents, workflows, and memory
- Integration points for APIs and LLMs
Building AI Agents
- Developing simple agents with TypeScript
- Utilizing tools and context in agent reasoning
- Structuring multi-step AI tasks
Workflows and Automation
- Designing agent-driven workflows
- Initiating and managing asynchronous tasks
- Error management and process control
RAG (Retrieval-Augmented Generation) Integration
- Executing document retrieval and indexing
- Linking external knowledge bases
- Refining responses using contextual data
Observability and Debugging
- Monitoring agent activity and logs
- Performance profiling and optimization
- Debugging workflows and tracking outcomes
Deployment and Scaling
- Deploying Mastra applications to production
- Integration with cloud infrastructure
- Best practices for security and scaling
Best Practices and Enterprise Use Cases
- Considerations for governance, auditability, and reliability
- Case studies from enterprise implementations
- Future directions and community roadmap
Summary and Next Steps
Requirements
- Proficiency in JavaScript and TypeScript fundamentals
- Experience with REST APIs or backend development
- Foundational knowledge of AI or LLM concepts
Audience
- Software engineers focusing on AI or automation solutions
- Engineering leads developing agent-driven systems
- Developers investigating enterprise-grade TypeScript AI frameworks
14 Hours
