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Course Outline
Introduction to Mastra
- Overview of AI frameworks for TypeScript.
- Key features and advantages of Mastra.
- Installation procedures and project setup.
Understanding the Mastra Architecture
- Core components and system design.
- The architecture of agents, workflows, and memory.
- Integration points with APIs and LLMs.
Building AI Agents
- Creating simple agents with TypeScript.
- Utilizing tools and context in agent reasoning.
- Composing multi-step AI tasks.
Workflows and Automation
- Designing agent-driven workflows.
- Triggering and managing async tasks.
- Error handling and process control.
RAG (Retrieval-Augmented Generation) Integration
- Implementing document retrieval and indexing.
- Connecting external knowledge bases.
- Optimizing 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.
- Security and scaling best practices.
Best Practices and Enterprise Use Cases
- Governance, auditability, and reliability considerations.
- Case studies from enterprise implementations.
- Future directions and community roadmap.
Summary and Next Steps
Requirements
- A solid grasp of JavaScript and TypeScript fundamentals.
- Prior experience with REST APIs or backend development.
- Basic familiarity with AI principles and LLM concepts.
Target Audience
- Software engineers engaged in developing AI or automation solutions.
- Engineering leads responsible for building agent-driven systems.
- Developers investigating enterprise-grade TypeScript AI frameworks.
14 Hours
