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Duration 14 hours (2 days)
Course Outline
Introduction to Mastra
- Overview of TypeScript AI frameworks
- Core features and benefits of Mastra
- Installation procedures and project configuration
Exploring the Mastra Architecture
- Essential components and system design principles
- Structure of agents, workflows, and memory
- Integration touchpoints with APIs and LLMs
Developing AI Agents
- Creating basic agents using TypeScript
- Incorporating tools and context into agent reasoning
- Structuring multi-step AI tasks
Workflows and Automation
- Designing workflows driven by agents
- Initiating and managing asynchronous tasks
- Implementing error handling and process control
Integration of RAG (Retrieval-Augmented Generation)
- Executing document retrieval and indexing
- Linking external knowledge bases
- Enhancing response quality via contextual data
Observability and Debugging
- Tracking agent activity and log data
- Conducting performance profiling and optimization
- Debugging workflows and monitoring outcomes
Deployment and Scaling
- Releasing Mastra applications to production environments
- Integrating with cloud infrastructure
- Adhering to security and scaling best practices
Best Practices and Enterprise Applications
- Considerations for governance, auditability, and reliability
- Analysis of enterprise implementation case studies
- Future developments and community roadmap
Conclusion and Recommendations
Requirements
- Foundational knowledge of JavaScript and TypeScript
- Proficiency with REST APIs or backend development
- Basic understanding of AI and LLM concepts
Target Audience
- Software engineers focused on AI or automation initiatives
- Engineering leaders responsible for agent-driven systems
- Developers investigating enterprise-grade TypeScript AI frameworks
