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Duration 14 hours (2 days)
Course Outline
Introduction to Mastra
- Survey of TypeScript-based AI frameworks
- Primary features and benefits of Mastra
- Setting up the environment and initializing projects
Exploring Mastra’s Architecture
- Essential components and system design principles
- Structure of agents, workflows, and memory
- Connecting with external APIs and LLMs
Developing AI Agents
- Building foundational agents with TypeScript
- Applying tools and context in agent logic
- Constructing multi-stage AI tasks
Workflows and Automation
- Architecting agent-based workflows
- Initiating and overseeing asynchronous tasks
- Managing errors and controlling process flow
Integrating RAG (Retrieval-Augmented Generation)
- Setting up document retrieval and indexing
- Linking to external knowledge repositories
- Refining responses with contextual information
Observability and Troubleshooting
- Tracking agent activities and logs
- Profiling performance and optimization strategies
- Debugging workflows and monitoring results
Deployment and Scalability
- Releasing Mastra applications to live environments
- Integrating with cloud-based infrastructure
- Best practices for security and scaling
Enterprise Standards and Practical Applications
- Considering governance, audit trails, and reliability
- Reviewing case studies from enterprise deployments
- Looking at future trends and the community roadmap
Conclusion and Recommended Next Steps
Requirements
- Solid grasp of JavaScript and TypeScript core concepts
- Practical experience with REST APIs or backend system development
- Foundational knowledge of AI and LLM principles
Target Audience
- Software engineers focused on AI or automation projects
- Engineering leaders responsible for agent-based systems
- Developers investigating enterprise-scale TypeScript AI frameworks
