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Duration 14 hours
Course Outline
Introduction to Mastra
- Survey of AI frameworks tailored for TypeScript
- Principal features and benefits of the Mastra framework
- Setting up the installation and initial project structure
Exploring Mastra's Architecture
- Core components and overall system design
- Structure of agents, workflows, and memory
- Integration points for APIs and LLMs
Developing AI Agents
- Creating basic agents using TypeScript
- Incorporating tools and context into agent reasoning
- Assembling complex, multi-step AI tasks
Workflows and Automation
- Structuring agent-driven workflows
- Initiating and overseeing asynchronous tasks
- Managing errors and controlling processes
RAG (Retrieval-Augmented Generation) Integration
- Executing document retrieval and indexing strategies
- Linking external knowledge bases
- Enhancing responses through contextual data optimization
Observability and Debugging
- Tracking agent activities and reviewing logs
- Conducting performance profiling and optimization
- Troubleshooting workflows and monitoring results
Deployment and Scalability
- Releasing Mastra applications to production environments
- Connecting with cloud infrastructure services
- Implementing security and scaling best practices
Best Practices and Enterprise Applications
- Addressing governance, audit trails, and reliability
- Examining case studies from enterprise deployments
- Discussing future trends and the community roadmap
Conclusion and Future Steps
Requirements
- Solid grasp of JavaScript and TypeScript basics
- Background in REST API development or backend engineering
- Fundamental knowledge of AI or LLM principles
Target Audience
- Software engineers focused on AI or automation initiatives
- Engineering leads developing agent-centric systems
- Developers investigating enterprise-level TypeScript AI frameworks
