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Course Outline
Introduction to Mastra
- Survey of AI frameworks for TypeScript.
- Key features and benefits of Mastra.
- Installation procedures and initial project setup.
Understanding Mastra’s Architecture
- Core components and system design principles.
- Architecture of agents, workflows, and memory.
- Integration points for APIs and LLMs.
Building AI Agents
- Developing simple agents using TypeScript.
- Applying tools and context to enhance agent reasoning.
- Composing complex, multi-step AI tasks.
Workflows and Automation
- Designing workflows driven by agents.
- Triggering and managing asynchronous tasks.
- Implementing error handling and process control.
Integrating RAG (Retrieval-Augmented Generation)
- Executing document retrieval and indexing.
- Connecting to external knowledge bases.
- Enhancing responses through contextual data optimization.
Observability and Debugging
- Monitoring agent activities and reviewing logs.
- Profiling performance and optimizing efficiency.
- Debugging workflows and tracking results.
Deployment and Scaling
- Deploying Mastra applications to production environments.
- Integrating with cloud infrastructure.
- Adhering to best practices for security and scalability.
Best Practices and Enterprise Use Cases
- Addressing governance, auditability, and reliability.
- Reviewing case studies from enterprise implementations.
- Exploring future developments and the community roadmap.
Summary and Next Steps
Requirements
- A solid grasp of JavaScript and TypeScript fundamentals.
- Previous experience with backend development or REST APIs.
- Foundational knowledge of AI concepts and Large Language Models (LLMs).
Target Audience
- Software engineers focused on developing AI or automation solutions.
- Engineering leaders responsible for constructing agent-based systems.
- Developers investigating enterprise-grade AI frameworks built with TypeScript.
14 Hours
