Mastra doesn’t behave like yet another AI framework — it feels more like a well-organized workshop for people who want to build things that think. Built on TypeScript, it gives developers a clean, opinionated space to shape AI agents, orchestrate workflows, and weave data flows together without the usual tangle of glue code and duct-taped libraries. There’s a sense of precision to it: the ergonomics of a modern toolkit wrapped around the chaos of real-world automation.
These instructor-led live training courses step inside that workshop. They dig into the architecture that makes Mastra compelling — the modular agent patterns, the workflow primitives, the integration layer that encourages scale instead of resisting it. Participants learn how to turn business logic into autonomous behavior, how to coordinate multi-step reasoning pipelines, and how to keep everything predictable in production, where reliability matters more than demos.
Training is available as online live training through an interactive remote desktop, providing participants with a hands-on environment that mirrors real development workflows and supports collaborative learning from any location.
Training is also available as onsite live training in Quito, whether at customer premises or NobleProg training centers, enabling teams to work together in a shared physical space while engaging directly with practical, scenario-based exercises.
Also known in some circles as a TypeScript-native AI agent framework, Mastra is quickly becoming the go-to choice for developers who want structure without rigidity — a place where AI automation, data orchestration, and enterprise-ready engineering finally meet on equal footing.
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Mastra is a framework that provides structured tools for evaluating, debugging, and assuring the reliability of AI agents operating across complex workflows.
This instructor-led, live training (online or onsite) is aimed at intermediate-level practitioners who wish to rigorously test agent behavior, improve reliability, and implement measurable evaluation processes.
At the end of this training, participants will confidently:
Apply debugging techniques to identify and correct agent behavior issues.
Evaluate agents using structured metrics, benchmarks, and quality scores.
Implement tooling and workflows that track reliability, drift, and hallucinations.
Design QA strategies that ensure consistent and predictable agent performance.
Format of the Course
Interactive lecture and discussion.
Hands-on debugging and evaluation exercises.
Live-lab analysis of agent behaviors using observability tools.
Course Customization Options
Customized reliability testing scenarios and industry-specific QA methods can be arranged upon request.
Mastra is a framework that supports deep integration between AI agents, APIs, enterprise applications, and external data systems.
This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers who wish to build reliable, secure, and scalable integrations between Mastra agents and the broader enterprise ecosystem.
Once this training is completed, participants will be prepared to:
Implement API-driven integrations between Mastra agents and external services.
Connect enterprise data systems and tools to automated agent workflows.
Apply secure data exchange and authentication best practices.
Design integration layers that are scalable, maintainable, and production ready.
Format of the Course
Interactive lecture and discussion.
Hands-on integration engineering and API exercises.
Live-lab implementation using real-world enterprise scenarios.
Course Customization Options
Custom API scenarios, enterprise system mappings, or data-integration workshops are available upon request.
Mastra is a framework that enables sophisticated workflow automation and coordination across multiple AI agents operating within distributed systems.
This instructor-led, live training (online or onsite) is aimed at intermediate-level practitioners who want to design, orchestrate, and operate multi-agent workflows at scale.
By completing this training, participants will gain the skills to:
Design complex workflows using Mastra’s orchestration capabilities.
Coordinate multiple agents performing parallel or dependent tasks.
Implement monitoring and debugging tools for workflow execution.
Optimize orchestration logic for reliability, throughput, and automation efficiency.
Format of the Course
Interactive lecture and discussion.
Hands-on workflow design and automation exercises.
Practical implementation in a containerized live-lab environment.
Course Customization Options
Customized automation scenarios, enterprise integrations, or workflow patterns can be provided upon request.
Mastra is an operational framework designed to streamline the deployment, scaling, and lifecycle management of AI agents in production environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level technical professionals who need to operationalize AI agents reliably and efficiently across production systems.
Upon completion of this training, attendees will be equipped to:
Deploy Mastra-based AI agents into controlled, production-grade environments.
Scale agents horizontally and vertically using platform-native primitives.
Implement observability pipelines to track agent behaviour and performance.
Optimize runtime configurations to reduce latency, costs, and operational risks.
Format of the Course
Interactive lecture and discussion.
Hands-on exercises focused on real deployment scenarios.
Live-lab implementation using containerized and orchestrated environments.
Course Customization Options
Customization of topics, hands-on labs, or industry-specific scenarios is available upon request.
This instructor-led, live training (online or onsite) is aimed at intermediate-level software developers and engineering teams who wish to build scalable, observable AI systems using Mastra.
By the end of this training, participants will be able to:
Understand Mastra’s architecture and how it integrates with LLMs and external APIs.
Design and implement AI agents and workflows using TypeScript.
Use Mastra’s observability and memory tools to monitor and improve agent performance.
Deploy production-ready AI applications leveraging Mastra’s framework features.
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