Workflow Automation with Mastra Training in Dhaka, Bangladesh

The Workflow Automation with Mastra Training is a hands-on, developer-focused program designed to teach how to build intelligent, automated workflows using Mastra and TypeScript.
The course focuses on orchestrating AI-driven processes, integrating tools and systems, managing state, and building reliable automation pipelines, enabling teams to automate complex business and technical workflows with AI.

This training is ideal for developers, automation engineers, platform teams, and solution architects building AI-powered workflow systems.

Workflow Automation with AI – Fundamentals

• What is AI-driven workflow automation

• Traditional automation vs AI workflows

• Where Mastra fits in automation stacks

Mastra Workflow Concepts

• Workflow primitives and abstractions

• Defining steps, tasks, and transitions

• Sequential, parallel, and conditional flows

• Designing maintainable workflows

Setting Up a Mastra Automation Project

• Project scaffolding and configuration

• Environment and secrets management

• Connecting LLM providers

• Basic workflow execution

Building Multi-Step Workflows

• Chaining AI and non-AI steps

• Passing data between steps

• Branching and decision logic

• Workflow state management

Event-Driven & Trigger-Based Automation

• Webhooks and event sources

• Time-based and schedule triggers

• External system triggers

• Reactive automation patterns

Tool & System Integration

• Integrating REST APIs

• Connecting databases and file systems

• Internal service orchestration

• Secure tool execution

AI in the Workflow Loop

• Using AI for classification and routing

• AI-driven decision steps

• AI-generated content in workflows

• Confidence and validation checks

Human-in-the-Loop Automation

• Approval and review steps

• Escalation workflows

• Blending human and AI decisions

• Designing for accountability

State, Memory & Long-Running Workflows

• Handling long-running processes

• Persisting workflow state

• Recovery after failures

• Idempotency and replay

Error Handling, Retries & Resilience

• Retry and backoff strategies

• Fallback and compensation logic

• Dead-letter queues (conceptual)

• Workflow reliability pattern

Observability & Monitoring

• Logging workflow execution

• Tracing and metrics

• Alerting on failures

• Debugging workflow behavior

Security, Governance & Access Control

• Managing secrets and credentials

• Role-based access for workflows

• Auditing and compliance

• Preventing unsafe automation

Performance & Cost Optimization

• Parallel execution strategies

• Caching and reuse

• Reducing LLM calls

• Scaling automation workloads

Hands-on Exercises

Summary and Conclusion