Developing AutoGPT Workflows Training in Thimphu, Bhutan

This course focuses on designing, developing, and deploying customized workflows using AutoGPT, a powerful AI agent that can autonomously complete multi-step tasks. Participants will learn how to break down business or technical tasks into actionable sequences, configure AutoGPT accordingly, and ensure reliability and control over its operations.

Workflow Planning and Core Setup

Introduction to AutoGPT as a Workflow Tool

• What is AutoGPT and how it works
• Overview of AI agents vs. traditional automation
• Key concepts: objectives, subtasks, tools, memory

Installing and Configuring AutoGPT

• Local or cloud setup instructions
• Installing dependencies and configuring API access
• Choosing memory type (local, Pinecone, Redis)
• Understanding the config.yaml and .env files

Designing Effective Objectives and Workflows

• What makes a good AutoGPT objective
• Structuring tasks as workflows
• Using goals, constraints, and command hints
• Real-world use case mapping (marketing, research, analysis)

Advanced Workflow Design and Debugging

Multi-Step Workflow Implementation

• Chaining multiple tasks together
• Incorporating file I/O, web browsing, and APIs
• Using “task memory” to handle progress tracking
• Adding feedback loops or checkpoints

Reusable Workflow Templates

• Building generalized templates for common tasks
• Automating report writing, content planning, or data review
• Managing agent identity and persona per task type
• Input customization for flexible use

Troubleshooting and Stability Practices

• Common errors: loop traps, hallucination, command failures
• Logging and debugging outputs
• Adjusting temperature, verbosity, and model parameters
• Performance optimization tips

Final Hands-On Exercises

• Group discussion and feedback
• Final Q&A and roadmap for next steps