An AI automation agent is a system that can understand goals, reason about tasks, call tools or APIs, and execute workflows with minimal human intervention. It combines three pillars:
Intelligence (LLMs, rules, or models)
Tools (APIs, scripts, connectors)
Orchestration (logic, workflows, triggers)
Section 1: Typical architecture
User or system trigger
Orchestrator (agent brain)
Tools: Python scripts, REST APIs, Fabric queries
Memory/logging
Monitoring & feedback
Section 2: Technologies used
Python: core agent logic and tool wrappers
Azure AI Foundry: LLMs, prompt orchestration, hosted endpoints
Microsoft Fabric: data access, analytics, and event pipelines
Other options: Logic Apps, Power Automate, GitHub Actions for scheduling
Learning outcome:
Design an AI automation agent architecture
Implement an agent in Python
Call Azure AI Foundry models from your agent
Read/write data via Microsoft Fabric
Build an end‑to‑end automated workflow