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Cheat Sheet

Your Cheat Sheet to AI Agents in ITOps

AI agents are changing how IT teams investigate incidents, make decisions, and coordinate responses. But with so many types of agents—and so much overlap in how vendors describe them—it can be difficult to understand what each one actually does.

This practical cheat sheet breaks down the roles AI agents play across IT operations, from alert correlation and root cause investigation to knowledge retrieval and governed remediation. It shows where agents reduce manual work, how they fit into existing workflows, and what organizations need to consider as they move toward Autonomous IT.

You’ll also find real-world incident scenarios, example prompts, and a breakdown of the technologies that help agents work together without losing context or control.

Inside the cheat sheet:

 

  • What distinguishes AI agents, AIOps, agentic AI, and Autonomous IT
  • Where different types of AI agents fit across the incident lifecycle
  • How agent-assisted incident response compares with traditional workflows
  • What to ask each agent—and what to expect in return
  • How context graphs, MCP, and A2A support coordinated agent workflows
  • How Edwin AI connects investigation, intelligence, and governed action

Whether you’re evaluating AI agents or looking to get more value from the ones you already use, this cheat sheet provides a practical reference for putting them to work in IT operations.

Get the cheat sheet

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