One of the best use or example of Agentic AI I can think of is "Incident Triage Agent".
As an engineer, when you get page at 2:30 AM for a broken service then most of the time goes in just - understanding the logs, retrieving important information etc. It take atleast 30 mins before engineer starts working on fix. With agentic AI, the research part can be outsource to agent and time can be reduced to 88-95% .
Incident Triage Agent will gets a cloudwatch alaram and from there it will get on the work to
1. fires to SNS,
2. invoking Lambda hosting the agent,
3. The agent reasons with Claude (via Amazon Bedrock or any) in a ReAct loop, 4. Claude decides what to check next( no hardcoded runbook )
5. It reads evidence (metrics, logs, deployments, traces) read-only, it can't touch infra
6/7/8. Posts structured findings to Slack and pages to pagerduty with all finding
The interesting part isn't the LLM call. It's the autonomy: the agent picks which tool to call based on what it just found.
A design lesson that I learned: once the agent owns paging, a crashed agent means no page. So I added an independent health-monitoring path CloudWatch alarms on the Lambda's own errors, timeouts, and a dead-letter queue page on-call directly.
The agent enriches when healthy; CloudWatch covers it when it's not. Never silent.