A network change can complete successfully while the service it was meant to repair remains slow. As AI agents take on approved operational tasks, NetOps teams need a way to check the result before treating the problem as resolved. Cisco’s approach to AgenticOps puts continuous assurance, or ongoing measurement of service experience and performance, inside that decision process.
Define recovery before an agent changes the network
Consider an agent that redirects traffic to address a slow application. Confirmation from the routing system establishes that the change took effect. It doesn’t establish that the application became more responsive.
Did the replacement path reduce delay, or does packet loss still affect the service?
The practical distinction is between completing a task and restoring acceptable performance. A successful API response answers the first question. Measurements of the affected service help answer the second.
Cisco describes continuous testing as a way to establish conditions before an agent acts, then compare them with measurements taken afterward. That gives the workflow a reference point rather than leaving it to assume that a completed change helped.
Evidence to compare around a change
- Application response time and availability
- Delay, packet loss, and behavior along the affected network path
- Experience measurements for users and applications
- Results from synthetic tests conducted before and after the action
These checks should follow the intended outcome. If the task is to improve application response time, confirmation that a routing update was accepted cannot substitute for measuring that response time again.
Failed validation should keep the investigation open
Cisco’s AgenticOps model describes agents that examine operational information, investigate possible causes, and perform permitted actions. The workflow becomes iterative: evidence from one intervention shapes the next decision.
A failed check is useful evidence.
In Cisco’s illustrative scenario, an approved remediation completes, but synthetic tests still show poor application response time. Measurements of the path continue to indicate packet loss, while experience metrics remain degraded. Closing the incident at that point would confuse successful execution with recovery.
Depending on the organization’s permissions and controls, the agent could investigate further, attempt another already-approved remedy, seek human review, request permission for a different action, or reverse the original change. Those are possible responses within defined boundaries, rather than a blanket license to keep making changes.
For operators, the practical requirement is clear: the workflow needs a next step when validation fails. A check that merely records disappointment without informing the next decision leaves the operational loop incomplete.
Give agents evidence beyond the system they changed
Cisco positions Cisco Assurance as a source of performance and experience information spanning applications, networks, users, cloud services, SaaS, and the Internet. It describes active tests, telemetry, Experience Metrics, and information about network paths and Internet conditions as complementary views of service behavior.
The purpose is to give an agent evidence beyond the acknowledgment returned by the system it changed.
Cisco also describes access through APIs and the Model Context Protocol (MCP) as a route for making assurance information available within agent workflows. In practical terms, measurements that people would otherwise interpret can become inputs to the agent’s next decision. That access supports validation; it doesn’t itself prove that a remedy worked.
Let measured results shape operating permissions
Cisco argues for a gradual expansion of autonomy, starting with recommendations and potentially progressing through human-approved execution to bounded autonomous actions. Repeatedly successful outcomes can provide evidence for expanding permissions. Repeated failures can support keeping those permissions narrow or reducing them.
The operational pressure is speed. As agents act more frequently, manual review of every result becomes harder to sustain. Continuous validation offers a way to keep checking outcomes as the pace increases.
For NetOps teams, the immediate design question is what evidence each approved action must produce before the incident can close. Defining that evidence, and the response when it is missing or unfavorable, makes agent execution part of a controlled service-recovery workflow.
