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Cisco’s presentation at AI Field Day 8 addressed the growing complexities in enterprise network operations, where siloed teams across NetOps, SecOps, and AppOps grapple with a sprawl of disparate dashboards and a lack of consistent context during incident response. Meghan Kachhi emphasized that while agentic AI is no longer just a buzzword, its adoption is challenged by issues like data silos, the absence of domain-specific expertise in generic large language models, and a general lack of trust in closed-loop automation due to security concerns or opaque audit trails. The presentation highlighted the evolution of network operations from CLI and GUIs to software-defined networking and AIOps, positioning agentic ops as the latest layer of enhancement rather than a complete replacement of prior methodologies.
To tackle these challenges, especially for customers opting for their own large language models, Cisco introduces the Multi-Capability Platform (MCP) server integrated with Nexus Dashboard. This MCP server acts as a standardized, secure interface, simplifying how customer-owned AI agents interact with the network infrastructure. Instead of navigating thousands of complex REST API endpoints, agents can leverage the MCP server to call specific, high-value tools. The MCP intelligently handles complex API calls, pagination, and semantic understanding, providing aggregated schemas and data to the AI agents while establishing guardrails for access and scope, making the Nexus Dashboard a single, governed source of truth for network intelligence.
The operational flow demonstrated begins with an AI agent in an “assisted ops” mode, allowing human oversight. It identifies incidents, queries the MCP server for network anomalies on the Nexus Dashboard, verifies configurations, and initiates fixes using a network agent. Upon resolution, the MCP server’s integration capabilities extend to third-party platforms like PagerDuty for incident resolution, Confluence for knowledge base article creation, and Slack for team communication. This framework allows enterprises to build domain-specific skills and learn from resolved issues, with Cisco providing the foundational infrastructure for agentic AI. This approach supports a gradual transition from human-assisted operations to fully automated agentic ops, empowering organizations to address critical issues like AI/ML job performance degradation and security segmentation.
Personnel: Meghan Kachhi
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