The Everything Feed - All Packet Pushers Pods HN792: Understanding Agentic AI for Network Operations (Sponsored)
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Aug 15, 2025 Joining the discussion is Bob Friday, Chief AI Officer at Juniper Networks, now HPE, known for his expertise in AI and self-driving networks. The talk dives into the fascinating world of agentic AI and its role in network operations, emphasizing its nonlinear functionalities and the significance of high-quality data. Bob explains how these AI agents can autonomously interface with APIs and manage complex tasks, likening trust in AI systems to that of self-driving cars. Other highlights include the evolution of IT roles, the challenges of large language models, and the important balance of guardrails in AI operations.
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Agentic AI Is A Graph-Based Programming Model
- Agentic AI composes graphs of specialized agents that call LLMs, use tools, and reflect on answers to solve complex tasks.
- This creates a nonlinear, non-deterministic programming model that delegates cognitive work to connected agents.
Agents Use Reflection, Tools, And Planning
- Core agent attributes include reflection, tool use, planning and reasoning, and non-deterministic LLM-driven behavior.
- Agents break complex tasks into smaller steps and choose APIs/functions to achieve goals.
Prepare APIs And Docs For Agents
- Start by cataloging where your data lives and ensure APIs and docs clearly describe those sources for agent consumption.
- Prepare API descriptions (OpenAPI/MCP) and improve docs so agents can reliably call functions without hallucinating.