**Intact Gift Giving Condition book**

Building AI Agents for Network Operations shows how to use AI agents, LLMs, and network automation in a controlled way, so engineers can get clearer evidence without giving up validation or operational control. Build AI-assisted network troubleshooting workflows that parse CLI output, call approved tools, use MCP, and keep evidence visible for review Key Features Build local LLM workflows for NetOps using Python, Ollama, and validated CLI data Create troubleshooting agents that use memory, approved tools, and clear evidence Package reusable network tools with MCP and plan controlled read-only pilots Book Description Network troubleshooting is full of clues, but they are often buried in noisy alerts, long CLI output, missing topology context, and incomplete handoffs. You will start with local LLM workflows using Ollama and Python, then use a simple RACE prompt structure to make repeatable NetOps tasks clearer, safer, and easier to review. You will parse interface and BGP output into structured data, build a chatbot that keeps troubleshooting context, and connect the model to approved tools for device status, interfaces, reachability, topology, and BGP health.