Building an AI Agent is only half the work — getting it ready for production is where the real discipline begins. In this video, Ritesh Ramesh and Dustin Snell walk through practical guidance for improving AI Agent prompts, selecting the right tools, understanding retrieval-augmented generation, and preparing agents for enterprise deployment with guardrails, security controls, and evaluations. The session covers how ServiceNow AI Agents can operate across conversational channels, connect to enterprise systems, use internal and external data sources, and be tested before going live. —————————————————————————— ⏱ TIMESTAMPS —————————————————————————— 00:04 - AI Agents across channels and enterprise systems 00:53 - Prompts and tools: the two core building blocks 01:16 - Retrieval-Augmented Generation (RAG) explained 01:46 - Context stuffing and context window tradeoffs 02:16 - Decomposing prompts and simplifying instructions 02:46 - Writing prompts for different models 03:14 - Defining clear agent roles 04:21 - Prompting best practices recap 04:51 - Tools as the second major control 05:41 - Knowledge Graph as an AI Agent tool 06:04 - MCP tools and external system connections 06:23 - Search Retrieval and AI Search 07:27 - Reusing Integration Hub connectors as tools 07:49 - Preparing agents for production 08:48 - Prompt injection and jailbreaking protection 09:10 - Data privacy and sensitive information masking 09:51 - Agent evals and production testing 10:43 - Measuring accuracy and tool usage 11:33 - Running evals with ground truth or production logs 11:58 - Human-in-the-loop review and regulated industries 12:42 - Homework: run an agent eval 13:26 - Why evals, KPIs, and measurement matter 13:43 - Filtering sensitive topics —————————————————————————— 📌 WHAT YOU’LL LEARN —————————————————————————— ✅ How AI Agents can operate across channels like Messenger, Slack, Teams, SMS, and more ✅ Why prompts and tools are the two core controls when building AI Agents ✅ How Retrieval-Augmented Generation improves accuracy with business context ✅ When to use context stuffing — and when it can become too much ✅ How to simplify prompts so agents follow instructions more reliably ✅ Why agents need permission to say “I don’t know” ✅ How roles, examples, and prompt structure affect output quality ✅ What tool types are available inside ServiceNow AI Agent Studio ✅ How to prepare agents for production with security, privacy, and evals —————————————————————————— 🛠 TOOLS COVERED —————————————————————————— 🔎 Search Retrieval and AI Search 📚 Knowledge Articles and external content connectors 🕸️ Knowledge Graph ⚙️ Flows, subflows, scripts, and records 🔗 Integration Hub connectors 🌐 MCP tools for external systems —————————————————————————— 🛡 PRODUCTION READINESS, SECURITY, AND EVALS —————————————————————————— This video highlights several production readiness capabilities, including: 🛡 Now Assist Guardian guardrails 🚨 Offensiveness detection and blocking 🔐 Prompt injection and jailbreaking protection 🕵️ Data privacy and sensitive information masking 📊 Agent evaluations ✅ Accuracy measurement 🔧 Tool usage validation 👤 Human-in-the-loop review Agent evals help teams prove whether an AI Agent is actually doing its job before turning it on for employee-facing or customer-facing use cases. —————————————————————————— 💡 KEY TAKEAWAY —————————————————————————— Good AI Agents are built with both creativity and control. Prompts help define how the agent thinks. Tools determine what the agent can do. Guardrails define what the agent must not do. Evals prove whether the agent is ready. The future of AI Agent deployment will not be just about building agents — it will be about measuring, governing, and improving them continuously. —————————————————————————— 🔗 RELATED VIDEOS IN THIS SERIES —————————————————————————— Explore the rest of our AI Agent series to learn more about identifying AI Agent use cases, building agents in AI Agent Studio, adding tools, deploying across channels, using Knowledge Graphs, and governing enterprise AI safely. —————————————————————————— 🏷 ABOUT THIS SERIES —————————————————————————— This series explores AI Agents in ServiceNow — from use case selection and architecture to hands-on implementation, prompting, tool selection, governance, evaluations, and production readiness. Built for ServiceNow architects, developers, administrators, platform owners, AI practitioners, and business leaders looking to build enterprise AI solutions that are useful, measurable, and safe to deploy. #ServiceNow #AIAgents #AgenticAI #NowAssist #AIAgentStudio #EnterpriseAI #PromptEngineering #AITrust #WorkflowAutomation #ServiceNowDeveloper