𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐚𝐫𝐞𝐧'𝐭 𝐣𝐮𝐬𝐭 𝐚𝐧𝐬𝐰𝐞𝐫𝐢𝐧𝐠 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 𝐭𝐢𝐜𝐤𝐞𝐭𝐬. 𝐓𝐡𝐞𝐲'𝐫𝐞 𝐨𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐞𝐧𝐭𝐢𝐫𝐞 𝐫𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰. This week, 𝐈’𝐦 𝐬𝐡𝐚𝐫𝐢𝐧𝐠 𝟓 𝐩𝐨𝐰𝐞𝐫𝐟𝐮𝐥 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐩𝐚𝐭𝐭𝐞𝐫𝐧𝐬 that can transform how businesses operate. 👉This is Day 2: 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 If you’re still thinking in terms of chatbots, it's time to rethink. Here’s a high-level agentic workflow you can start with: 𝟏. 𝐅𝐫𝐨𝐧𝐭𝐞𝐧𝐝 𝐋𝐚𝐲𝐞𝐫: The user submits a query through a web or mobile interface. 𝟐. 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐚𝐲𝐞𝐫: It analyzes the request and routes tasks to specialized agents based on the problem domain. 𝟑. 𝐈𝐧𝐭𝐞𝐧𝐭 𝐀𝐠𝐞𝐧𝐭: Detects what the user needs (billing, account help, technical issue) and enriches the query using vector search across past tickets and documents. 𝟒. 𝐓𝐨𝐨𝐥 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧 𝐯𝐢𝐚 𝐌𝐂𝐏: Securely connects to systems like CRMs or ticketing platforms to fetch data or trigger actions, no manual input required. 𝟓. 𝐐𝐮𝐞𝐫𝐲 𝐑𝐞𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 𝐀𝐠𝐞𝐧𝐭: Uses all available context to generate a complete, relevant response using an LLM. 𝟔. 𝐅𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐀𝐠𝐞𝐧𝐭: Evaluates the output’s confidence level, improves it if needed, and determines whether it requires human escalation. 𝟕. 𝐆𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥 𝐀𝐠𝐞𝐧𝐭: Performs safety checks, ensuring no sensitive or non-compliant content is sent out. 𝟖. 𝐅𝐢𝐧𝐚𝐥 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲: The orchestrator delivers the validated response back to the user via the original frontend channel. This is intelligent resolution at scale, powered by modular, collaborative AI agents. N͟o͟t͟e͟: Actual production workflows may differ based on your organization’s requirements, integrations, and compliance standards. Human-in-the-loop reviews, monitoring, and safety checks may be added or adjusted to suit specific operational needs. Please repost ♻️ if you found this useful. Follow me for more insights on Agentic AI. Join my community agentbuild ai to learn and build together. #AIAgents #CustomerSupport #LLM #AgentArchitecture #AgentBuildAI | 92 comments on LinkedIn