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Most AI tools stop at prompts. Lyzr Agent Studio goes all the way to production-grade AI agents. Lyzr Agent Studio is the control center for building, deploying, evaluating, and monitoring AI agents at scale. It gives teams a single pane of glass to manage the entire agent lifecycle, from defining agent behavior to orchestrating multi-agent systems with memory, tools, and real infrastructure. In this deep dive, we walk through the Agent Studio end to end and show how enterprise AI agents are actually built. You’ll learn how to: Define agent roles, goals, and execution instructions Select models based on cost, speed, context size, and capabilities Ground agents using a knowledge base built from docs or websites Crawl and index hundreds of pages into a vector store Test retrieval quality and tune semantic thresholds Add memory, global context, and structured outputs Enable safety, hallucination management, and responsible AI Deploy agents as APIs or shareable apps Connect tools, MCP servers, and custom microservices Clone and customize verified blueprints Build manager agents that orchestrate multiple sub-agents This video also demonstrates a real multi-agent IT Help Desk workflow, where a manager agent routes employee requests to the correct sub-agent automatically. If you’re building AI agents for real workflows, not just demos, this is the infrastructure you need to understand. ⏱️ Chapters 00:00 What is Lyzr Agent Studio 01:10 Agent lifecycle overview 02:15 Role, goal, and instructions explained 04:10 Model selection strategy 06:20 Knowledge base creation and crawling 10:50 Retrieval testing and tuning 12:30 Memory and global context 14:50 Deployment and agent APIs 16:00 Tools, MCP, and integrations 18:50 Blueprints and templates 21:00 Manager agents and orchestration 22:10 IT Help Desk multi-agent demo 🔗 Important Links 🌐 Lyzr Website → https://hubs.ly/Q03wbGVt0 📥 Book a demo → https://hubs.ly/Q03wbH0k0 🤖 Build your own agents → https://hubs.ly/Q03wb5Md0