May 23
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When should your AI app use a single agent with multiple tools, and when do you actually need a Multi-Agent System (MAS)? In this video, we unpack the engineering trade-offs behind AI orchestration. Using a real-world ticket reservation, invoicing, and email notification pipeline, we map out the design patterns used by enterprise systems today. You'll learn about cognitive load in LLMs, why separation of concerns matters for application security, and how to optimize API computing costs by assigning different models (like Gemini Pro vs. Gemini Flash) to specific sub-agents. We also discuss how a conversational supervisor handles edge cases and data validation dynamically compared to rigid sequential pipelines. If you are an AI engineer or developer looking to scale your autonomous agent workflows, this architectural breakdown is for you. Hit that subscribe button for more deep dives into advanced AI engineering and agentic design patterns!