Apr 16
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Most people building with AI agents get this wrong early on. Should you use a single agent that does everything, or split the work across multiple specialized agents? In this video, I break down how both architectures actually work under the hood, using real examples like customer support agents and multi-agent content pipelines. More importantly, I walk through when each approach makes sense and the tradeoffs you need to be aware of before you start building. If you’re working on agentic systems, this is one of those decisions that will impact everything from performance to cost to how easy your system is to debug. What you’ll learn: ✦ What an AI agent actually is (beyond the buzzwords) ✦ How a single-agent system works step by step ✦ What changes in a multi-agent architecture ✦ When to use single vs multi-agent systems ✦ The hidden costs of going multi-agent If you’re building with agents or planning to, this should give you a much clearer mental model. I am launching Mastering Agentic AI, a 6-week intensive, technical, and project-based bootcamp starting May 30th. And for my YouTube family, I am giving an exclusive 10% discount. Link is in the description. This is not just for software engineers and AI engineers. If you are an AI PM, a PMM, a go-to-market expert, or in any adjacent role building AI products, this is for you too. Being technical is no longer only an engineer's thing. Every week you will be working on real projects in two flavors: coding and SDK-based for engineers, and no-code or low-code for tech leads, PMs, and everyone else. https://maven.com/aishwarya-srinivasan/mastering-ai-agents?promoCode=EXCLUSIVE-YT Subscribe for more deep dives on AI systems, agents, and real-world architectures.