Stop Building One Big AI Agent. Use Subagents Instead (TypeScript)

Adding too many tools to a single AI agent leads to inconsistent results and poor tool selection - and prompt engineering won't save you. In this video, I'll show you how to fix that with sub-agents: a supervisor/worker architecture that keeps each agent focused, reduces context bloat, and makes your whole system smarter. We'll cover when and why to use sub-agents, how to implement them with Mastra, real-world challenges like context management and response evaluation, and how to wire everything together in a Next.js app using the AI SDK. By the end, you'll have a working multi-agent customer support app — Skybridge Airways — with specialized agents for FAQ, booking, flight status, and cancellations. Project: https://github.com/Quintui/mastra-supervisor-agent-demo Mastra: https://mastra.ai/docs/agents/supervisor-agents X: https://x.com/kristianvtr Work with me: https://www.dawnstudio.co/ 0:00 Too many tools makes your agent dumb 0:28 Demo: Skybridge Airways app 2:07 Naive approach vs. sub-agent architecture 3:31 The supervisor/employee mental model 4:16 Sub-agents for context overflow 5:04 Defining agents in Mastra 6:56 Wiring it into a Mastra instance 7:27 Next.js API route setup 8:22 Context management between sub-agents 9:54 Task scoring and feedback loops 10:57 Frontend rendering with useChat 11:43 Sub-agents as tool calls in the message stream 13:14 Wrap-up