Attachment download: Agent Interview Questions.pdf — handy for printing or offline reading

Why Would You Need Multiple Agents

An opening question to separate people who have “read the articles” from people who have “actually built one”.

The bad answer: “Multi-agent enables parallel processing, which improves system throughput and robustness.”

Every word of that is correct, but if you follow up with “so after splitting into two agents, did throughput actually double?”, they stall. The reality: inter-agent communication has overhead, coordination has complexity, and after the split total throughput may well drop. Adding agents is not like adding CPU cores.

It runs a complete expert workflow — requirement research, material retrieval, outline planning, layout planning, visual design — where every step allows manual fine-tuning, or the whole thing can run automatically end to end. In terms of output, pages generated with Gemini 3 Flash already reach commercial delivery quality.

Conclusion first: multi-agent collaboration is not “spinning up a few more model instances.” It has to solve task scheduling, context isolation, permission control, state management, and result merging — every one of which is an engineering problem, not a prompt problem.

The multi-agent stories on TikTok and Xiaohongshu usually go like this: one agent researches, one agent writes code, one agent runs tests, one agent does review, and the main agent collects results like a project manager. The comments: “Whoa, that’s insane.”