Same topic, related formats. Practice these next.
Same topic, related formats. Practice these next.
Explain how agent personas work in a multi-agent system. How do they constrain tool selection and reasoning focus, and what problem do they prevent?
A persona is a system prompt role that narrows an agent's decision space, biasing which tools it picks and what it reasons about, so multiple agents stop stepping on each other.
Imagine a small newsroom with three people. One is the reporter, one is the editor, one is the fact checker. Nobody told them their job titles in their genes, someone just handed each a short note saying what they do and what they should not touch. The reporter gathers quotes, the editor shapes the story, the fact checker only verifies numbers. Because each person knows their lane, they do not all fight over the same task or accidentally do each other's work. An agent persona is exactly that note. It lives in the agent's system prompt, the instructions it reads before every step. It tells the agent who it is, which tools to reach for first, and what to leave alone. Nothing about the model changes, only the instructions it starts each turn with.
Everything you need to truly understand this topic: intuition, mechanics, step by step explanation, code, formulas, and worked example. Click to expand.
Everything you need to truly understand this topic: intuition, mechanics, step by step explanation, code, formulas, and worked example.
Everything important, quickly.
Define a persona as system prompt role conditioning, explain the two axes of tool bias and reasoning focus, stress that weights never change, name the role conflict problem it prevents, then close on the coordination cost tradeoff and when one generalist agent wins.
Real products, models, and research that use this idea.
What an interviewer would ask next. Try answering before peeking at the approach.
Red flags and common mistakes that signal junior thinking. Click to expand.
Thinking a persona retrains or changes the model. It only changes the prompt context. The same model answers differently because its instructions, not its weights, now define a narrower role.
The night-before-the-interview bullets. Scan these on the way to the call.
Primary sources. Skim if you want the original framing.