---
schema: 1
type: term
title: roleplaying prompt
description: >-
  A **roleplaying prompt** is a prompt that instructs an AI model to adopt a
  particular persona or role — such as acting as an analyst — so that its
  answers come from that role’s perspective. It is used to shape a model’s
  responses to fit a specific viewpoint or style.
canonical: >-
  https://liquidgold.cc/channel/everyinc/explore/term/roleplaying-prompt-ca31c7afaa4f
markdown: >-
  https://liquidgold.cc/channel/everyinc/explore/term/roleplaying-prompt-ca31c7afaa4f.md
llms: null
parent: 'https://liquidgold.cc/channel/everyinc/llms.txt'
channel: everyinc
updated: '2026-10-23T22:12:35.346Z'
language: null
children: []
---


# roleplaying prompt

Canonical: https://liquidgold.cc/channel/everyinc/explore/term/roleplaying-prompt-ca31c7afaa4f

Parent: [Channel index](https://liquidgold.cc/channel/everyinc/llms.txt)

## Definition

A **roleplaying prompt** is a prompt that instructs an AI model to adopt a particular persona or role — such as acting as an analyst — so that its answers come from that role’s perspective. It is used to shape a model’s responses to fit a specific viewpoint or style.

A **roleplaying prompt** is a prompt that asks an AI model to *take on a persona or role* — for example, “act as a stock analyst” — so that its responses are shaped by the expertise and viewpoint that role implies. In this episode, Dan Shipper and Jesse Beyroutey explore whether AI can help find their next great stock trade using **Gemini 1.5 Pro**’s one-million-token context window and **ChatGPT** [^21a76a20-f436-5d84-a76e-752842065aea]. Roleplaying prompts are one of the ways a prompt can steer a model during that kind of exploration: instead of asking a bare question, you frame the request around a role so the model’s screening and analysis come back in a useful professional voice.- It is a simple way to **shape a model’s output** without changing the underlying question. - It pairs naturally with the episode’s bigger techniques — screening stocks with LLMs and using giant context windows as an *analyst’s memory*. - Understanding it helps you understand how the hosts structure their prompts as they explore whether LLMs can support real investing decisions.