STORM prompting

STORM (Synthesis of Topic Outlines through Retrieval and Multi-perspective Question Asking) is an AI-powered research assistant developed by Stanford University. Designed to automate the writing of Wikipedia-style reports, the system works by simulating conversations between virtual "writers" and "subject matter experts," retrieving live web data to create comprehensive, well-cited articles. 

The STORM approach is specifically designed to eliminate "hallucinations" and avoid the shallow responses typically generated by single-prompt AI chatbots. It operates in three main stages: 

Pre-Writing (Multi-Perspective Questioning): Instead of asking the AI to "write a report on X," STORM creates two virtual personas: an interviewer and an expert. The interviewer asks the expert a wide variety of questions from different viewpoints (e.g., historical, economic, scientific, or skeptical).

Outlining: STORM then analyzes the answers to structure a logical, hierarchical Wikipedia-style outline.

Drafting: Finally, the system uses the outline and collected sources to generate the full article, complete with inline citations. 

There are several ways to apply the STORM technique to your own workflows:

The Web App: You can test the open-source web interface directly at the Stanford STORM Platform, where you simply input a topic and let the agents research and draft. 

Local Installation: Advanced users can download the GitHub Repository to run the system locally using open-source LLMs (like Llama 3) and custom search engines. 

Manual Prompting (The "STORM Method"): You do not need the software to use the technique. You can prompt standard LLMs (like Claude) with specific instructions to view your topic from multiple angles before drafting (e.g., asking the AI to provide a practitioner's view, a skeptic's view, and an economic analysis). 

For tips on how to apply multi-perspective prompting on platforms like Claude and ChatGPT, this guide walks through the exact workflow: