ChatGPT for research

OpenAI’s guide shows how ChatGPT can accelerate research workflows by moving from a vague question to evidence-backed decisions. The tool offers two primary methods: a quick search mode that pulls up-to-date web information and summarizes it with citations, and a deep research mode that breaks complex questions into sub-questions, gathers and evaluates sources across those threads, and synthesizes the results into structured deliverables such as briefs, memos, or competitor tables. Users are encouraged to start with a research outline that includes sub-questions, source strategy, and evaluation criteria, and to request citations for key claims and a source quality check when accuracy is critical. The guide also recommends asking for a “what’s missing” section to highlight unknowns, disputed areas, or data limitations, and suggests follow‑up prompts like “Go deeper on X,” “Validate Y,” or “Compare A vs B.” Finally, it advises requesting concise one‑page or one‑slide summaries alongside full outputs to facilitate sharing and auditing of the reasoning and citations. This structured approach aims to make research outputs more trustworthy and easier to share within the AI industry.