OpenAI has published a structured how-to guide through OpenAI Academy for using ChatGPT as a research tool — covering everything from fast web searches to multi-step investigative briefs with citations. It's less a product announcement and more a workflow manual, aimed at anyone using ChatGPT to turn raw questions into shareable, auditable outputs.
What's new
The guide formalizes two distinct modes: Search, for quick web-sourced orientation with citations, and Deep Research, for complex, multi-thread investigations that produce structured deliverables like memos, competitor tables, or annotated bibliographies. The distinction matters — Deep Research is designed to break a question into sub-questions, evaluate sources across each thread, and synthesize results in a format where reasoning is explicitly traceable. OpenAI includes sample prompts for both modes, including a competitive analysis scenario for a fictional cleaning products company, so users can see the expected output shape before committing to a workflow.
Why it matters
The guide signals how OpenAI is positioning ChatGPT in professional and knowledge-work contexts — not as a chatbot you ask one question, but as a structured research layer you run iterative, staged queries through. Tips like asking for a research outline first, requiring a "what's missing" section, and following up with targeted refinements like "Validate Y" or "Go deeper on X" reflect a more deliberate workflow than most casual users apply. For teams already using ChatGPT for research, this is a codification of best practices. For those who aren't, it's a reasonably concrete on-ramp.
What to watch
The practical ceiling here is still citation quality and hallucination risk — OpenAI's own guide recommends explicitly requesting source quality checks "when accuracy matters," which is an implicit acknowledgment that you shouldn't take outputs at face value. As Deep Research capabilities expand across models, the real competition will be in how reliably these tools surface primary sources versus summarized summaries of summaries. That's the gap nobody's fully closed yet.