What deep research is and when you need it

You already know the weakness of an ordinary answer: the model replies from memory — stale data, fabrication included. Deep research fixes both.

How the mode works

1. You frame the research question.
2. The model plans: which sub-questions to split it into, what to look for.
3. It searches and reads: dozens of queries, dozens of pages opened — on its own, for minutes.
4. It writes the report: structured text with a source link behind every claim.

What you get after 5–20 minutes isn't "the model's opinion" — it's a digest of real web pages you can check link by link.

When to launch it (and when not to)

• ✅ Decisions where being wrong costs you: which CRM to pick, where to move, which course or university, what kind of company that employer really is.
• ✅ Many-sided topics: a market, the competition, "what does the science actually say about…".
• ✅ Fresh topics where the model's memory has gone stale.
• ❌ Simple facts ("capital of Australia") — normal chat is faster.
• ❌ Creative and stylistic work — no research needed there.

The honest caveat, up front

Deep research cuts fabrication sharply, but it doesn't repeal the main rule: the report is an analyst's draft, not the truth. Sources can be junk, readings can be skewed. Modules 2–3 are about telling one from the other.

Try it now

Run your first study on something personal ("should I buy [that thing you've been eyeing]: pros, cons, alternatives") and look at how the report is built and what it links to. Next we'll learn to do this properly.