Impressive paper showing how much the first retrieval step matters for deep research agents. It helps to improve GPT-5.5 from 83.1% to 90.5% on BrowseComp-Plus with the same retriever and the same agent loop. It seems that the gain comes from the opening context. The authors propose Question's Gambit which runs once, before the agent starts searching. It splits the question into clues, turns each clue into complementary searches, pools the results, and reranks them. The agent then starts…