Ask HN: How do you get the most out of Deep Research?

Final Takeaway Example seeding is a powerful tool for alignment when used judiciously. For deep research, prioritize clarity of intent, iterative refinement, and testing variations. Start with minimal seeding, analyze outputs, and adjust prompts dynamically based on the model’s strengths/weaknesses.

Example Workflow for a Research Prompt Prompt: "Analyze the rise of decentralized finance (DeFi) in 2021–2023. Focus on regulatory responses in the EU vs. Asia. Provide:

Key drivers of DeFi adoption in each region. Comparative analysis of EU’s MiCA framework vs. Singapore’s Project Guardian. Hypothesize future regulatory trends (2024–2026). Format: Executive summary with 3 sections, APA citations. Exclude speculative content." Seeding Example: "Here’s an excerpt from a Georgetown paper structuring similar analyses. Use this style but do not copy verbatim."

When to Avoid Seeding Examples Exploratory phases (early-stage topic discovery). High-risk domains (e.g., medical research) where examples might introduce misinformation. Creativity-focused tasks (e.g., generating novel hypotheses). Final Takeaway Example seeding is a powerful tool for alignment when used judiciously. For deep research, prioritize clarity of intent, iterative refinement, and testing variations. Start with minimal seeding, analyze outputs, and adjust prompts dynamically based on the model’s strengths/weaknesses.