Give a topic and get an AI agent that searches the web, cross-references sources, resolves contradictions, and produces a cited research brief.
Use this with ChatGPT Agent Mode, Claude with web access, or Perplexity Pro. The agent will autonomously search, read, and synthesize multiple sources.
You are a deep research agent. Your task is to conduct thorough, multi-source research on the following topic and deliver a comprehensive brief. Topic: [YOUR TOPIC OR QUESTION] Research protocol: 1. SEARCH PHASE: Search for at least 8-10 different sources on this topic. Prioritize recent sources (last 12 months). Include a mix of: academic papers, industry reports, expert blogs, news articles, and official documentation. 2. READING PHASE: For each source, extract: key claims, supporting data, author credentials, publication date, and any cited references worth following. 3. CROSS-REFERENCE PHASE: Compare claims across sources. Flag any contradictions. Note where multiple independent sources agree (high confidence) vs. where only one source makes a claim (low confidence). 4. SYNTHESIS PHASE: Produce the research brief with these sections: - Executive Summary (3-4 sentences) - Key Findings (numbered, with confidence level: HIGH/MEDIUM/LOW) - Contradictions & Debates (where experts disagree and why) - Data Points (specific numbers, statistics, dates) - Gaps (what the research couldn't answer or what needs more investigation) - Sources (linked, with brief note on each source's credibility) 5. FOLLOW-UP: Suggest 3 specific follow-up questions that would deepen understanding of this topic. Be relentless. Don't stop at surface-level results. Dig into the sources that sources cite. If a claim seems important but poorly supported, actively search for confirmation or contradiction.
What separates "Deep Research Agent" from an off-the-cuff AI question is precision. It applies depth requirements and analytical framing and reasoning elicitation, which gives the model enough direction to produce reliable agent workflows with decision logic, error recovery, and clear completion criteria. Expect reliable agent workflows with decision logic, error recovery, and clear completion criteria. The constraints in this prompt prevent the model from falling back on vague, unhelpful responses.
These agentic ai tips will help you get stronger results when using "Deep Research Agent" and similar prompts in this category.
"Deep Research Agent" is particularly useful in these situations. If any of these scenarios sound familiar, this prompt will save you significant time.
When you use "Deep Research Agent" with ChatGPT, Claude, or Gemini, here is what to expect in the AI output.
Adapt "Deep Research Agent" to your specific situation by modifying these key areas. The more context you add, the better the results.