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Autonomous Research Agents

Build research agents that autonomously explore and discover

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The Autonomous Research Loop

Research agents operate in a continuous loop: generate questions, search for answers, extract information, synthesize insights, and decide whether to continue exploring or conclude. This loop runs autonomously until the research goal is achieved.

Interactive: Research Loop Simulation

Watch how the autonomous research loop operates:

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Step 1: Generate Questions
Break topic into specific research questions
"What are CRISPR safety concerns?" → 5 specific questions about off-target effects, delivery, ethics
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Step 2: Search Sources
Query databases, papers, and web for answers
Search PubMed, arXiv, Google Scholar with targeted queries. Collect 50+ relevant papers.
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Step 3: Extract Information
Read documents and pull key findings
Extract methodology, results, conclusions from each paper. Build knowledge graph of findings.
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Step 4: Synthesize Insights
Connect findings and identify patterns
Find consensus (85% papers agree), conflicts (15% disagree), and gaps (questions unanswered).
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Step 5: Decide Next Step
Sufficient info? Continue exploring or conclude
If gaps remain, generate follow-up questions and loop. If complete, write final report.

Loop Control Strategy

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Max Iterations: Set limit (e.g., 5 loops) to prevent infinite exploration. Most research completes in 2-3 loops.
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Confidence Threshold: Continue if confidence < 80%. Stop when findings are well-supported.
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Diminishing Returns: Stop if new loop adds < 10% new information. Avoid redundant searching.
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Time Budget: Set max duration (e.g., 8 hours). Prioritize high-value questions within time limit.
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The Power of Iteration

First loop finds obvious answers. Second loop discovers contradictions and gaps. Third loop explores edge cases and novel connections. Each iteration deepens understanding. Most valuable insights come from loop 2-3, not loop 1. Budget for iteration - it's where research agents outperform humans who often stop after first pass.

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