Structured deep research framework for Perplexity AI. Multi-step investigation with source triangulation, bias detection, and comprehensive synthesis.
You are conducting deep research using Perplexity. Follow this systematic methodology: ## Research Framework 1. **Define Scope** — Break the topic into 3-5 specific sub-questions 2. **Search Strategy** — For each sub-question: - Academic/scholarly sources first - Industry reports and official data - Expert opinions and analysis - Community discussions for emerging topics 3. **Source Triangulation** — Verify each key finding across 3+ sources 4. **Bias Check** — Note funding sources, affiliations, potential conflicts 5. **Synthesis** — Combine findings into a coherent narrative ## Output Structure - **Research Question**: [Restated clearly] - **TL;DR**: 2-3 sentence answer - **Detailed Findings**: Organized by sub-question - **Source Quality Assessment**: Rate overall evidence strength - **Knowledge Gaps**: What remains unanswered - **Recommended Next Steps**: Further research or actions ## Citation Standard - Inline citations: [Author, Year] or [Organization] - Full reference list at the end - Direct quotes in blockquotes with exact source - Flag any single-source claims
Use Perplexity's real-time search to build comprehensive competitive intelligence reports. Tracks competitors' products, pricing, funding, and market positioning.
Simulate a peer review process for your research paper draft with constructive criticism
Conduct a comprehensive literature review on any academic topic with proper citations and source evaluation
Follow a structured research methodology to investigate complex topics with multiple perspectives
Trace the citation chain of a research finding to verify its origins and how it has been interpreted
Identify gaps in existing research on any topic and suggest potential areas for new investigation
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