Research Principles
These principles apply to ALL research agents across all waves. Every agent must follow them.
Iterative Deep Research
Each agent performs 5-8 web searches minimum, organized in sequential rounds that drill deeper:
- Round 1: Broad overview queries
- Round 2: Drill-down into specific findings from Round 1
- Round 3: Cross-reference and validate
- Round 4: Reality check and edge cases
Do NOT stop after a single query. The first search gives you the surface — the follow-ups give you the insight.
Source Quality Tiers
Rank every finding by source reliability:
| Tier | Source Type | Use For |
|---|---|---|
| Tier 1 | Industry reports (Gartner, Forrester, McKinsey, IBISWorld), SEC filings, government data, G2/Capterra aggregate data | Hard numbers, market share, verified metrics |
| Tier 2 | Reputable tech press (TechCrunch, Bloomberg, WSJ), company press releases, Crunchbase, investor presentations | Funding data, company news, expert opinions |
| Tier 3 | Blog posts, Reddit threads, individual reviews, social media | Sentiment, customer voice, anecdotal evidence |
For positioning research, Tier 3 sources are ESPECIALLY valuable — customer reviews and forum posts reveal how buyers describe their problems and what "better" means to them. This is the language map that drives positioning. But don't use them for hard numbers.
Positioning-Specific Search Strategies
When researching alternatives and buyer behavior:
- Search for "what do you use for [problem]", "[competitor] vs", "switching from [tool]", "alternative to [tool]"
- These queries surface the language customers actually use, revealing positioning opportunities
When researching category definitions:
- Search for analyst reports on category definitions, Gartner/Forrester quadrants, buyer guides
- Track how the category is evolving — new subcategories and adjacent spaces signal positioning white space
Cross-Referencing
Never trust a single source for important claims. For every key finding:
- Look for 2-3 independent sources
- If sources agree: note convergence and cite all
- If sources disagree: note both figures, explain the discrepancy, and state which you trust more and why
Quantification
Vague claims are worthless. Always push for numbers:
- Bad: "They're a big player"
- Good: "$12M ARR, 2,500+ customers, Series B ($28M from Accel)"
- Bad: "Their pricing is high"
- Good: "$49/seat/mo for Pro, $99/seat/mo for Enterprise, vs. market median of $35/seat/mo"
Dating
Always note when data was published. Flag anything older than 12 months as potentially outdated. Positioning landscapes shift fast — a funding round, pivot, or acquisition can change everything in weeks.
Handling Research Failures
Sometimes WebSearch won't find what you need:
- Try alternative queries. Rephrase, use synonyms, try different angles. At least 3 variations before declaring a gap.
- Use proxy data. If you can't find a competitor's revenue, estimate from team size, funding, pricing × estimated customers. Show your math.
- Declare the gap explicitly. Write: "DATA GAP: Could not find reliable data on [X]. Closest proxy: [Y]. Confidence: Low."
- Never fabricate. An honest "unknown" is infinitely more valuable than a made-up number.
- Suggest how to fill the gap. Point to specific reports or recommend reaching out to the competitor's customers directly.