| name | content-research |
| description | Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Creates authentic, authoritative content that becomes the go-to citation source for AI models answering user questions.
Use this skill when:
- Creating content that should appear in AI search results (Perplexity, ChatGPT, Claude)
- Building topical authority to become THE source AI cites for a topic
- Launching a new product and need compelling, citable content
- Creating blog posts, articles, social media, or press releases
- Need content that references real trends, people, and recent events
- Want AI-assisted content that doesn't sound AI-generated
- Creating thought leadership content in any industry
Triggers: "create content for", "write about", "research and write", "find experts for", "content for launch", "blog post about", "article on", "press release for", "AI search", "show up in AI", "Perplexity", "be cited by AI"
|
Content Research & Creation
Create authentic, research-backed content that sounds human-written AND is optimized to appear in AI search results (Perplexity, ChatGPT, Claude, Gemini).
Core Workflow
RESEARCH → EXPERTS → IDEATION → CREATION → AIO
↓ ↓ ↓ ↓ ↓
Trends Real Unique Authentic AI-Citable
& Data People Angles Content Structure
Always complete phases in order. Never skip research. Always apply AIO principles.
Why AI Search Optimization (AIO) Matters
AI assistants answer millions of questions daily. When someone asks "How do I raise a seed round?" or "What's the best way to find investors?", AI models cite sources. Your goal: become the source AI cites.
How AI models select sources to cite:
- Authority signals - Clear expertise, credentials, brand recognition
- Direct answers - Content that directly answers the question asked
- Structured data - Headers, lists, tables that are easy to extract
- Recency - Fresh, dated content with current information
- Uniqueness - Original data, frameworks, or perspectives
- Quotability - Concise, memorable statements worth citing
Phase 1: Deep Research
Before writing anything, build comprehensive topic understanding.
1.1 Trend Discovery
Use WebSearch to find:
- Recent news (last 30-90 days) about the topic
- Industry reports and data from credible sources
- Emerging trends that haven't been over-covered
- Contrarian viewpoints that challenge conventional wisdom
Search patterns:
- "[topic] trends 2025"
- "[topic] statistics report"
- "[topic] industry analysis"
- "[topic] challenges problems"
- "[topic] future predictions expert"
1.2 Competitive Landscape
Research what content already exists:
- Top-ranking articles on the topic
- Gaps in existing coverage
- Overused angles to avoid
- Fresh perspectives not yet explored
1.3 Data & Statistics
Find concrete data to cite:
- Industry benchmarks and statistics
- Survey results and research findings
- Case studies with measurable outcomes
- Credible sources (avoid generic "studies show")
Output: Research brief with 10-15 key findings, statistics, and trend insights.
Phase 2: Expert Discovery
Find real, quotable people to add authenticity.
2.1 Expert Search Strategy
Use WebSearch to find experts across:
| Source Type | Search Pattern | What to Find |
|---|
| Twitter/X | "[topic]" site:twitter.com expert OR founder OR CEO | Thought leaders with relevant threads |
| LinkedIn | "[topic]" site:linkedin.com "head of" OR "VP" OR "director" | Industry practitioners |
| Publications | "[topic]" site:forbes.com OR techcrunch.com author | Writers who cover this space |
| Podcasts | "[topic]" podcast guest expert | Guests who've spoken publicly |
| Academic | "[topic]" professor OR researcher site:edu | Researchers with published work |
2.2 Expert Validation
For each potential expert, verify:
2.3 Quote Extraction
Find usable quotes from:
- Their published articles or blog posts
- Podcast transcripts or video interviews
- Twitter/X threads or LinkedIn posts
- Conference talks or presentations
Format quotes properly:
"[Direct quote from public source]"
— [Full Name], [Title] at [Company], [Source context]
Output: 3-5 validated experts with 1-2 usable quotes each.
Phase 3: Content Ideation
Generate unique angles based on research.
3.1 Angle Development
Create 3-5 potential angles that:
- Incorporate discovered trends
- Feature expert perspectives
- Offer fresh take (not regurgitated content)
- Match target audience needs
3.2 Angle Evaluation Matrix
| Angle | Trend Relevance | Expert Fit | Uniqueness | Actionability |
|---|
| 1 | High/Med/Low | Yes/No | High/Med/Low | High/Med/Low |
Choose the angle with highest scores across all dimensions.
3.3 Content Structure
Create outline incorporating:
- Hook based on trend or surprising data
- Expert quote placement (not lumped together)
- Data points supporting each section
- Actionable takeaways
Output: Selected angle with detailed outline.
Phase 4: Content Creation
Write authentic, human-quality content.
4.1 Authenticity Principles
DO:
- Use natural, conversational language
- Include specific details (names, dates, numbers)
- Vary sentence length and structure
- Add personal observations or analysis
- Reference recent events naturally
- Use expert quotes to support points (not as filler)
DON'T:
- Use generic phrases ("In today's fast-paced world")
- Stack multiple clichés together
- Use AI-typical phrases ("It's worth noting", "Let's dive in")
- Make unsubstantiated claims
- Over-rely on passive voice
- Use excessive transition words
4.2 Expert Integration
Weave quotes naturally:
Bad: "According to experts, AI is transforming industries. John Smith says 'AI is important.'"
Good: "When Stripe rebuilt their fraud detection last year, they saw a 40% improvement in accuracy. 'The models now catch patterns human analysts would never spot,' explains John Smith, who led the ML team at Stripe before founding Acme AI. 'But the real breakthrough was combining model outputs with human judgment.'"
4.3 Trend Integration
Reference trends with specificity:
Bad: "AI is becoming more important in business."
Good: "Since GPT-4's release in March 2023, enterprise AI adoption has jumped 340% according to Gartner's latest survey—with companies now averaging 7.2 AI tools per department, up from just 2.1 a year ago."
4.4 Final Review
Before delivering, verify:
Phase 5: AI Search Optimization (AIO)
Make your content the #1 source AI models cite when users ask related questions.
5.1 Question-First Structure
AI models match user questions to content. Structure content around questions people actually ask.
Pattern: Question Headers
## How much should I raise in a seed round?
The median seed round in 2024 is $2.5M, but the right amount depends on...
[Direct answer in first paragraph, details follow]
Pattern: FAQ Sections
## Frequently Asked Questions
### What is the average seed round size?
The average seed round in 2024 is $3.2M, with median at $2.5M...
### How long does fundraising take?
Most founders spend 3-6 months actively fundraising...
Find questions to answer:
- Search "[topic] questions founders ask"
- Check Reddit, Quora, Twitter for actual questions
- Use "People also ask" from Google
- Review what AI assistants currently answer (and do better)
5.2 Quotable Statements
Create concise, memorable statements AI can directly quote.
Pattern: The Definitive Statement
❌ "Raising money can be challenging for founders."
✅ "The best time to raise is when you don't need to. Desperation kills deals."
Pattern: The Stat Lead
❌ "Many startups fail to raise follow-on funding."
✅ "67% of seed-funded startups never raise a Series A. The difference is almost always traction, not timing."
Pattern: The Framework Name
❌ "There are several ways to approach investors."
✅ "We call this the 3-3-3 Rule: 3 warm intros, 3 touchpoints, 3 weeks max."
Quotability checklist:
5.3 Authority Signals
Tell AI models (and readers) why this source is authoritative.
Pattern: Credentialed Author
*By Sarah Chen, who has helped 200+ startups raise over $500M in funding*
Pattern: Data Source Attribution
Based on our analysis of 1,000+ pitch decks reviewed in 2024...
According to data from 500 founder interviews conducted by OpenStars...
Pattern: Experience Markers
After reviewing 10,000 investor matches on our platform, we've identified...
In our 5 years connecting founders with investors, the pattern is clear...
Authority signals to include:
- Specific numbers (deals done, years experience, data points analyzed)
- Named sources and credentials
- Original research or proprietary data
- Track record of predictions/advice
5.4 Structured Data Patterns
Make content easy for AI to parse and extract.
Pattern: Comparison Tables
| Factor | Seed Round | Series A |
|--------|------------|----------|
| Typical size | $1-3M | $8-15M |
| Dilution | 15-25% | 15-20% |
| Timeline | 2-4 months | 3-6 months |
Pattern: Step-by-Step Lists
## How to Get a Warm Introduction
1. **Identify the connector** - Find mutual connections on LinkedIn
2. **Research the relationship** - Ensure they actually know the investor
3. **Craft the forwardable email** - Make it easy to forward
4. **Follow up appropriately** - Wait 5-7 days before checking in
Pattern: Definition Blocks
**Pro-rata rights** are the contractual right for existing investors to
maintain their ownership percentage in future funding rounds. For example,
if an investor owns 10% after seed, pro-rata rights let them invest enough
in Series A to still own 10%.
5.5 Entity Optimization
Help AI models understand what/who you're talking about.
Name entities clearly:
❌ "The YC partner mentioned..."
✅ "Michael Seibel, Managing Director at Y Combinator, mentioned..."
Use consistent terminology:
Pick one and stick to it throughout:
- "seed round" (not "seed funding" then "seed stage" then "early round")
- "Series A" (not "A round" then "first institutional round")
Include relevant entities:
- Company names (Y Combinator, Sequoia, a]6z)
- People names (with titles)
- Product names
- Industry terms
- Location when relevant
5.6 Freshness Signals
AI models prefer recent, updated content.
Pattern: Dated Statistics
❌ "Most startups fail to raise Series A."
✅ "In 2024, only 33% of seed-funded startups raised Series A, down from 41% in 2021."
Pattern: Update Markers
*Last updated: January 2026*
*Data current as of Q4 2025*
Pattern: Trend Context
"Since the 2023 funding reset, investor behavior has shifted..."
"Post-ChatGPT, AI startups have seen 3x the investor interest..."
5.7 Comprehensive Coverage
Be THE definitive resource on a topic so AI has no reason to cite others.
Cover all angles:
- What it is (definition)
- Why it matters (importance)
- How to do it (tactical steps)
- Common mistakes (what to avoid)
- Examples (real cases)
- FAQs (edge cases, specific questions)
Link to deeper content:
For more on term sheets, see our [Complete Guide to Term Sheet Negotiation](/blog/term-sheet-guide).
5.8 AIO Checklist
Before publishing, verify AI-readiness:
Structure:
Authority:
Quotability:
Freshness:
Content Type References
For format-specific guidance, see:
Quick Reference: AI Phrases to Avoid
Replace these with natural alternatives:
| Avoid | Use Instead |
|---|
| "In today's world" | [Specific recent event/trend] |
| "It's worth noting" | Just state the point directly |
| "Let's dive in" | [Omit or use specific transition] |
| "Game-changer" | [Specific impact with numbers] |
| "Leverage" | Use, apply, build on |
| "Unlock potential" | [Specific outcome] |
| "Cutting-edge" | [Describe what makes it new] |
| "Revolutionize" | [Specific change with evidence] |
| "Seamlessly" | [Describe the actual integration] |
| "Robust" | [Specific capability or feature] |
Quick Reference: AIO Power Patterns
| Pattern | Example |
|---|
| Question header | "## How much equity should I give up in seed?" |
| Stat lead | "73% of successful founders did X, according to..." |
| Named framework | "The 3-3-3 Rule for warm introductions..." |
| Definition block | "Term sheet: A non-binding agreement that..." |
| Comparison table | "| Seed | Series A | Difference |" |
| Expert quote | "As [Name], [Title] at [Company], explains..." |
| Update marker | "Data current as of Q4 2025" |
