Cursor Setup and Extensions

1. Tools Installed

• Cursor IDE
• Claude Code Extension
• Codex Extension

2. Steps Completed

1. Installed Cursor IDE from https://cursor.com/
2. Opened Cursor and navigated to Extensions
3. Searched for and installed "Claude Code"
4. Logged into Claude Code
5. Searched for and installed "Codex"
6. Logged into Codex
7. Created a GitHub account
8. Created a new public repository
9. Opened the repository in Cursor
10. Created this README.md file

3. Issues Encountered and Solutions

Issue 1: Extension not installing

• Solution: Restarted Cursor IDE and retried installation

Issue 2: Login issues with extensions

• Solution: Ensured stable internet connection and re-authenticated

Issue 3: GitHub push failed

• Solution: Configured Git with username and email using: git config --global user.name "Your Name" git config --global user.email "your@email.com"

4. Conclusion

The setup was successfully completed, and all tools are working correctly.

Research: AI-Powered SEO Content Production

This repository contains a research corpus on AI-powered SEO content production – a practitioner-focused investigation into how AI is changing SEO content workflows, LLM citations, and brand strategy.

What Was Collected

Folder	Contents
research/sources.md	10 expert profiles with links, collection dates, and annotations
research/linkedin-posts/	LinkedIn posts from each expert (manually collected)
research/youtube-transcripts/	Video transcripts fetched via fetch_transcripts.py
research/other/	Cross-expert pattern analysis and emerging signals

Why These 10 Experts

Experts were selected against four criteria:

1. Practitioner status – actively runs SEO/content campaigns, not just commentary
2. AI-specific output – publishes experiments, frameworks, or tools for AI content
3. Verifiable track record – named clients, measurable results, or open-source tools
4. Active in 2024–2026 – current relevance, not historical

Expert	Why Chosen
Kevin Indig	Former VP SEO at Shopify, G2, Atlassian. Analyzed 7,000+ LLM citations.
Lily Ray	Google update authority. Created AEO framework tracking AI brand mentions.
Aleyda Solís	International SEO + LLM workflow automation. Practical prompt templates.
Chima Mmeje	Moz content strategist. Keyword clustering methodology for AI content.
Kyle Roof	Controlled ranking experiments with isolated test sites – empirical data.
Bernard Huang	Built Clearscope. Content relevance scoring and AI quality gates.
Ross Hudgens	Agency-side AI production at scale. "Brand-first SEO" framework.
Michał Suski	Surfer SEO co-founder. Tool-native AI workflows used by thousands.
Nathan Gotch	GEO frameworks and step-by-step AI tutorials – replicable templates.
AJ Ghergich	Enterprise AI content governance. Named on multiple expert lists.

Key Patterns Found

Across all 10 experts, six consensus themes emerged (detailed in research/other/cross-expert-patterns.md):

1. AI Draft Model – AI writes 80%, humans add E-E-A-T
2. LLM Citation ≠ Google SEO – Dual optimization required
3. Brand as Infrastructure – Brand recognition is now a search variable
4. Reddit, YouTube, Forums as SEO Infrastructure – LLMs cite them heavily
5. Volume Without Quality is a Liability – Penalties for low-E-E-A-T AI content
6. Evergreen Declining, Experience Rising – Original data is the moat

How to Use This Research

1. Read research/sources.md to understand each expert's focus
2. Run python fetch_transcripts.py to download YouTube transcripts (requires pip install yt-dlp)
3. Study research/other/cross-expert-patterns.md for actionable consensus and disagreements
4. Use the patterns to build your own AI content workflow

Research collected April 2026