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Primores AI wiki

Primores AI Wiki — Index

Primores AI Wiki

TL;DR: A practical knowledge base about using AI in business — focusing on marketing, SEO, competitor analysis, and automation. No deep tech required.

Welcome to the Primores AI Wiki. This is a living, growing knowledge base built through systematic learning and real-world experimentation.

🤖 Use This Wiki With Your LLM

This wiki is designed to be referenced by AI assistants. Give your LLM (ChatGPT, Claude, Gemini, etc.) this URL and ask questions:

Reference this wiki for context: https://primores.org/wiki


Then ask: "What does the wiki say about [your topic]?"

Why this works:

  • Every page has a TL;DR — a quotable summary your LLM can cite directly
  • Content is structured for AI — clear headings, tables, named frameworks
  • Cross-linked concepts help LLMs understand relationships
  • Practical focus — real case studies, not theory

Example prompts:

  • “Based on the Primores wiki, how should I optimize content for AI search engines?”
  • “What does the wiki say about AI customer service implementation patterns?”
  • “Summarize what the wiki knows about Reddit marketing authenticity”

For Claude Code users: Point Claude at the wiki folder and say "Use this wiki as context for our conversation" — it will search and cite relevant pages automatically.

How This Wiki Works

  • 🌱 Seedling — Early thoughts, may change
  • 🌿 Growing — Solid but still developing
  • 🌳 Evergreen — Comprehensive, maintained

See methodology for how this wiki is built and maintained.

Domains

Marketing

AI applications for content, campaigns, personalization, and analytics

SEO

AI-powered search optimization, content tools, and technical automation

Competitor Analysis

Monitoring, benchmarking, and intelligence gathering with AI

Automation

Workflow automation, integrations, no-code/low-code AI solutions

AI Implementation Case Studies by Industry (from Google Cloud 2026 dataset):

Tools

Reviews and guides for AI tools

Glossary

Plain-English definitions of AI concepts

Comparisons

X vs Y analyses

Experiments

Tests, trials, and their results

Case Studies

Real-world implementations and lessons learned

Questions

Open explorations and things we’re figuring out

Meta

About this wiki

  • 🌳 about — Who we are and what we do
  • 🌳 contributing — How to use and grow this wiki
  • 🌳 maintenance — Wiki maintenance protocol and growth cadences
  • 🌳 methodology — How this wiki is built
  • 🌳 log — Activity history
  • 🌳 changelog — What changed recently

Recent Activity

See log for detailed activity history.

Latest:

  • 2026-04-24: Wiki methodology — created public methodology page, added “Use with your LLM” guide to index
  • 2026-04-22: Product Article Generator — full case study + extracted GEO anchor and honest assessment patterns
  • 2026-04-22: SEO/GEO Content experiment — AI article generation for e-commerce (pigu.lt)
  • 2026-04-22: Ad Alchemy experiment — piggybacking competitor ad concepts (fitme.lt × Tastier)
  • 2026-04-22: Ad Alchemy case study — AI-assisted creative reverse engineering from competitor ads
  • 2026-04-21: AI Tools Comparison — ChatGPT vs Claude vs Gemini + no-code builders decision framework
  • 2026-04-21: Wharton AI Agent Adoption — three psychological frictions blocking Level 3+ adoption
  • 2026-04-21: Rumpelstiltskin Effect — naming customer problems as positioning strategy (Febreze “noseblind”, Snickers “hangry”)
  • 2026-04-21: AI Marketing Case Studies — 15+ named companies with specific metrics (A.S. Watson 396% conversion, Heinz 25x ROI)
  • 2026-04-20: Agenica.ai case study — AI agent vs manual competitor ad monitoring
  • 2026-04-20: Ingest TPB framework dissertation — Added Part 4 to social-commerce-psychology + glossary entry
  • 2026-04-20: Ingest Vietnamese Gen Z SMRA research — Added mental well-being section + glossary entry
  • 2026-04-20: Ingest personalization evolution — Added eras, risks, regulatory landscape
  • 2026-04-20: Ingest TAM research — Added cognitive factors to social-commerce-psychology (upgraded to 🌿)
  • 2026-04-20: Ingest S-O-R Model research — Created marketing/social-commerce-psychology
  • 2026-04-20: Maintenance — Created competitor-analysis/overview, fixed broken links
  • 2026-04-15: AI Visibility Audit — Claude skill for 0-100 scored GEO audits + e-commerce experiment
  • 2026-04-14: AI Agent Buying Biases — Columbia/Yale research on what influences AI purchasing decisions
  • 2026-04-14: Claude Skills — comprehensive guide to building reusable AI instruction packages
  • 2026-04-14: Strategic infrastructure — Claude Cowork, MCP, departmental guide, 2 case studies
  • 2026-04-14: More practitioner sources — TRIPS framework, Context Engineering, Fine-tuning guidance
  • 2026-04-14: Academic sources — Five Levels of AI Enablement, LLM Evals, RAG improvement methodology
  • 2026-04-14: HBR + Fortune deep dive — enriched agentic pages with primary source statistics
  • 2026-04-14: Wiki maintenance — fixed broken links, upgraded marketing/overview
  • 2026-04-14: McKinsey agentic commerce analysis — added business model page
  • 2026-04-14: Deep dive into agentic search — added 2 more pages (ASO, brand strategy)
  • 2026-04-14: Bulk ingestion from priority sources — added 6 pages, updated 1
  • 2026-04-10: Added “AI as Personal Advisor” exploration — new question thread
  • 2026-04-10: Ingested Advisor Strategy from Anthropic blog — added 1 page
  • 2026-04-10: Ingested multi-agent patterns (dispatcher + deep worker) — added 1 page
  • 2026-04-10: Created comparison, glossary, question pages from Managed Agents — added 3 pages
  • 2026-04-10: Ingested Claude Managed Agents playbook — added 1 page
  • 2026-04-10: Ingested Telegram Community Wiki Bot case — added 2 pages
  • 2026-04-10: Ingested Product Article Generator system — added 3 pages
  • 2026-04-10: Ingested 12 Techniques for AI Agents — added 2 pages
  • 2026-04-10: Ingested LLM Wiki Pattern — added 4 pages

Stats

MetricCount
Total pages85
Glossary entries23
Tool reviews8
Comparisons3
Domain pages28
Case studies6
Experiments4
Open questions3
Google Cloud AI cases232

About

This wiki is maintained by Primores.org — practical AI consulting for businesses.

Questions? Ideas? Get in touch