Industrial SEO at 100 Pages/Week: My n8n + Claude Code + RAG Stack
Stéphane Jambu discusses his approach to industrial SEO, achieving high output through a structured content generation pipeline. His method involves a three-layer system that ensures coherence across content clusters while utilizing AI tools. This strategy allows his agency to produce 50 to 100 pages per project per week without sacrificing quality.
- ▪Stéphane Jambu runs a French SEO agency based in Siem Reap, Cambodia.
- ▪The agency has produced over 1,300 semantic content clusters for more than 650 brands.
- ▪Jambu's three-layer pipeline includes a RAG knowledge base, n8n orchestration, and a QA loop with Claude Code.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3953538) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Stéphane Jambu Posted on May 27 Industrial SEO at 100 Pages/Week: My n8n + Claude Code + RAG Stack #seo #ai #automation #rag I run a French SEO agency from Siem Reap, Cambodia. We've shipped 1,300+ semantic content clusters for 650+ brands — typically at 50 to 100 pages per project per week. That cadence is impossible with a traditional content team. It's also impossible with raw LLM generation: the output looks fine in isolation and rots when you read three pages in a row.
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