SEO Automation Agent Workflow
End-to-end automated SEO content research, SERP analysis, article generation, and WordPress publishing pipeline.
Project Overview
An autonomous SEO content pipeline engineered using n8n and large language model APIs. It systematically executes live SERP analysis, keyword intent clustering, semantic competitor gap evaluation, structured content synthesis, on-page schema formatting, and automated WordPress staging.
The Challenge
Writing high-ranking, research-backed SEO articles manually was taking 5 to 6 hours per article, severely constraining organic publishing scale and competitive topic cluster coverage.
The Objective
Automate the end-to-end research, drafting, structuring, and publishing pipeline while preserving high editorial depth, accurate keyword integration, and rich schema compliance.
Strategy & Engineering
Strategic Framework & Workflow Architecture
Orchestrated a multi-node n8n workflow connecting SERP research APIs, Claude/GPT reasoning for outline structuring, and the WordPress REST API for automated draft staging.
Technical Execution & Implementation
Built an automated pipeline that scrapes top-ranking SERP competitors, identifies keyword semantic gaps, drafts formatted long-form articles with FAQ schema, and uploads featured assets directly to WordPress.
Key Features & Deliverables
Verified Impact & Results
Reduced content creation time by 95% (from 5–6 hours down to under 5 minutes per article), enabling organic topic cluster scaling across 200+ target keywords.
Key Takeaways & Insights
AI automation works best when paired with strict structural constraints, validated keyword prompts, and programmatic editorial checks before final publishing.
