AI SEO in Practice: Skills System Slashes Content Production to 10 Minutes
yangyi · x · 2026-08-10
The author shares hands-on experience in building SEO/GEO traffic using AI. Directly asking AI to write often leads to formatting issues and SEO pitfalls; the core solution is building an externalized, verifiable AI Skills system.
Core Methodology:
- Three Design Principles: 1) Keep the context lean, only providing expert info the AI lacks; 2) Match freedom to task fragility (e.g., strict limits on Meta length, high freedom for writing style); 3) Rules must be verifiable (e.g., checking character counts via code) rather than subjective.
- Architecture & Workflow: Uses SKILL.md as an entry point, referencing single-responsibility detail docs on demand. The pipeline is divided into five stages: research, content generation, automated AI QA, manual review, and publishing.
- QA Mechanism (BLOCKING): Implements 19 automated checks (e.g., internal link count, external 404s, Schema structure). Unmet criteria block the workflow.
Results: After nine iterations on a real content pipeline, SEO guideline compliance jumped from 60% to 95%, reducing single-article production time from 1 hour to about 10 minutes.
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