Building an AI Content Publishing Workflow That Actually Holds Together

Short summary

A practical guide to building an AI content publishing workflow that chains generation, editing, formatting, and CMS deployment into a repeatable process. The key insight is that breakdowns happen at handoff boundaries — not in generation — so human involvement should be concentrated at editing and QA stages rather than spread across every step. The author shares prompt template structures, automation patterns using Airtable and Notion, and cautions against publishing raw AI output for anything beyond low-stakes commodity content.

• •Breakdowns in AI content workflows happen at publishing handoffs, not generation
• •Seven-stage workflow from keyword input through post-publish QA with human checkpoints at editing and formatting
• •Prompt templates should stay simple; over-constraining produces worse output than letting the model reason freely

Generated with AI, which can make mistakes.