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AI Content Workflow

When to Use

Use the 8-stage AI content workflow when creating, managing, or optimizing content at scale. Use when you need consistent quality, SEO optimization, and strategic alignment.

Decision

Content Type Recommended Stages to Automate Human Touch Required
Blog posts 4 (drafting), 6 (SEO), 7 (QA) 2, 5, 8
Product descriptions 4 (drafting), 6 (SEO) 5, 7
Landing pages 3 (framework), 4 (drafting), 6 (SEO) 2, 5, 7, 8
News articles 4 (drafting), 6 (SEO) 2, 5, 7, 8
Technical documentation 4 (structure), 6 (SEO) 2, 3, 5, 7, 8

The 8-Stage Workflow

Stage 1: Strategic Planning - Use AI Content Advisor to analyze existing content and identify gaps - Generate content briefs based on keyword research and competitive analysis - Map content to user journey stages - Define success metrics (traffic, engagement, conversion)

Stage 2: Research & Preparation - Leverage RAG (Retrieval Augmented Generation) to analyze existing site content - Use vector search to identify related content and avoid duplication - Extract key facts, statistics, and quotes using AI summarization - Validate source credibility and freshness

Stage 3: Content Framework Selection - Choose appropriate framework (AIDA, PAS, BAB, Inverted Pyramid, Storytelling) - Define tone, voice, and target audience - Set content structure and required sections - Establish word count and depth targets

Stage 4: AI-Assisted Drafting - Use AI Automators or CKEditor AI for initial content generation - Apply selected framework to structure content - Generate field-level content (titles, summaries, tags) - Create multiple variants for A/B testing

Stage 5: Human Review & Enhancement - Review AI-generated content for accuracy and brand alignment - Add unique insights, examples, and expert perspective (E-E-A-T) - Refine tone and ensure natural language flow - Fact-check AI-generated claims

Stage 6: SEO Optimization - Generate optimized metatags (title, description, Open Graph, Twitter Cards) - Create structured data markup - Optimize heading hierarchy and keyword placement - Generate alt text for images

Stage 7: Quality Assurance - Apply 4 C's framework (Clear, Concise, Compelling, Credible) - Run AI Content Advisor for improvement suggestions - Check readability scores and reading level - Validate links and references

Stage 8: Publishing & Discovery - Enable AI-powered content recommendations - Configure chatbots with RAG for content discovery - Monitor AI search rankings and discovery patterns - Iterate based on performance data

Pattern

// Stage 1: AI Content Advisor analysis
$advisor = \Drupal::service('ai_content_advisor.analyzer');
$recommendations = $advisor->analyzeContent($node);

// Stage 2: RAG-based research
$vdb = \Drupal::service('ai.vdb_provider');
$related_content = $vdb->proximitySearch($query_embedding, 10);

// Stage 4: Automator-based drafting
// Configured via UI at node type field settings

// Stage 6: SEO automation
// AI SEO Automator generates metatags on save

// Stage 7: Quality check
$quality_score = $advisor->assessQuality($node, [
  'readability' => TRUE,
  'completeness' => TRUE,
  'seo_optimization' => TRUE,
]);

Common Mistakes

  • Wrong: Skipping human review (Stage 5) → Right: AI-generated content requires human verification for accuracy and brand alignment; publishing raw AI output risks factual errors and tone mismatches
  • Wrong: Over-automating creative content → Right: Personal stories, thought leadership, and unique insights cannot be AI-generated; reserve automation for tactical, data-driven content
  • Wrong: Not monitoring AI content performance → Right: Track AI-generated content separately to measure ROI and identify optimization opportunities
  • Wrong: Ignoring E-E-A-T in Stage 5 → Right: Search engines prioritize Experience, Expertise, Authoritativeness, Trustworthiness; add human expertise signals
  • Wrong: Using same framework for all content → Right: Match framework to content type and audience; not all content benefits from AIDA or storytelling

See Also