| Understand the AI module architecture and plugin system |
AI Module Architecture |
Use AI module architecture knowledge before implementing any AI functionality. Understanding the provider layer, model types, and plugin system is essential for choosing the right approach for your use case. |
| Choose and configure an AI provider (OpenAI, Anthropic, etc.) |
AI Provider Configuration |
Configure AI providers before using any AI features. Use provider configuration when you need to establish authentication, model access, rate limits, and operational settings for AI services. |
| Implement structured content workflows |
AI Content Workflow |
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. |
| Apply content frameworks (AIDA, PAS, BAB) |
Content Framework Patterns |
Use content frameworks to structure AI content generation. Choose frameworks based on content goals: persuasion, information delivery, storytelling, or education. |
| Set up AI automators for content fields |
AI Automator System |
Use AI Automators when you need consistent, automated content generation for specific fields without custom code. Use for field-level automation triggered on entity create or update. |
| Generate optimized metatags and descriptions |
SEO with AI |
Use AI-powered SEO automation to generate optimized meta tags, descriptions, structured data, and content that ranks well in both traditional search engines and AI-powered discovery tools (ChatGPT, Perplexity, Google SGE). |
| Use AI in CKEditor for in-editor assistance |
CKEditor AI Integration |
Use CKEditor AI integration for in-editor AI assistance. Use when content creators need real-time content generation, rewriting, and enhancement without leaving the editing interface. |
| Ensure content quality and consistency |
Content Quality & Review |
Use AI-powered quality review to ensure consistency, readability, and effectiveness across all content. Use the 4 C's framework (Clear, Concise, Compelling, Credible) for structured quality assessment. |
| Set up vector databases for semantic search |
Vector Databases & RAG |
Use vector databases for semantic search, content similarity analysis, and RAG (Retrieval-Augmented Generation) workflows. Use when you need to find conceptually similar content, power AI chatbots with site context, or analyze content… |
| Implement RAG for content intelligence |
Vector Databases & RAG |
Use vector databases for semantic search, content similarity analysis, and RAG (Retrieval-Augmented Generation) workflows. Use when you need to find conceptually similar content, power AI chatbots with site context, or analyze content… |
| Secure AI integrations and API keys |
Security & Privacy |
Security and privacy considerations are MANDATORY for all AI integrations. Every prompt, API call, and data flow must be evaluated for potential vulnerabilities and data exposure. |
| Optimize performance and manage rate limits |
Performance Optimization |
Performance optimization is critical for AI features because API calls are slow (1-30+ seconds) and expensive. Optimize from day one to prevent poor user experience and cost overruns. |
| Avoid common mistakes |
Common Anti-Patterns |
Learn from common mistakes to avoid technical debt, security vulnerabilities, poor user experience, and cost overruns. Every anti-pattern includes WHY it's problematic. |