I. The Challenge
The editorial team was spending 15+ hours per week manually categorizing, tagging, and organizing content across multiple publications. Content discovery was inefficient, with readers unable to find relevant articles across the growing archive of 10,000+ pieces.
II. The Solution & Architecture
Designed and implemented an AI-powered publishing platform that automates content categorization and enables semantic search across the entire content library.
System Architecture
Sanity CMS
Headless CMS for editorial workflow
OpenAI Integration
AI-assisted tagging & summarization
↓
Algolia Indexing
Syncs structured content for instant retrieval
↓
Next.js Frontend
Consumes Sanity via GROQ & Algolia search
Netlify Deployment
Globally distributed static build
III. Technology Stack
Frontend & Framework
- Next.js 14 (App Router)
- React Server Components
- TypeScript
AI & Search
- OpenAI GPT-4 API
- Algolia Semantic Search
- Vector Embeddings
Content & Asset Management
- Sanity Headless CMS
- Content Schema
- Youtube Trending API
Infrastructure
- Vercel Deployment
- Edge Functions
- CDN Optimization
IV. Results & Impact
50%
Reduction in editorial workload through automated categorization
3x
Increase in content discovery with semantic search
<200ms
Average article search response time
95%
Accuracy in AI-generated tags and summaries
Key Learnings
- •Implementing prompt engineering best practices reduced AI hallucinations by 80%
- •Algolia's vector search required careful index optimization for relevance/performance balance
- •Building a feedback loop for editors improved model performance over time
