AI Folio
A proof-of-concept AI tools directory built during an internship, focusing on data aggregation, SEO, and performance using Next.js SSR and ISR.
Timeline
1 week
Role
Frontend Developer
Team
Solo
Status
CompletedTechnology Stack
Key Challenges
- Aggregating AI tool data from third-party sources
- Designing a scalable data structure for AI tools
- Implementing SEO-friendly dynamic pages
- Balancing SSR and ISR for performance and freshness
- Building a clean UI within internship timelines
Key Learnings
- Next.js rendering strategies (SSR & ISR)
- SEO-first frontend development
- Open Graph and metadata handling
- Working with external AI data sources
- Building proof-of-concept products efficiently
AI Folio: AI Tools Directory (POC)
Overview
AI Folio is a proof-of-concept AI tools directory built during my internship to explore how curated AI platforms can aggregate, present, and optimize the discovery of AI tools at scale.
The project prioritizes performance, SEO, and data structure over complex UI interactions.
What Users Can Do
- Browse a curated list of 100+ AI tools
- Search tools through a fast and minimal interface
- View detailed tool pages with structured metadata
- Share SEO-optimized pages with rich Open Graph previews
- Experience fast page loads using SSR and ISR
Why This Project Was Built
This project was created to validate:
- Aggregation of AI tool data from external sources
- SEO-friendly page generation at scale
- Performance impact of different Next.js rendering strategies
It was intentionally scoped as a POC rather than a long-term product.
Data Source & Architecture
- AI tool data is sourced from Hugging Face Spaces
- Data is normalized for consistent rendering
- Server-Side Rendering is used for dynamic routes
- Incremental Static Regeneration is used for scalable content pages
This architecture balances freshness, performance, and crawlability.
SEO & Metadata Focus
AI Folio was designed with search visibility in mind:
- Dynamic meta tags for each tool
- Open Graph metadata for social sharing
- Indexable, crawl-friendly detail pages
- Optimized structure for AI-related search queries
Tech Stack
- Next.js
- TypeScript
- Tailwind CSS
- Hugging Face Spaces
- SSR & ISR
- SEO & Open Graph metadata
Key Takeaways
- Proof-of-concept projects should focus on architectural clarity
- Rendering strategies directly affect performance and SEO
- Clean data models simplify frontend logic
- Not every project needs extensive feature sets to be valuable
After Build & Impact
- Strengthened understanding of content-driven Next.js applications
- Gained hands-on experience with SSR and ISR
- Improved ability to design SEO-optimized frontend systems
- Learned to execute focused projects under real-world constraints
Future Improvements
No planned enhancements.
This project served its purpose as a proof-of-concept to validate ideas and architectural decisions.