If you're interested in the project, check out the repository
github.com/vorillaz/net... and the full walkthrough on my website
vorillaz.com/netflix-but-...

The data comes from Kangle's Netflix dataset, which was backported to the database.
I then used the Vercel AI SDK with Mistral to generate embeddings and metadata for the shows.

`pgvector` and `pg_trgm` extensions are used for vector search and full-text search, respectively.

The initial idea was inspired by
@tej.as's talk on building RAG apps with Datastax and Langflow. The project also drew inspiration from
@leerob.com 's book inventory.

The app is built using Next.js, Shadcn UI, Tailwind, and Postgres, powered by Neon.

A working example can be found on my GitHub https://github.com/vorillaz/nextjs-rendering

Full demo is also available https://nextjs-rendering-demo.vercel.app/

Tips:
- Use Static for marketing pages.
- Dynamic for user dashboards.
- Streaming for complex layouts.

Performance Impact:
- Static: Fastest initial load
- Dynamic: Slowest but fresh
- Streaming: Fast initial + smooth updates
- PPR: Fast initial + optimized dynamic parts per layout or page

🌊 Streaming
Progressively sends UI pieces to the browser. Think loading states, then content. Great for complex pages where some parts are faster to load than others.

🔄 Dynamic Rendering
Content generated fresh on each request. Ideal for personalized pages or real-time data. Slower than static, but always up-to-date.

🚀 Static Rendering (Default)

Pages are built at build time and cached. Perfect for content that doesn't change often, like blog posts or docs. Super fast because everything's ready to serve.

Summoning my friend and amazing coach @sugarenia.com . I am pretty sure you will keep your kidneys in place :)