Lluis Jover

I pick AWS Lambda because it offers this effortless, automatic scalability that's tough to beat. I never have to worry about provisioning or managing servers; Lambda just instantly scales my application to handle anything from a few requests to massive traffic spikes, and I only pay for the compute time I actually use.

I prefer Vercel for deploying my Next.js apps (and other frontend frameworks too!) because of its native integration, those instant deployments on every git push, built-in serverless functions, and a global CDN that keeps things fast everywhere. Honestly, it's just way simpler to manage than setting up a server myself.

I like Next.js over other options because it makes setting up server-side rendering (SSR) and static site generation (SSG) incredibly simple. Its file-based routing system just clicks for me, and the ecosystem built around Vercel (the creator) makes deployments and serverless functions a breeze.

I prefer PostgreSQL because it's just such an incredibly robust and versatile relational database that I trust. The huge advantage, especially for AI and search stuff lately, is the pgvector extension. It lets me store and run similarity searches on vector embeddings right inside my main relational database, totally avoiding the complexity of managing a separate vector database system. It feels like having the best of both worlds in one reliable platform.

I choose Langchain because it provides these really helpful abstractions and modular tools that simplify building complex workflows with language models. Things like chaining API calls, working with vector databases (RAG), and managing conversation memory become much more straightforward. It just makes experimenting and prototyping LLM-based applications way faster than building everything from scratch.