Q: Where should I deploy an AI app — Hugging Face Spaces, Vercel, Render, or AWS?

Think of it as a ladder, and climb it in order.

Hugging Face Spaces is the demo step: made for showing AI projects, integrates with Gradio (the UI library most AI tutorials use), and puts your app at a public URL quickly. Its free tier has grown more restrictive over time, so treat it as a demo shelf, not a home.

Render is the simple hosting step. It deploys from your GitHub repository and runs your Python app on an always-on server. Free and cheap tiers exist, and it behaves like real hosting with none of the setup burden.

Vercel is the product step. It's built for modern web applications: a polished frontend, user accounts, payments, real-time streaming. This is where your project stops looking like an exercise and starts looking like a product someone would pay for. Its serverless model has execution time limits, so long-running agent jobs live better elsewhere.

AWS is the production step, and the one that matters most for your career. It's where companies actually run their systems: Docker, serverless functions, monitoring, security, scaling. AWS deployment experience is what turns a portfolio project into evidence you can do the job, which is why it appears in so many AI Engineer job descriptions.

Deploy early on the easy rungs, but don't stop there. The engineers who stand out are the ones whose projects run on the infrastructure employers actually use.