Building with AI: Prototype v.s. Production-grade

What differentiates a prototype and a production app built with the help of AI?

Honestly, I’d say: a prototype remains a prototype until it starts making money, then suddenly, it’s a production app.

Tongue-in-cheek, yes, but it’s also very YC: make something people want. That motto has never felt more alive than today. We’ve entered the age of permissionless building, where anyone can spin up something real without waiting for approvals, investors, or even a team.

Like how we Singaporeans might put it, "last time need whole team, now one-man show can already."

This isn't something spoken in hype with all the AI advancements moving at the speed of private equities (oh, and my government's sovereign fund) hosing out streams of cash to AI companies. I spent most of August 2025 building an elaborate data management platform, solo. Zero developers, just me, Claude, and GPT-5.

The experience? One word: scary.
Scarily fast. Scarily cheap.

What used to take a year of full-stack dev work and a million-dollar burn rate… can now be done in days, for a few hundred dollars. The shift is mind-bending compared to just three years ago.

And it’s not only AI coding at warp speed. Platforms like Vercel, Convex, Posthog, Clerk — they’ve made infra, auth, and observability practically one-click. A whole stack that used to be painful is now damn shiok.

But here’s the thing: speed alone doesn’t mean much. All this acceleration only matters if it helps us learn faster; Whether we’re solving the right problem, whether we’re building the right thing, and ultimately, whether the market even cares.

And that’s the real line between prototype and production: not the polish, not the infra, not the AI magic… but whether it proves its worth in the wild.