Building & Product

How founders use AI for Vibe Coding

4 questions founders actually ask, each with a straight answer and the resources worth your time.

Why can non-technical founders now build software with AI? #

AI coding tools can now turn a plain-English description, "build me an app that does X", into working software, and you improve it by chatting, not by writing code. This became real in 2025 when models got good enough that ex-OpenAI researcher Andrej Karpathy named the practice "vibe coding," and it's not a toy: Y Combinator reported that for a quarter of one recent batch, 95% of the code was written by AI. In practice, the skill that matters has shifted from knowing how to code to knowing exactly what you want and describing it clearly.

What tools should I start with (Cursor, Claude Code, Lovable, Replit, Bolt, v0)? #

Start with a browser-based app builder, Lovable, Bolt, Replit, or v0, because you just type what you want and get a working, hosted app with no setup; they're perfect for prototypes and simple MVPs. Cursor and Claude Code are more powerful (they work on real code on your computer) but assume some comfort with developer concepts, so graduate to them when your product outgrows the simple builders. The good news: the workflow is nearly identical across all of them, so picking "wrong" costs you little, master one and you can switch easily.

How do real founders ship an MVP with AI in days instead of months? #

The pattern that works: write down exactly what the product should do (a short spec), let the AI build one small piece at a time, test each piece yourself like a user would, and save your progress constantly so you can undo bad changes. Founders who do this ship working products in a weekend, from Pieter Levels' flight simulator that hit $1M ARR in 17 days to a solo founder who built and sold an $80M company in six months. The speed comes from skipping nothing except the code-writing: you still do the thinking, scoping, and testing.

What are the limits, when do I still need a real engineer? #

AI gets you roughly 70% of the way, a working demo fast, but the last 30% (security, handling real user data, payments, performance at scale) is where non-technical founders hit a wall, because you can't judge whether the AI's code is safe or fragile. The failure modes are real: leaked API keys, security holes, and in one famous 2025 incident an AI agent deleted a company's production database. A good rule: vibe-code freely for prototypes and internal tools, but bring in an experienced engineer (even part-time) before you take real customers' money or data, and always keep backups and version control.