Author :
PC
You’ve watched the ads from vibe coding platforms that show people prompting their way to an amazing product. Possible, but not always the case. What actually happens is people produce a minimum viable product (MVP), and then try to get customers using it. That’s when the pain begins.
Three months in, a customer asks how secure their information is. A simple audit reveals security holes: files exposed on the web, databases not secured. Rescue work on these projects reportedly runs into the tens or hundreds of thousands of dollars per project. This happens because the agents used for vibe coding rush to create a prototype. They don’t consider security, scaling, or maintenance unless you specifically bake those things in.
The result is technical debt — the things that were rushed through and will eventually need fixing for the product to keep working. According to Vexlint, in 2025 they estimated that nearly 8,000 vibe-coded apps would need to be properly re-engineered, at a cost of $50k to $500k each.
The builders who avoid this aren’t faster prompters. They spend time understanding what they’re building before they ask AI to build it. In practice, that means a few things before the first real prompt: work through a conceptual design, consider what systems and processes you’ll need, and settle on a consistent naming convention. Write one paragraph that says what you’re building, what the hard part is, and what you’re deliberately not building. Get your work into your own hands early, so you can see what’s actually there rather than trust the preview.
Lean into frameworks and open-source tools that are battle-tested. Design and implement core authentication, data persistence, validation, and payments upfront — these are concepts that work the same way whichever service or language you pick. If you change your mind about a feature, go back to the start rather than build on top of what’s already there. Changing your mind after the fact is reliably expensive, but it’s a cost you can avoid entirely by tackling these decisions up front.
Over the years spent helping people build skills for a tech career, the thing we know helps most is a good mentor. A good mentor does this work with you as you go — asking “show me what the AI gave you, and what you changed” before a small decision becomes an expensive one. That’s the role mentors play in the Tech Solopreneur Accelerator. Since 2019, we’ve built an extensive network of mentors to guide candidates.
Even Andrej Karpathy, who coined the term “vibe coding”, hand-built his most ambitious recent project rather than prompting it, because the work was novel enough that AI had little to draw on. That’s the real boundary: AI is strongest on familiar ground, and the less familiar your idea, the more the thinking has to come from you.
None of this is a reason to hold back. It’s a reason to start well. The founders who get furthest are the ones willing to slow down for the unglamorous parts, and to bring someone else into the room when they hit the edge of what they know. That’s a far better place to build from than a perfect prompt ever was.