Everyone is using AI to build software now. Cursor, Claude, v0 and these tools are genuinely good. However, I keep seeing people use AI to build faster, and end up building the wrong thing faster. The problem is people try to build too much. Someone comes in with a 47 feature idea, AI makes it feel achievable, so they try to build all 47. Six weeks later they’ve burned through budget, have tons of errors and the core feature still hasn’t been proven. The ones who actually ship something useful with AI do one thing differently. They strip it down to the core user flow first. One problem. One solution. Does it work? Good. Now build the next and grow based on user feedback. So how does this look when you’re hiring a software engineer rather than just prompting AI tools? Same principle. You want someone who isn’t starting from zero on the basics. Login, payments, user accounts, notifications…these are solved problems. If an engineer is billing you hours to set up auth or wire up Stripe for the first time, that’s the same problem as using Lovable to build all 47 features. The right engineer brings the foundation with them and uses AI on top of it. AI or human, the logic is the same. Budget should be spent on the unique core features. Build small. Prove the core. Go from there. Happy to answer questions if you’re fighting with AI trying to build a 45+ feature MVP and keep hitting walls. :D submitted by /u/Ejboustany
Originally posted by u/Ejboustany on r/ArtificialInteligence
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