The speaker's brother built an MVP in two days with AI instead of two months. His own programmers use AI for rough outlines and schemas, then fix and improve them, saving time but requiring significant manual work as complexity grows.
So let's talk about a couple different other areas where we can use AI and what's going on with it. So number one, I want to talk about programming. My brother is deep into, into using AI tools and he's been building, he's been building some test products, having the AI build it for him, and he says it's cut our time to building a minimum viable product from two months to two days. Like, that's super awesome. I keep pushing my programming team to try and use AI tools in their, in their code writing and they keep coming back and saying this is not great. And that's as far as I'm going to go with it. I have tested it towards creating an outline for a software system and it did a really good job towards creating a database schema for a software system. And it did a really good initial job of it. And then I was able to look at it and be like, okay, well this and this and this are wrong, or this and this and this need to be changed. These things can be fixed. We can build on it here. Like, and the more, the more I gave it, the more complicated the system got, the worse the design improved. Now is that going to change with AI? I don't know. But with my programmers using that, what they're doing right now to help them is getting an initial piece from it and then doing the actual work. So in that case it's saving them time.
Stop Being the Dispatcher, Start Being the CEO: How to Scale Your Field Operations 🛠️
