Peter H. Diamandis

Because we had to rewrite it because generative AI came out towards the end.

But this third book was three months, right?

And because there was so much, every contributor could use an AI, add more data to it, more help to it, add their methodology to it, and then boom, you're off to the races.

So the second domain where this has fully happened, by the way, is marketing and content generation, right?

We used to have, it was agency heavy, then it was AI assisted, and now it's AI native.

Right, and so we can see certain verticals hitting this spot in a particular way.

So let me go into the rewriting methodology.

We call this methodology rewrite.

Okay.

And I wanna go into a little bit of detail so people understand the specific steps that are involved in this.

So you have a workflow like invoice processing and you're gonna start moving workflow over.

Before you do any of that, you have to do a backcasting exercise.

Backcasting is a methodology in future studies and forecasting where you pick what the vision looks like.

Say Elon wants to get to Mars, you could say, okay, I want to get to Mars in seven years.

In order to get to Mars in seven years, where do I have to be in five years?

Where do I have to be in three years?

And now you have your roadmap.

If you start from the starting point and go, I want to get to Mars, you've no idea what you're doing, how you're going to get there, et cetera.

Backcasting has turned into a very powerful methodology.

So step one is take your company, so let's say it's that trucking company or retail company that I used earlier, and say, okay, in this future world, what does that company look like, fulfilling its MTP and its architecture in an AI native-centric way, and you paint that picture.