Peter H. Diamandis

So how do you balance that out?

Okay, so now you have these layers of agents, purpose agents, sensing agents, interpretation agents, deciding agents.

Next level is an orchestration agent.

So let's say the decision agent comes back and says, we should buy a startup that's doing this, right?

And then now the orchestration is saying, okay, we got to set up a set of functions to go find a bunch of startups, analyze whether which ones are ready for M&A, tell the corporate dev team, get the lawyers ready, et cetera.

Get the legal agents ready.

And then finally a learning loop where did we buy another company before and did it work out or not?

Right.

And how did that work out?

And all wrapped up in this governance thing.

So that's the kind of an example of how you would flow through these.

And at the core is this engine recursive learning.

Another way to think about the organizational singularity is when you can have recursive self-improvement at the workflow level.

Okay.

So if you took say invoice processing and you have right now, all these human checkpoints of yes, did the goods arrive?

Should we, who's the, does the supplier exist in our systems?

Is there a legal contract?

There's a human checking all those things.

Maybe you have an ERP system that's automated one or two of these layers, but now you can have the whole thing done.

And then an agent can say, well, how would I make this better every loop?