Jake

in order to give the answer. This is called chain of thought. Right. And this is the underlying mega model that sits on top of the LLMs. And the mega model, effectively, the chain of thought approach is the model asks itself the question, how should I answer this question? Right. And then it comes up with an answer.

And then it says, now, based on that, what are the steps I should take to answer the question? So the model keeps asking itself questions related to the structure of the question that you ask. And then it comes up with a series of steps that it can then call the LLM to do to fill in the blanks, link them all together and come up with the answer.

And then it says, now, based on that, what are the steps I should take to answer the question? So the model keeps asking itself questions related to the structure of the question that you ask. And then it comes up with a series of steps that it can then call the LLM to do to fill in the blanks, link them all together and come up with the answer.

It's the same way that a human train of thought works. And it really is the kind of, ultimate evolution of what a lot of people have said these systems need to become, which is a much more, call it intuitive approach to answering questions rather than just predictive text based on the single statement you made. And it really is changing the game and everyone is going to chase this and follow this.

It's the same way that a human train of thought works. And it really is the kind of, ultimate evolution of what a lot of people have said these systems need to become, which is a much more, call it intuitive approach to answering questions rather than just predictive text based on the single statement you made. And it really is changing the game and everyone is going to chase this and follow this.

It is the new paradigm for how these AI kind of systems will work.

It is the new paradigm for how these AI kind of systems will work.

By the way, it's not just call centers. I had a conversation with, I'm on the board of a company with the CEO the other day. And he was like, well, we're gonna hire an analyst that's gonna sit between our kind of retail sales operations and figure out what's working to drive marketing decisions. And I'm like, no, you're not.

By the way, it's not just call centers. I had a conversation with, I'm on the board of a company with the CEO the other day. And he was like, well, we're gonna hire an analyst that's gonna sit between our kind of retail sales operations and figure out what's working to drive marketing decisions. And I'm like, no, you're not.

Like, I really think that that would be a mistake because today you can use O1 and describe, just feed it the data and describe the analysis you wanna get out of that data. And within a few minutes, and I've now done this probably a dozen times in the last week with different projects internally at my company,

Like, I really think that that would be a mistake because today you can use O1 and describe, just feed it the data and describe the analysis you wanna get out of that data. And within a few minutes, and I've now done this probably a dozen times in the last week with different projects internally at my company,

it gives you the entire answer that an analyst would have taken days to put together for you. And if you think about what an analyst's job has been historically is they take data and then they manipulate it.

it gives you the entire answer that an analyst would have taken days to put together for you. And if you think about what an analyst's job has been historically is they take data and then they manipulate it.

And the big evolution in software over the last decade and a half has been tools that give that analyst leverage to do that data manipulation more quickly, like Tableau and R and all sorts of different toolkits that are out there. But now you don't even need the analyst because the analyst is the chain of thought. It's the prompting from the model.

And the big evolution in software over the last decade and a half has been tools that give that analyst leverage to do that data manipulation more quickly, like Tableau and R and all sorts of different toolkits that are out there. But now you don't even need the analyst because the analyst is the chain of thought. It's the prompting from the model.

And it's completely going to change how knowledge work is done. Everyone that owns a function no longer needs an analyst. The analyst is the model that's sitting on the computer in front of you right now. And you tell it what you want. And not days later, but minutes later, you get your answer. It's completely revolutionary in...

And it's completely going to change how knowledge work is done. Everyone that owns a function no longer needs an analyst. The analyst is the model that's sitting on the computer in front of you right now. And you tell it what you want. And not days later, but minutes later, you get your answer. It's completely revolutionary in...

ad hoc knowledge work as well as kind of this repetitive structured knowledge work.

ad hoc knowledge work as well as kind of this repetitive structured knowledge work.

There's probably also an aspect of this that we can't predict what is going to work with respect to data structure. So right now, all of... all of the tooling for AI is on the front end.