Taste, Judgment and Scale - Season 5: Episode # 98

Yeah, you know, I as I've been going to dive into what everyone's been diving into, which is which is AI and how do you particularly how do you how do you bring in AI into the go to market motion function? I think it's the go to market game is definitely changing in real time in front of all of us.

And so like keeping up with that is has been really exciting.

It feels like the early days of like the sales loft and outreaches of the world where we're trying to figure out the SDR game.

Now it's like, how do we figure out this AI game? But one thing I've really noticed is there's a lot of conversation that we're starting to see around like the context layer, which I think is really smart, right? In order for you to have an effective workflow, like an intent workflow for sales organization, like you have to have great context, right? And for me, the way I think about all these layers is like there's the data layer.

Got to make sure that you have the right data to support whatever outbound or whatever motion that you want to enable within the organization.

And then now you're hearing a lot of this other layer, which is the context layer.

Well, the agents or your agentic workflows have to have context of who you are, who your buyer is, what's the pain that they have, what's the pain that you solve, and how does it piece all the context together to then the end result, like send out a message that's relevant to them.

But the one layer that kind of sits on top of those two that I have been really working on that not a lot of people are talking about, you're starting to see it more often, really is that taste layer or what I call the judgment layer, which is how do we bring our own judgment from our experience, right? And there's a lot of nuance in terms of what we do in our roles that...

hasn't really been documented or provided anywhere for any kind of agentic system with an agent workflow to actually understand what does good look like.

And so now what you're seeing, we all see it, right? It's all over LinkedIn.

It's all over the emails we get is we have this style of writing that where it sounds very common and everyone sounds like it, where it's written by AI, right? And it's missing that judgment layer of like what actually looks good.

And so it's really easy to understand and cap and catch when someone's using AI to write something, whether it's a call script, whether it's an email or marketing content, whatever the case might be.

So for me, I'm spending a lot of time in that.

taste layer, because I think that is where as organizations, we start to build our own moat and defensibility is, is going to be unlocking that judgment layer.

And so that's, that's where I like to spend most of my time today.

That's super interesting.

Are you thinking about that through the lens of the common LLM solutions, like a chat GPT or a cloud, or are you thinking about this in terms of like bringing in your own, you know, AI solutions into an organization? Like when you're talking to customers, what's the, what's the angle?

It's just what an organization has.

We're not looking at bringing in our own AI solutions, right? I think whether I bring in – we bring in our own or they have their own, you're still going to have the same problem because with a judgment, where that resides, it resides in people.

It resides in our brains.

It resides in our experience.

And so how do you actually extract that from the individual? or the organization to where you can actually document it, right? So now you have these, call them rules, if you would, that the AI needs to follow to understand what it's going to look like.

What are the things that you shouldn't do? What are the things that you should do that looks good, right? What they get the taste.

You have to bake that into what you're doing.

And I think that's the hard part.

Yeah, you know, I as I've been going to dive into what everyone's been diving into, which is which is AI and how do you particularly how do you how do you bring in AI into the go to market motion function? I think it's the go to market game is definitely changing in real time in front of all of us.

And so like keeping up with that is has been really exciting.

It feels like the early days of like the sales loft and outreaches of the world where we're trying to figure out the SDR game.

Now it's like, how do we figure out this AI game? But one thing I've really noticed is there's a lot of conversation that we're starting to see around like the context layer, which I think is really smart, right? In order for you to have an effective workflow, like an intent workflow for sales organization, like you have to have great context, right? And for me, the way I think about all these layers is like there's the data layer.

Got to make sure that you have the right data to support whatever outbound or whatever motion that you want to enable within the organization.

And then now you're hearing a lot of this other layer, which is the context layer.

Well, the agents or your agentic workflows have to have context of who you are, who your buyer is, what's the pain that they have, what's the pain that you solve, and how does it piece all the context together to then the end result, like send out a message that's relevant to them.

But the one layer that kind of sits on top of those two that I have been really working on that not a lot of people are talking about, you're starting to see it more often, really is that taste layer or what I call the judgment layer, which is how do we bring our own judgment from our experience, right? And there's a lot of nuance in terms of what we do in our roles that...

hasn't really been documented or provided anywhere for any kind of agentic system with an agent workflow to actually understand what does good look like.

And so now what you're seeing, we all see it, right? It's all over LinkedIn.

It's all over the emails we get is we have this style of writing that where it sounds very common and everyone sounds like it, where it's written by AI, right? And it's missing that judgment layer of like what actually looks good.

And so it's really easy to understand and cap and catch when someone's using AI to write something, whether it's a call script, whether it's an email or marketing content, whatever the case might be.

So for me, I'm spending a lot of time in that.

taste layer, because I think that is where as organizations, we start to build our own moat and defensibility is, is going to be unlocking that judgment layer.

And so that's, that's where I like to spend most of my time today.

That's super interesting.

Are you thinking about that through the lens of the common LLM solutions, like a chat GPT or a cloud, or are you thinking about this in terms of like bringing in your own, you know, AI solutions into an organization? Like when you're talking to customers, what's the, what's the angle?

It's just what an organization has.

We're not looking at bringing in our own AI solutions, right? I think whether I bring in – we bring in our own or they have their own, you're still going to have the same problem because with a judgment, where that resides, it resides in people.

It resides in our brains.

It resides in our experience.

And so how do you actually extract that from the individual? or the organization to where you can actually document it, right? So now you have these, call them rules, if you would, that the AI needs to follow to understand what it's going to look like.

What are the things that you shouldn't do? What are the things that you should do that looks good, right? What they get the taste.

You have to bake that into what you're doing.

And I think that's the hard part.