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Hey everyone!

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Today I'm

super excited to be talking to Ian Craft.

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He's the founder and chief

futurist at Signal and Cipher,

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and he is an absolute thought leader

when it comes to the intersection

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of AI and enterprises

that we all work for.

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He has so many deep, amazing insights.

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I had the chance

to watch a number of his keynotes at South

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by Southwest recently,

and it just never ceases to amaze me

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how much new thought leadership

he brings to the table here.

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So I'm really excited to pick his brain

to understand

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how much of this new technology

is really being limited by us

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and our own boundaries,

and how we can break through that.

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It should be an amazing conversation.

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I've been a big fan of, of your keynotes.

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I've been bingeing them

in the last couple of days.

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One of the quotes that I wrote down,

I don't remember

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if, is from South by Southwest this year

last year, but as I was bingeing,

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one of the quotes I wrote

down was poor leadership,

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adherence to old systems and technology.

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First, mindsets are a bigger risk

than AI to organizations.

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What is going on out there?

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And can you kind of dissect that quote?

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Yeah, absolutely.

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So it to me,

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when we go through times of change,

we need to galvanize behind something.

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And that happens

both productively and disruptive.

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We tend to find something

to create opposition towards.

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And for a lot of people, they see AI

as the main threat because it is the

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easiest thing to point to and say,

that's a threat to my job.

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I look at that and I see very clearly it's

automating pieces of what I do,

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and that becomes extractive.

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It's taking something

that basically I provided

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value through that thing before

and I no longer do.

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And because of that, I as an individual

are less valuable to that organization.

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Now, if I'm continuing as a leader

to just say

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my goal is to create efficiency and scale

within the system that we have today,

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the typical lever we're going to pull

is efficiency, which is code for layoffs.

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And that is essentially how our system

is operated for the last hundred

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and 50 years.

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And it's been able to grow.

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We've been able to create prosperity

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in a number different ways,

but that systems changing now, the era

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of unending exponential growth,

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in existing paradigms,

is starting to fray at the seams.

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And when we think about the future

through the lens of the past,

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what we do is we apply old metrics,

old ways of thinking, old processes

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to new technologies, new ways

of working, and new challenges.

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And those things come together

and they don't work.

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But when leaders are so fixed in

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how they want to approach these things,

they're not thinking

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about how this is different

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and how they have to take a

different paradigm or a different approach

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to this new type of challenge

and new type of circumstances.

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And that's what leads to the demise

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of the organization,

not just that employee or that department.

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Right.

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So I want to

I want to zoom in on two different phrases

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you use there

that I think are really important.

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You talked about, shoot.

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Now I'm going to screw it up,

but you talked about,

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you know, growth and the ability for us

to have these, you know, productivity

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improvements and, and be thinking about

what we're doing differently.

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And you also said efficiency

and efficiency has become a really,

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popular word these days.

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You know,

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efficiency is something,

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you know, across the public sector,

across the commercial sector.

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You know, I've very hot word

to what degree is efficiency

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the right thing to be looking at right now

or a distraction from what's

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actually going to help us?

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Yeah, I think there's a balance here.

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There's a recognition that organizations

have a duty to their stakeholders

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and their stockholders, and that means

you have to look for efficiencies.

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And if you're not,

that's a dereliction of that obligation.

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Understandable. Right.

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So they should be looking at efficiency

and they should be looking

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at increasing productivity.

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But to do so with the same fervor

we have over the past several decades

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since the beginning

of the digital revolution,

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I think is absolutely, incredibly

shortsighted, because what this does

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is this doesn't just scale in individuals

efficiency and effectiveness.

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This changes the fundamental boundaries

of what jobs and tasks are.

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We're really, we're reengineering

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or completely changing

what the atomic unit of work looks like.

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So, for example, we take a look

at organizations as built from people,

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which are defined for jobs, very specific

slotted roles that are well defined.

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And if I look at an org chart

of any organization, I had these mental

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shortcuts that I can use to understand

who does what, where and how.

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All of that starting to change, though,

because I makes it

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so that I don't actually have to stick

within the boundaries

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of a specific role and say,

that's all you do.

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If you're accountant number two,

you know, in the finance department or

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whatever that,

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designation

might mean to a specific organization,

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you have a very specific set of roles,

responsibilities, KPIs, and remit

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that you are responsible for

what happens with I though, is it makes it

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so that the skill sets

that might sit adjacent to

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my existing skill sets or responsibilities

are now accessible to me.

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So it starts to put pressure

on these boundaries

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that we keep people in with their roles.

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So if you're just a copywriter

or just an ad,

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if you're staying within those boundaries,

now with the access to AI and generative

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AI and other toolsets, it's

also almost a, abdication

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of responsibility to say,

I'm just going to stay in my lane,

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and all of a sudden we have this chaos

that comes with people saying,

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I have access to new skill sets,

I have access to capabilities,

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but the system around me has not adapted

to really make that possible.

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Fluid and part of the system

where I'm not stepping on other people's

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toes, I'm not doing things

without permission.

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I'm not doing things without support

and an apparatus or feedback loop.

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So what's happening is

we have this new technology that allows

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all sorts of new behaviors

within the organization, right?

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But the organization has no idea

how to pull those

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behaviors and structures and processes

together.

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Right?

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It's too rigid to actually take advantage

of what this technology could unlock.

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Absolutely.

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So so what do we what do we do with that?

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Like as leaders, where do we start?

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How can we start to rethink these systems

and processes in a way

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that's more dynamic, or at least

can help us harness these possibilities?

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Absolutely.

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Well, what I would say

is, the first place you should

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look is not just about

how do I do more with less?

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You can.

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I'm not saying don't think about that,

but that shouldn't be the primary goal,

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the value you're trying to get out of AI

because that's a race to the bottom.

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Like we're all going to get that benefit.

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And if that's your focus, then you're

playing a Walmart game for, you know,

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a premium enterprise type of environment

that's not going to help anybody.

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It might give short term impact.

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So a quarter to quarter

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thinking of a Western or American style

way of doing business,

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you'll see immediate impact.

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And I think that when you take a look

at what's happening

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in the balance sheets at meta and several

other organizations, people see oh,

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less staff, higher margins,

more productivity, that's the way of it.

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They're missing a lot of what's

actually going on behind the scenes.

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So a lot of these companies that are

in the space of building the models

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and kind of changing the way they work

have seen this coming around the bend,

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and they're already restructuring

the way that they operate.

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For leaders that are trying to figure out

what this means for them,

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I would say, first of all, you need

some sort of experiential learning,

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like just understanding this stuff

theoretically, theoretically

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might have worked for the past 25 years

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because you have a lot of understanding

of how the digital paradigm works.

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This is not new digital, you know,

connected networks, all that stuff.

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We've known that since the 80s and 90s.

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This is a fundamentally different

paradigm, different way of working,

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a different way of thinking

about growth, different way of connecting,

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software and systems.

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I mean, we're literally working

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with quote unquote software

that now replicates and imitates

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cognitive processes, completely different

paradigm for people. So

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having

some sort of education or experience

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that gets you into that headspace

where you can start to grapple

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with what those changes are,

is absolutely necessary.

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Just reading articles

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and doing a couple of things

and ChatGPT is not going to be enough,

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because if you're going

to competently lead an AI transformation,

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you as a leader also need to have spent

that time immersed in that space.

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I'm not saying,

you know, hundreds of hours, but

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at least dozens in that space

to understand it with the proper guidance,

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what it's going to do for your team,

your business.

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How does it help

you answer the questions about

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what kind of value

we providing as a company?

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How do we structure our teams?

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How do we grow effectively in this market

where, you know,

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everyone else is starting to go

into these adjacent spaces as well?

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So there's a lot of new questions

that I have to answer from that.

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Yeah.

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Well, when you talk about that

experiential learning, Ian,

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do you have a sense of

like what leaders are doing?

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Like, what does that mean?

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Like what tools are they using?

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What does that look like? Yeah.

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So the most effective programs

that we've seen,

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is, are ones that are built to be used

with the same types of tools.

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They are already using their environment.

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So everyone uses Microsoft Teams,

slack, have access to ChatGPT or something

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like that, 90% of what you need to do

can be done with is in those environments,

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but just using the vanilla version of it

is not going to cut it.

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Being able to learn with these tools

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by also building the documentation,

the vision,

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the information you need to move forward

is really where we've seen the most value.

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So to give you an example of a module

that we run will work with leaders

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in an environment where they're working

with the AI to build their vision for what

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AI looks like in the organization,

to create a maturity assessment.

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So where do we stand and where's

the alignment amongst the CXOs?

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And it's not just about the education of

in AI.

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It's about alignment.

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And there's a strong difference

between agreement and alignment.

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What happens oftentimes at a leadership

level is we agree AI is important.

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We agree that we're all implementing it,

but they're not aligned

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as to how that happens or where they even

are on a maturity index.

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So having them come together

to do that together

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while using the tools to facilitate

it brings a couple of those objectives

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together, and all of a sudden

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they start to see, okay, here, here's

how the tools can facilitate this work.

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It doesn't need to take six weeks.

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It can literally take an afternoon.

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So you've taken something

that might have been a six month

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consulting engagement

and said, we're walking out in 2.5 hours

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with a much clearer understanding

of what we're doing, how we're doing it,

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who's responsible

and what that roadmap looks like.

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So that's one of the big

paradigm shifts we're seeing.

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So it's more,

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if I understand you correctly,

there's there's more value in like

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one condensed facilitated session of ask

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having the right people in the room

and asking the right questions.

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Then like a protracted engagement on like,

here's a bunch of recommendations

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of like potential use cases

and what you could be doing.

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Is that fair?

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I think the potential use case

model is kind of outdated at this point.

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So I do think that the idea of the

the thousand page Dax

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and the the long consulting engagements

need to change.

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I won't proclaim that consulting companies

are dead on arrival.

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I think that's a

there's a little hyperbole there.

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They're like advertising agencies,

like they survive this kind of stuff.

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The consulting company of the future

looks wildly different than it does today.

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But one of the things that they're often

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kind of admonished for

is this idea of a thousand page deck.

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And I do think that the idea of learning

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being separate from doing so, having

a thousand page deck, a bunch of seminars,

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and then finally being responsible

to do on your own is outdated.

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We now have the tools,

we have the apparatus to learn and do at

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the same time, while also building

some of the most essential infrastructure,

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as well as documentation

and strategy amongst executives.

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So when you walk out of a session,

you should have a clear vision.

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You should have an understanding

of how this impacts you,

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what your maturity assessment looks like

and what your roadmap looks like.

232

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So what we've come to see is that we can

take things that should take six weeks

233

00:12:18,137 --> 00:12:22,141

or even three months and condense that

into one afternoon or a full day session.

234

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Right.

235

00:12:24,276 --> 00:12:26,512

Which is which is really exciting.

236

00:12:26,512 --> 00:12:30,182

And, you know,

I think helps us get a lot more

237

00:12:30,282 --> 00:12:33,452

like just accelerate our time

to value our time to results.

238

00:12:34,053 --> 00:12:36,422

And there's a, there's a phrase

I want to talk about,

239

00:12:36,422 --> 00:12:38,824

that you've said quite a lot,

and I want to

240

00:12:38,824 --> 00:12:42,228

I want to put some parameters around it,

which is the tools.

241

00:12:42,228 --> 00:12:44,997

Right. Talking about AI and the tools.

242

00:12:44,997 --> 00:12:48,667

Because, you know, in my mind,

when we talk about AI

243

00:12:48,667 --> 00:12:50,536

and when we talk about the tools, it's

244

00:12:50,536 --> 00:12:53,139

everything from,

you know, just go to ChatGPT

245

00:12:53,139 --> 00:12:57,076

or Google and write in your question

to, you know, this world I'm finding

246

00:12:57,076 --> 00:13:02,047

we live in increasingly where like

every software vendor and their brother

247

00:13:02,047 --> 00:13:05,985

is promising you that, oh, there's

AI in this now it's an AI PC that like,

248

00:13:06,152 --> 00:13:11,624

like any crevice we can hide

AI in, we're telling you there's AI in it.

249

00:13:12,358 --> 00:13:14,760

What tools do

people need to be thinking about?

250

00:13:14,760 --> 00:13:18,631

How should we be bringing tool

wise AI into our organizations?

251

00:13:18,631 --> 00:13:23,269

Yeah, we're at the very beginning of the

development of a very robust ecosystem.

252

00:13:23,502 --> 00:13:27,673

So most people are seeing things

like ChatGPT, Claude, Copilot, etc.

253

00:13:27,673 --> 00:13:30,776

and that's kind of when people say tools,

they think of that and that's fine.

254

00:13:32,011 --> 00:13:33,813

But what we're seeing at the enterprise

level

255

00:13:33,813 --> 00:13:37,783

is a weaving of that into the basic

infrastructure across the board.

256

00:13:37,783 --> 00:13:41,187

So for a lot of people,

they're pulling in copilot, others

257

00:13:41,187 --> 00:13:44,356

they're pulling in, you know, open

AI's API into the work that they do.

258

00:13:44,757 --> 00:13:47,326

And stage one is just to get people

exposed to tools.

259

00:13:47,326 --> 00:13:49,461

So that's access to the chat bots.

260

00:13:49,461 --> 00:13:51,463

It's a 1 to 1 relationship.

261

00:13:51,463 --> 00:13:55,701

You put in an input,

you get an output that is barely silly.

262

00:13:55,768 --> 00:13:58,771

Even alpha products for an enterprise

at this point in time, like you're

263

00:13:59,071 --> 00:14:03,008

just getting your socks on before

you put your shoes on to get out the door.

264

00:14:03,475 --> 00:14:08,581

And what we're seeing with organizations

that are more successful is their leading

265

00:14:08,581 --> 00:14:11,183

with use cases

that everyone can understand,

266

00:14:11,183 --> 00:14:14,286

and then they're building that into

the infrastructure of their organization,

267

00:14:14,587 --> 00:14:17,590

not just saying,

can you go learn how to use ChatGPT?

268

00:14:17,823 --> 00:14:21,260

That's basic and necessary,

because people can't start

269

00:14:21,260 --> 00:14:22,962

to identify

what the use cases are going to be

270

00:14:22,962 --> 00:14:25,164

unless they have experienced

the technology.

271

00:14:25,164 --> 00:14:28,000

And I'm a big fan of pushing

that down and out.

272

00:14:28,000 --> 00:14:29,935

You can have people at the edges

273

00:14:29,935 --> 00:14:32,905

coming up with the use cases,

not just the people at the top,

274

00:14:32,905 --> 00:14:33,739

because the people

275

00:14:33,739 --> 00:14:37,743

who are dealing with the challenges,

who are the ones actually doing the work,

276

00:14:38,010 --> 00:14:41,013

have a much more nuanced understanding

of how it should be done

277

00:14:41,080 --> 00:14:44,083

and what success looks like

for those types of tasks and activities.

278

00:14:44,483 --> 00:14:47,820

To get there has to go way

beyond just access to ChatGPT.

279

00:14:48,754 --> 00:14:49,221

What we

280

00:14:49,221 --> 00:14:53,559

found for so many organizations is

they'll often us like, hey, we we invested

281

00:14:53,559 --> 00:14:57,196

half $1 million in ChatGPT licenses,

and people loved it at the beginning.

282

00:14:57,196 --> 00:15:00,199

And then like,

nobody uses it, it goes like this.

283

00:15:00,532 --> 00:15:02,001

It creates and then it crashes.

284

00:15:02,001 --> 00:15:03,168

As far as usage.

285

00:15:03,168 --> 00:15:05,604

And the big part of it is

you just gave them a new tool.

286

00:15:05,604 --> 00:15:09,108

You gave them barely

any training, barely any context.

287

00:15:09,174 --> 00:15:11,176

And you said amongst

all the things you're doing,

288

00:15:11,176 --> 00:15:14,513

you're overstretched, under-resourced,

your expectations are just getting higher.

289

00:15:14,513 --> 00:15:17,182

Now you have to go

learn a new way of doing things.

290

00:15:17,182 --> 00:15:19,618

There's no surprise

people are not using the tools, right?

291

00:15:19,618 --> 00:15:23,589

So it has to be very clear from

the beginning how this applies to them,

292

00:15:24,123 --> 00:15:28,627

why it's relevant, why it's going to

change their life, not the organization.

293

00:15:29,261 --> 00:15:32,264

Like really put it into terms

they can understand and grapple with.

294

00:15:33,065 --> 00:15:36,235

And then over time,

as the knowledge starts to diffuse across

295

00:15:36,235 --> 00:15:39,238

the organization, the infrastructure

also becomes more robust.

296

00:15:39,371 --> 00:15:42,608

It's almost the opposite

in many ways of previous transformation.

297

00:15:42,608 --> 00:15:45,611

So let's take a SAP ERP implementation.

298

00:15:45,811 --> 00:15:47,880

That's a 3 to 5 year process.

299

00:15:47,880 --> 00:15:49,415

IT command and control.

300

00:15:49,415 --> 00:15:50,582

We install it.

301

00:15:50,582 --> 00:15:52,851

Everyone else has to adapt to it.

302

00:15:52,851 --> 00:15:55,287

What's happening with

AI is we're kind of reversing that

303

00:15:55,287 --> 00:15:58,290

in a in a way,

yes it is provisioning, licensing.

304

00:15:58,524 --> 00:16:00,392

But this is not just an IT issue anymore.

305

00:16:00,392 --> 00:16:01,460

This is an HR issue.

306

00:16:01,460 --> 00:16:02,728

This is a strategy issue.

307

00:16:02,728 --> 00:16:04,763

This is a finance issue.

308

00:16:04,763 --> 00:16:10,803

And if you don't have your CE, CFO,

your CRO and your CEO all in lockstep

309

00:16:10,803 --> 00:16:13,472

on how this is being distributed,

you're not going to come up

310

00:16:13,472 --> 00:16:16,175

with an effective way

of distributing the technology,

311

00:16:16,175 --> 00:16:19,178

the knowledge and the application

across your organization

312

00:16:19,411 --> 00:16:22,748

so that that changes

the dynamic of the tool enormously.

313

00:16:23,182 --> 00:16:26,318

And over time, it then becomes

part of the fabric of the organization,

314

00:16:26,318 --> 00:16:30,622

just like we have with all of our

other, productivity tools. So

315

00:16:31,890 --> 00:16:34,593

I'm lot lots to process there.

316

00:16:34,593 --> 00:16:36,862

What one of the,

317

00:16:36,862 --> 00:16:40,966

one of the things you've said in is

we talked a little bit about it already,

318

00:16:40,966 --> 00:16:44,269

but this there's a fear of people

losing their jobs.

319

00:16:44,269 --> 00:16:48,574

And like Disintermediated like jobs from

tasks and augmenting what we're doing.

320

00:16:49,308 --> 00:16:51,543

You had said previously,

321

00:16:51,543 --> 00:16:52,678

we're not going to lose jobs.

322

00:16:52,678 --> 00:16:54,980

We're going to lose job descriptions.

323

00:16:54,980 --> 00:16:56,815

Well, what does that mean?

324

00:16:56,815 --> 00:17:00,986

And what does that look like

with these, with AI and with these modern

325

00:17:00,986 --> 00:17:02,421

tools and approaches? Absolutely.

326

00:17:02,421 --> 00:17:07,993

So, I said that probably 2 or 3 years ago

in one of my South by Southwest speeches,

327

00:17:07,993 --> 00:17:10,996

I said, we're we won't lose our jobs

or lose our job descriptions.

328

00:17:11,230 --> 00:17:14,166

And, I've, I've had several people say,

well, that age horribly.

329

00:17:14,166 --> 00:17:16,101

And I'm like, actually, yes and no.

330

00:17:16,101 --> 00:17:18,971

Like, I will willingly say

there are jobs that are going to be lost.

331

00:17:18,971 --> 00:17:20,806

This there's no question about them.

332

00:17:20,806 --> 00:17:24,710

But the the image that conjures

for a lot of people is like,

333

00:17:24,710 --> 00:17:26,678

well, you're going to be on a breadline

for the rest of your life.

334

00:17:26,678 --> 00:17:29,681

You'll never be allowed to work again

because you're completely irrelevant.

335

00:17:30,249 --> 00:17:32,117

That's not how this works.

336

00:17:32,117 --> 00:17:35,254

There will be some fracturing

of the system that we work within,

337

00:17:35,254 --> 00:17:36,588

and that's not going to be easy.

338

00:17:36,588 --> 00:17:39,992

And it's going to cause some some pain for

some organizations and a lot of people.

339

00:17:40,592 --> 00:17:44,730

But what does happen is it also changes

the nature of the jobs we hold.

340

00:17:45,064 --> 00:17:47,933

So what I see happening,

and this is related to the concept

341

00:17:47,933 --> 00:17:48,867

of creative journalist

342

00:17:48,867 --> 00:17:51,670

that have been talking about for a while

now, and I can define that as well.

343

00:17:51,670 --> 00:17:55,607

But, a creative journalist is essentially

I'll pull this back

344

00:17:55,607 --> 00:17:58,610

because it's related to the waves

educated, and we build our careers.

345

00:17:58,610 --> 00:18:01,613

So we grew up in a system

that said, go to school,

346

00:18:01,880 --> 00:18:05,851

get a job, build expertise within that job

that becomes defensible.

347

00:18:05,851 --> 00:18:07,686

And that's

what gets you promoted over time.

348

00:18:07,686 --> 00:18:10,689

Over time, you start to manage

the functions that you're an expert in.

349

00:18:11,123 --> 00:18:14,026

You become management and leadership

and up you go.

350

00:18:14,026 --> 00:18:18,430

That vertical, vertical, way of working

351

00:18:18,430 --> 00:18:21,800

has been the way we've promoted people

and told people to go after their careers.

352

00:18:21,800 --> 00:18:23,402

Right. Decades.

353

00:18:23,402 --> 00:18:27,139

What I does, as I mentioned earlier,

is it essentially abstracts

354

00:18:27,139 --> 00:18:32,010

the years and decades of expertise,

influence, opportunity, exposure

355

00:18:32,244 --> 00:18:36,849

that you need to build expertise

in a specific, subject.

356

00:18:37,316 --> 00:18:40,953

And it allows you to perform proficiently

in skill sets that are adjacent

357

00:18:40,953 --> 00:18:43,989

to your own, or even some

that you never had access to before.

358

00:18:44,423 --> 00:18:47,459

I said proficiently,

I did not say in any means an elite level,

359

00:18:47,993 --> 00:18:51,630

but what we often have to confront

in our organizations

360

00:18:51,630 --> 00:18:55,000

is, in many cases,

good enough is good enough.

361

00:18:55,501 --> 00:18:59,938

You don't need somebody with 25 years

of experience to do junior level work.

362

00:19:00,339 --> 00:19:03,775

And if I am an outsider adjacent

to that role

363

00:19:03,775 --> 00:19:08,347

and I can get that junior level work done,

why do I have to wait? Or,

364

00:19:08,447 --> 00:19:12,151

you know, rely on specialized expertise

and resources to get that work done?

365

00:19:12,618 --> 00:19:14,520

So that changes this dynamic.

366

00:19:14,520 --> 00:19:18,857

And, the nature

of how I relate to my peers, their roles,

367

00:19:18,857 --> 00:19:22,261

my rules, and it expands the capacity

368

00:19:22,261 --> 00:19:25,264

and responsibility

in the remit of individual roles.

369

00:19:25,264 --> 00:19:28,567

We're moving away from role

based relationships to jobs,

370

00:19:29,001 --> 00:19:32,070

to skill based

and task based relationships to jobs.

371

00:19:32,838 --> 00:19:36,608

And that's where I feel like

the idea of jobs are not going away.

372

00:19:36,608 --> 00:19:39,611

I even say in that same speech,

jobs are dead.

373

00:19:39,678 --> 00:19:41,580

Long live work.

374

00:19:41,580 --> 00:19:46,218

And one thing that I think we're so stuck

on and say we need good jobs, we need,

375

00:19:46,351 --> 00:19:46,785

you know,

376

00:19:46,785 --> 00:19:49,788

you'll hear every politician say, we need

to bring good jobs back to America.

377

00:19:50,155 --> 00:19:54,026

And it's not the jobs,

it's the work that we need.

378

00:19:54,393 --> 00:19:58,463

If we're so focused on jobs or already

narrowly defining ourselves and oftentimes

379

00:19:58,463 --> 00:20:01,500

attaching ourselves

to things that are not coming back,

380

00:20:01,900 --> 00:20:05,270

like we're we're not really going to be

bringing back the coal sector that way.

381

00:20:05,270 --> 00:20:07,039

Everybody is talking about it

in many ways.

382

00:20:07,039 --> 00:20:10,042

That's kind of a train

that's moved along no matter what we do,

383

00:20:10,576 --> 00:20:13,078

and other jobs are the same way.

384

00:20:13,078 --> 00:20:16,915

But we talk about the work

as it relates to the tasks and roles

385

00:20:16,915 --> 00:20:20,452

and things like that that need to be,

put together for the future of work.

386

00:20:20,852 --> 00:20:23,188

That's

where we can actually make some traction.

387

00:20:23,188 --> 00:20:26,191

And that's why I do believe, like,

we're not getting rid of jobs.

388

00:20:26,425 --> 00:20:30,229

We're getting rid of the definition

of the artificial boundaries

389

00:20:30,229 --> 00:20:32,864

that keep you in a specific space

in your organization.

390

00:20:32,864 --> 00:20:36,902

And that's how I see organizations evolving significantly over the next decade.

391

00:20:38,570 --> 00:20:40,172

So if that if that

392

00:20:40,172 --> 00:20:43,842

is the case,

there's like tons of wild implications.

393

00:20:43,942 --> 00:20:46,478

And I by the way,

I think that probably is the case.

394

00:20:46,478 --> 00:20:50,015

But there's like tons of wild implications

from the education system

395

00:20:50,015 --> 00:20:53,018

to our careers to organizations.

396

00:20:53,485 --> 00:20:56,488

But in terms of impacts in,

397

00:20:58,056 --> 00:21:00,359

and maybe feel free to tell me

398

00:21:00,359 --> 00:21:03,495

this entire paradigm is wrong,

but where is there more risk?

399

00:21:03,495 --> 00:21:07,766

Is there more risk for,

you know, junior employees right now

400

00:21:07,966 --> 00:21:11,603

who you know, their general skill set

401

00:21:11,603 --> 00:21:14,873

and their baseline

level of knowledge can be replaced by AI?

402

00:21:15,107 --> 00:21:19,144

Or is there more risk for people

who are 20 years into their career

403

00:21:19,411 --> 00:21:22,347

and they have a deep skill set

404

00:21:22,347 --> 00:21:25,350

that maybe now is almost commoditized?

405

00:21:25,417 --> 00:21:28,420

Because you can ask, you know, I

406

00:21:28,520 --> 00:21:31,523

how to, you know,

I'll pick on data scientists, you know,

407

00:21:31,690 --> 00:21:34,593

just for example, because, you know,

these are, you know, historically

408

00:21:34,593 --> 00:21:38,130

high paid roles

that have a lot of schooling behind them.

409

00:21:38,130 --> 00:21:39,164

And if you can start to get

410

00:21:39,164 --> 00:21:42,768

some of these answers,

some of this validation information

411

00:21:42,968 --> 00:21:46,972

commoditized by AI, what does that mean

for people in these careers.

412

00:21:46,972 --> 00:21:50,008

So where where is the risk greater

413

00:21:50,008 --> 00:21:53,111

or is the entire paradigm

just, you know, misplaced.

414

00:21:53,145 --> 00:21:56,782

It's so they're both under

an enormous amount of strain right now.

415

00:21:56,948 --> 00:22:00,786

The one that's most present

that we're seeing, happen

416

00:22:01,753 --> 00:22:04,656

with more frequency is those

who are at the beginning of their careers

417

00:22:04,656 --> 00:22:08,493

are at highest risk to this exposure,

because you can replace a lot

418

00:22:08,493 --> 00:22:09,995

of the things that they would do.

419

00:22:09,995 --> 00:22:13,899

Now we're kind of there was this unspoken

contract that when you leave school,

420

00:22:13,899 --> 00:22:15,434

you would continue your training

421

00:22:15,434 --> 00:22:18,437

almost like a vocation in whatever place

you would go in and learn.

422

00:22:18,704 --> 00:22:20,205

And there's

an enormous amount of teaching,

423

00:22:20,205 --> 00:22:22,674

mentoring that goes on with that.

424

00:22:22,674 --> 00:22:27,012

And when I can just consult ChatGPT

and get it done and not have to mentor it,

425

00:22:27,145 --> 00:22:28,213

I'm going to do that.

426

00:22:28,213 --> 00:22:31,049

There's just no question

that that's going to happen in my case.

427

00:22:31,049 --> 00:22:34,052

So junior roles are already starting

to disappear.

428

00:22:34,686 --> 00:22:38,590

The capacity and capability that juniors

have are starting to disappear.

429

00:22:38,857 --> 00:22:41,560

And the challenge

that just adding the technology

430

00:22:41,560 --> 00:22:44,696

to and giving juniors access

to that doesn't help a lot

431

00:22:44,696 --> 00:22:48,734

because they don't have the experience

and the frameworks to understand.

432

00:22:48,967 --> 00:22:51,136

You know, when I'm

doing some exploratory research on this,

433

00:22:51,136 --> 00:22:54,473

what matters, what are the things

I should be looking and honing in on?

434

00:22:54,673 --> 00:22:55,474

And they just

435

00:22:55,474 --> 00:22:58,910

they get overwhelmed by the sheer

volume of things they should be looking at

436

00:22:59,144 --> 00:23:03,482

without being able to find the right

signals to, to to hone in on.

437

00:23:03,882 --> 00:23:07,386

Now, the other part

that's true is that middle management

438

00:23:07,552 --> 00:23:10,455

is also getting

hit really hard with this stuff.

439

00:23:10,455 --> 00:23:14,793

Because if your role is focused

more on creating alignment,

440

00:23:15,026 --> 00:23:18,663

checking in on organizations,

or checking in on your employees,

441

00:23:18,663 --> 00:23:20,766

doing a little bit of mentoring here

and there, but more

442

00:23:20,766 --> 00:23:23,769

so the things that are around

productivity and efficiency of a team.

443

00:23:24,102 --> 00:23:26,805

So not the leadership level,

not the visioning.

444

00:23:26,805 --> 00:23:27,139

Right.

445

00:23:27,139 --> 00:23:31,410

But just like the operations

of the company that is directly

446

00:23:31,410 --> 00:23:35,013

in the line of fired

AI and what that changes, is it

447

00:23:35,013 --> 00:23:38,850

the stuff of being a boss

is also starting to go away.

448

00:23:39,284 --> 00:23:43,188

What that makes space for is for people

to step into actual roles of leadership.

449

00:23:43,655 --> 00:23:46,158

So we're seeing this layer

of middle management

450

00:23:46,158 --> 00:23:50,862

that is directly in the line of fire,

but also collapses the organization a bit,

451

00:23:50,862 --> 00:23:54,399

where the line between junior

or more junior people and leadership

452

00:23:54,633 --> 00:23:57,569

is also starting

to become thinner and thinner and thinner.

453

00:23:57,569 --> 00:23:59,604

But it means more direct contact

with people

454

00:23:59,604 --> 00:24:02,674

who can spend time in the space of

being leaders versus bosses.

455

00:24:03,975 --> 00:24:04,609

Can you can

456

00:24:04,609 --> 00:24:07,612

you, just unpack that a little bit for me?

457

00:24:07,879 --> 00:24:10,148

What is it? I'm.

458

00:24:10,148 --> 00:24:13,051

I'm actually a little bit surprised

to hear that that the some of the team

459

00:24:13,051 --> 00:24:16,021

management

piece is something that I can do.

460

00:24:16,354 --> 00:24:19,357

What what are the tasks

that you see as being,

461

00:24:20,492 --> 00:24:22,627

you know, no. Now doable to AI.

462

00:24:22,627 --> 00:24:24,596

What does that look like? Absolutely.

463

00:24:24,596 --> 00:24:29,701

So a lot of what happens at the management

level is facilitation and alignment

464

00:24:30,068 --> 00:24:33,472

and things like facilitation

are easily done by AI.

465

00:24:34,172 --> 00:24:38,109

When we actually work within Signal and

Cipher, the projects that we're working on

466

00:24:38,410 --> 00:24:42,180

are known not only to us, but also our AI

and our project management system.

467

00:24:42,180 --> 00:24:43,782

So I don't have to check in

with my co-founder.

468

00:24:43,782 --> 00:24:45,617

You're like, where are you on this?

469

00:24:45,617 --> 00:24:46,251

It knows.

470

00:24:46,251 --> 00:24:49,821

Therefore I know, so that

the amount of meetings that I'm having

471

00:24:49,921 --> 00:24:54,392

around alignments

and approval have dropped like 70%.

472

00:24:54,826 --> 00:24:58,096

So the wow, these big parts

where we call it corporate waste,

473

00:24:58,797 --> 00:24:59,865

these items where you're

474

00:24:59,865 --> 00:25:03,301

waiting on specialized resources,

they come available to do the work

475

00:25:03,568 --> 00:25:07,806

or to have a moment of someone's

time to say, do you approve of this?

476

00:25:08,073 --> 00:25:11,676

Or having those CYA moments

of does legal approve of this?

477

00:25:12,210 --> 00:25:14,312

Those are actually starting

to disappear as well

478

00:25:14,312 --> 00:25:16,348

because the systems

can check on these things.

479

00:25:16,348 --> 00:25:19,351

Now, none of these things are bulletproof

or faultless yet.

480

00:25:19,484 --> 00:25:23,522

So in the beginning they actually create

more work in an apparatus.

481

00:25:23,522 --> 00:25:26,525

So there's more work for bosses

and middle management to work on.

482

00:25:26,525 --> 00:25:28,226

There's more work for implementation.

483

00:25:28,226 --> 00:25:32,130

And and we see that almost in every

transformation, it actually productivity

484

00:25:32,130 --> 00:25:36,601

dips and effort and investment

go up during that transitory phase.

485

00:25:36,968 --> 00:25:39,704

But when you get past that

and start to see some of those

486

00:25:39,704 --> 00:25:42,707

benefits,

it changes dramatically how you operate.

487

00:25:42,941 --> 00:25:44,943

So we'll go into organizations.

488

00:25:44,943 --> 00:25:48,079

We'll see, you know, 25 people sitting

at a table for an hour long meeting.

489

00:25:48,079 --> 00:25:49,347

And the first thing I think of is like,

490

00:25:50,882 --> 00:25:51,650

three of you need to

491

00:25:51,650 --> 00:25:54,786

be here, and this is so expensive,

like you're wasting so much more.

492

00:25:55,420 --> 00:25:58,790

And for us, it's gotten to a point

where we say that the small team

493

00:25:58,790 --> 00:25:59,691

is the ultimate flacks.

494

00:25:59,691 --> 00:26:03,461

It means that if you've got a small team

that can really run effectively

495

00:26:03,762 --> 00:26:06,765

and you're using your tools

and your infrastructure appropriately,

496

00:26:06,831 --> 00:26:10,402

then you can move so fast,

you can make decisions confidently

497

00:26:10,502 --> 00:26:12,203

without having to consult everybody.

498

00:26:12,203 --> 00:26:15,740

And most of those meetings

are really about CIA.

499

00:26:15,740 --> 00:26:16,575

It's about,

500

00:26:16,575 --> 00:26:20,712

can I distribute the liability

of this decision across a group of people?

501

00:26:20,712 --> 00:26:22,948

So it's not just my fault,

502

00:26:22,948 --> 00:26:24,983

right.

503

00:26:24,983 --> 00:26:27,953

So so with that in mind,

you've talked before about this notion

504

00:26:27,953 --> 00:26:31,122

of augmented teams and being able to use

some of this technology

505

00:26:31,122 --> 00:26:34,392

to get more out of an existing team

or even restructure an existing team.

506

00:26:34,893 --> 00:26:36,928

What does that look like in practice?

Yeah.

507

00:26:36,928 --> 00:26:40,565

So there's a couple things that we lean

into to to help augment teams.

508

00:26:40,565 --> 00:26:42,701

The first level is just learning

to use the tools.

509

00:26:42,701 --> 00:26:46,037

Like just by doing

that, you're already moving 10 to 20%

510

00:26:46,037 --> 00:26:49,541

faster, more effectively

better thought partnership with AI.

511

00:26:50,175 --> 00:26:53,912

But the next level is starting

to actually encode your own knowledge.

512

00:26:54,112 --> 00:26:56,681

So that can happen at a team level

or an individual level.

513

00:26:56,681 --> 00:26:59,784

What I mean by including

it is taking things that you've written,

514

00:26:59,784 --> 00:27:04,723

whether that's briefs, emails, contents,

and starting to turn that

515

00:27:04,723 --> 00:27:08,193

into something that the large language

model can work with and understand.

516

00:27:08,493 --> 00:27:11,162

It's a bit like training a Laura,

517

00:27:11,162 --> 00:27:14,833

on your own assets,

and that becomes a bit of a digital twin.

518

00:27:15,300 --> 00:27:16,735

And we do this at the team level.

519

00:27:16,735 --> 00:27:19,304

The individual level

and the organizational level.

520

00:27:19,304 --> 00:27:21,973

What most people aren't seeing right

now, we're seeing a lot of that happen

521

00:27:21,973 --> 00:27:23,475

at the organizational level.

522

00:27:23,475 --> 00:27:27,646

But when we augment an individual and say,

okay, I've taken everything

523

00:27:27,646 --> 00:27:29,247

you've written at it, not everything,

524

00:27:29,247 --> 00:27:32,350

but the the highest signal,

highest quality stuff that you've written,

525

00:27:33,685 --> 00:27:36,688

content

about who you are, what you've done, etc.

526

00:27:37,022 --> 00:27:40,158

and turn that into a document that sits on

top of the large language model,

527

00:27:40,458 --> 00:27:43,261

and that becomes the filter through

which you prompt.

528

00:27:43,261 --> 00:27:46,231

It's to fill out a filter

and going in and going out.

529

00:27:46,231 --> 00:27:49,067

So it's going to augment

what you're actually prompting against.

530

00:27:49,067 --> 00:27:52,203

It's also going to filter

the responses that the LM gives you.

531

00:27:52,370 --> 00:27:56,307

So everything you do is going to be

in your style, in your tone of voice,

532

00:27:56,574 --> 00:27:59,577

with your strategic

understanding of the business.

533

00:27:59,744 --> 00:28:03,548

And that can really expand

your capabilities in a number of different

534

00:28:03,548 --> 00:28:04,683

directions.

535

00:28:04,683 --> 00:28:07,352

The same thing happens

with the organization, which helps

536

00:28:07,352 --> 00:28:11,222

enormously with things like brain drain

or bringing people up to speed.

537

00:28:11,389 --> 00:28:15,727

One of our goals is as an organization,

if I bring someone in off the street,

538

00:28:15,727 --> 00:28:18,930

I want to be able to get them

to the same level as everybody else within

539

00:28:18,930 --> 00:28:22,600

less than a month and on day one,

they should be able to write an email.

540

00:28:22,667 --> 00:28:24,869

The tone of voice of the company

that should be able to manage

541

00:28:24,869 --> 00:28:26,905

our social media presence,

all that kind of stuff,

542

00:28:26,905 --> 00:28:28,373

because we've built a layer

543

00:28:28,373 --> 00:28:31,710

on top of the large language model

that already has all of that encoded,

544

00:28:32,410 --> 00:28:35,647

rather than having to teach someone

to do that from day one.

545

00:28:36,381 --> 00:28:37,916

So it's doing two things.

546

00:28:37,916 --> 00:28:41,319

It's augmenting the individual's

capability and capacity.

547

00:28:41,720 --> 00:28:45,590

And it's also removing all the friction

of having to become up to speed

548

00:28:45,857 --> 00:28:47,625

on how your organization works.

549

00:28:49,060 --> 00:28:49,828

Right?

550

00:28:49,828 --> 00:28:51,196

So I mean, I

551

00:28:51,196 --> 00:28:54,199

it's such an interesting approach

and I can, you know, immediately

552

00:28:54,199 --> 00:28:58,737

see like huge transformational

organizational benefits, you know,

553

00:28:58,737 --> 00:29:02,073

from an efficiency and effectiveness

perspective by doing something like that,

554

00:29:02,574 --> 00:29:07,245

are you finding that there's resistance

at an individual level to that?

555

00:29:07,445 --> 00:29:10,315

Like my concern would be that

people say like, oh, you're

556

00:29:10,315 --> 00:29:13,685

trying to like download my brain into AI

and then get rid of me.

557

00:29:13,685 --> 00:29:18,156

Like,

I can imagine a world where there's angst.

558

00:29:18,690 --> 00:29:20,992

Is that the case?

And if so, how do you overcome that?

559

00:29:20,992 --> 00:29:23,995

That's the very first response

most people give is like, hey,

560

00:29:23,995 --> 00:29:25,463

this, this is my value.

561

00:29:25,463 --> 00:29:27,932

Like, this is why you hired me to do this.

562

00:29:27,932 --> 00:29:30,635

And that becomes a conversation

between the organization,

563

00:29:30,635 --> 00:29:33,738

the individual, and a contract of

this is yours, not ours.

564

00:29:34,339 --> 00:29:37,909

So the goal with the data

is for the organization

565

00:29:37,909 --> 00:29:40,779

and a team level data

that is owned by the organization.

566

00:29:40,779 --> 00:29:44,349

The individual level data

must stay with the individual.

567

00:29:44,883 --> 00:29:46,951

And this is a

this is a personal philosophy of mine.

568

00:29:46,951 --> 00:29:50,255

I honestly don't believe

that we can move towards a future paradigm

569

00:29:50,255 --> 00:29:53,057

where this is a part of the way

we do our work.

570

00:29:53,057 --> 00:29:55,794

If that agreement doesn't stand a place.

571

00:29:55,794 --> 00:29:56,761

So it's like when you move

572

00:29:56,761 --> 00:30:00,532

from organization to organization,

you take your experience with you,

573

00:30:00,532 --> 00:30:03,835

but you're not taking the files

you worked on at at the office.

574

00:30:04,435 --> 00:30:07,639

If I'm going to encode

you and your thoughts, it's

575

00:30:07,639 --> 00:30:11,409

just like saying, as an actor

or a voice actor, I've encoded your voice

576

00:30:11,409 --> 00:30:15,180

and no longer have to give you credit

for what I extracted from you.

577

00:30:15,814 --> 00:30:19,083

That, by definition, creates

an antagonistic relationship

578

00:30:19,083 --> 00:30:21,152

between the organization

and the individual.

579

00:30:21,152 --> 00:30:24,122

I firmly believe

we should own our data, so

580

00:30:24,122 --> 00:30:27,091

that's what we have encouraged

and facilitated.

581

00:30:27,826 --> 00:30:30,628

But yes, that is typically the way people

look at it when they first start.

582

00:30:30,628 --> 00:30:33,631

It's like, okay, the company's

gonna own everything about me.

583

00:30:33,765 --> 00:30:36,601

And right, sometimes the company are like,

oh yeah, that's that's right.

584

00:30:36,601 --> 00:30:38,937

We could really do a lot more with a lot

fewer people.

585

00:30:38,937 --> 00:30:42,841

Like, no, that that will absolutely one

destroy morale

586

00:30:43,174 --> 00:30:44,843

and to no one a lot work with you.

587

00:30:45,977 --> 00:30:47,011

Right.

588

00:30:47,011 --> 00:30:49,614

So are we.

589

00:30:49,614 --> 00:30:51,282

It's such an interesting idea.

590

00:30:51,282 --> 00:30:52,650

And I and I really.

591

00:30:52,650 --> 00:30:54,919

I hadn't heard that before, to be honest.

592

00:30:54,919 --> 00:30:57,922

And I, I talk to people in this space

all day, every day.

593

00:30:58,056 --> 00:31:03,027

So the idea of having this, like,

this individual,

594

00:31:03,761 --> 00:31:06,764

you know, digital twin or AI ified,

595

00:31:06,764 --> 00:31:10,368

you know, likeness or,

you know, data model of you

596

00:31:11,069 --> 00:31:14,973

right now,

I have to imagine if most organizations

597

00:31:14,973 --> 00:31:17,876

propose that to a staff member,

that'll be like the first

598

00:31:17,876 --> 00:31:20,879

they've heard of it and they're like,

whoa, you know, what is this?

599

00:31:21,079 --> 00:31:23,882

Are we heading toward a world

in the next few years

600

00:31:23,882 --> 00:31:27,185

where this is going to become

the norm and, you know,

601

00:31:27,185 --> 00:31:31,155

everyone will start to be literate around

this and,

602

00:31:31,389 --> 00:31:34,392

you know, expecting this conversation

almost.

603

00:31:34,492 --> 00:31:37,161

I don't know, and the reason I say

that is not

604

00:31:37,161 --> 00:31:40,164

because the technology's not ready for it,

not because it's not possible.

605

00:31:40,598 --> 00:31:43,902

It's that the the limitations

of how our organizations grow

606

00:31:44,102 --> 00:31:45,737

are not just technological.

607

00:31:45,737 --> 00:31:48,673

There's so many different

other constraints as to why organizations

608

00:31:48,673 --> 00:31:52,310

change the way they do

and why technological adoption is so slow.

609

00:31:53,144 --> 00:31:55,647

There's a concept that I love called

martech law,

610

00:31:55,647 --> 00:31:58,950

and it's it's about the difference

between technology

611

00:31:58,950 --> 00:32:02,720

moving exponentially and people

and organizations develop logarithmically.

612

00:32:02,720 --> 00:32:07,392

And what this does is creates this ever

increasing gap between what is possible

613

00:32:07,392 --> 00:32:11,229

with the technology and what the companies

and individuals are actually capable of.

614

00:32:11,462 --> 00:32:14,599

So we're looking at potential versus

practical reality.

615

00:32:14,799 --> 00:32:19,971

And the thing that's pushing this curve

so much lower than this is infrastructure,

616

00:32:19,971 --> 00:32:23,741

technology, culture, decision

debt, technological debt.

617

00:32:23,741 --> 00:32:27,745

There are all these constraints

in an organization that dictate how high

618

00:32:27,745 --> 00:32:31,783

that logarithmic curve can go,

and how far you can push that up

619

00:32:32,150 --> 00:32:36,254

so the technology can move

as fast as you possibly could imagine.

620

00:32:36,688 --> 00:32:40,892

We are not going to be able to integrate

and adapt it as fast as it changes.

621

00:32:40,892 --> 00:32:43,861

We're already seeing that right

now. We're right.

622

00:32:43,861 --> 00:32:46,965

You'll see some people who are just,

you know, they've hundred x themselves,

623

00:32:47,699 --> 00:32:50,735

with what they can do, whether possible,

whether it capable of doing

624

00:32:50,735 --> 00:32:53,304

and then everyone else is looking at them

like they're an alien.

625

00:32:53,304 --> 00:32:56,741

And that's because they, as an individual,

have leaned into it

626

00:32:56,741 --> 00:32:58,242

and are already adapted.

627

00:32:58,242 --> 00:33:01,245

A lot of the stuff, they've already

had the experience to help them do that.

628

00:33:01,479 --> 00:33:02,246

Usually, you know,

629

00:33:02,246 --> 00:33:05,583

really good engineers and developers

can lean in and the way to do that.

630

00:33:06,017 --> 00:33:09,721

But if you're an account person

who doesn't have that expertise,

631

00:33:09,721 --> 00:33:11,489

you look at that and say,

there's all these limitations

632

00:33:11,489 --> 00:33:12,857

preventing me from doing that.

633

00:33:12,857 --> 00:33:14,926

Organizations work the same way.

634

00:33:14,926 --> 00:33:17,328

Some organizations like ours are small.

635

00:33:17,328 --> 00:33:19,497

We're built for this where native AI,

636

00:33:19,497 --> 00:33:22,533

whereas a lot of organizations

we're working with that are fortune 500,

637

00:33:22,934 --> 00:33:24,869

don't have any of those things,

any of those qualities

638

00:33:24,869 --> 00:33:27,372

that will allow them to say,

we're going to be AI native tomorrow.

639

00:33:28,773 --> 00:33:30,141

Right?

640

00:33:30,141 --> 00:33:32,977

So, you know, this brings me

to another central question

641

00:33:32,977 --> 00:33:35,313

that I was excited to ask you about, Ian,

which is

642

00:33:35,313 --> 00:33:38,282

who do you see as being the winners

and losers?

643

00:33:38,616 --> 00:33:39,684

Of this disruption?

644

00:33:39,684 --> 00:33:42,887

And I'm deliberately asking that

in kind of the broadest possible sense.

645

00:33:43,287 --> 00:33:46,824

Yeah, it's an interesting question for

which I'm still forming an answer myself,

646

00:33:47,191 --> 00:33:51,996

because the initial thinking is like,

okay, if we don't need big teams,

647

00:33:51,996 --> 00:33:57,001

then we obviously don't need organizations

that are 200, 300, and 400,000 people.

648

00:33:57,301 --> 00:34:01,172

And, right, all these startups

are going to come and take their lunch.

649

00:34:01,172 --> 00:34:04,142

And it's a lot more complicated than that.

650

00:34:05,209 --> 00:34:08,312

There are other structures

besides just size

651

00:34:08,312 --> 00:34:12,650

keeping the, the current winners

entrenched in their space.

652

00:34:12,917 --> 00:34:17,321

So let's take like a chemical manufacturer

for, for, instance,

653

00:34:17,522 --> 00:34:18,756

like there's a lot of the corporate work

654

00:34:18,756 --> 00:34:21,759

that can be taken away

by AI and made more efficient.

655

00:34:22,026 --> 00:34:23,194

And you can use machines for that.

656

00:34:23,194 --> 00:34:26,431

But there's physical apparatus,

there's mechanical apparatus,

657

00:34:26,431 --> 00:34:28,699

all that needs to be done,

this distribution,

658

00:34:28,699 --> 00:34:31,803

there's geopolitical elements

to how these companies grow.

659

00:34:32,336 --> 00:34:35,573

And again, that gets back

to the practical limitations

660

00:34:35,840 --> 00:34:40,111

that shape the growth and change

of these organizations in new paradigms.

661

00:34:40,478 --> 00:34:44,582

So I don't think it's just as simple

as, okay, you need smaller teams,

662

00:34:44,582 --> 00:34:48,519

fewer people, companies will shrink

and startups will come in and eat lunch.

663

00:34:48,519 --> 00:34:52,223

Of those who don't move fast

enough, speed is one variable.

664

00:34:52,223 --> 00:34:54,992

It's a very important variable,

but it's just one.

665

00:34:54,992 --> 00:34:58,496

What I do think,

though, is companies will get smaller.

666

00:34:59,831 --> 00:35:00,765

But I also think there will

667

00:35:00,765 --> 00:35:04,001

be more startups and more businesses

formed than ever before.

668

00:35:04,402 --> 00:35:07,805

If we just look at the trajectory

of the statistics, even since Covid,

669

00:35:08,005 --> 00:35:11,576

we've had a massive increase in the number

as corpse and LLCs formed

670

00:35:11,576 --> 00:35:14,579

more than any time in history,

and that's likely

671

00:35:14,579 --> 00:35:17,582

to get even easier,

672

00:35:17,582 --> 00:35:21,152

as time goes on, because the ability

to form a company again

673

00:35:21,719 --> 00:35:25,022

gets easier with AI, the ability to form

a team gets easier with AI.

674

00:35:25,056 --> 00:35:27,558

So I think freelancing is going to explode

even more than our. Yes.

675

00:35:27,558 --> 00:35:29,760

So an acceleration in the existing trend,

676

00:35:29,760 --> 00:35:32,797

the ability to open businesses,

the things that keep people away

677

00:35:33,064 --> 00:35:36,067

from opening

businesses is going to almost evaporate.

678

00:35:36,234 --> 00:35:40,071

And I think that the opportunity

to start creating these entities

679

00:35:40,071 --> 00:35:41,372

for even short time

680

00:35:41,372 --> 00:35:44,942

periods of times for more specialized use

cases is going to become a thing, too.

681

00:35:45,243 --> 00:35:49,313

So I could easily see the number

of businesses built in the next ten years.

682

00:35:49,313 --> 00:35:50,715

100 Xingu

683

00:35:50,715 --> 00:35:54,418

not just multiplying on that, because

we're also using agents for that too.

684

00:35:54,752 --> 00:35:58,322

We're not using agents for employees, but

we're using agents to build the business.

685

00:35:58,856 --> 00:36:01,459

So if you think about how you can scale

that,

686

00:36:01,459 --> 00:36:04,662

that's I'm still wrapping my head around

what that looks like.

687

00:36:04,662 --> 00:36:07,832

As far as what is the economy look like,

what is and, you know,

688

00:36:07,899 --> 00:36:10,368

how do we align that

in terms of geopolitics

689

00:36:10,368 --> 00:36:13,437

and how that becomes

the way organizations shape as well?

690

00:36:13,437 --> 00:36:16,841

It's a lot of things that, you know,

still not shape themselves yet.

691

00:36:17,208 --> 00:36:20,344

So I don't think it's

just a small organization's more business.

692

00:36:20,545 --> 00:36:22,580

But that's the closest

thing I could find so far.

693

00:36:23,714 --> 00:36:24,682

Right.

694

00:36:24,682 --> 00:36:29,520

And I'm glad you had that level of clarity

because it's it's easy to just end up

695

00:36:29,520 --> 00:36:32,890

in the mindset of, you know, smaller

organizations eating your lunch.

696

00:36:32,890 --> 00:36:35,893

You're done, you know, good luck.

697

00:36:36,961 --> 00:36:39,463

The when I think about the implications

698

00:36:39,463 --> 00:36:42,667

of what I think we broadly agree upon,

which is it's going to be way

699

00:36:42,667 --> 00:36:43,834

easier to start a business.

700

00:36:43,834 --> 00:36:45,970

There's already more businesses happening.

701

00:36:45,970 --> 00:36:50,074

That's really good for consumers,

I would imagine.

702

00:36:50,508 --> 00:36:54,645

And it does mean more competition

for incumbents.

703

00:36:54,645 --> 00:36:57,715

And I like I really like your point about,

well, it's

704

00:36:57,715 --> 00:36:58,983

not just they're going to eat your lunch

705

00:36:58,983 --> 00:37:03,421

because there's more to it than, you know,

just just the speed or the efficiency.

706

00:37:03,421 --> 00:37:05,223

They're

707

00:37:05,223 --> 00:37:08,492

you've talked before

about the need for transformational change

708

00:37:09,327 --> 00:37:13,264

versus just strictly optimizing

what incumbents are doing,

709

00:37:13,965 --> 00:37:16,968

how transformational do

we need to be thinking,

710

00:37:16,968 --> 00:37:20,304

and what's the best way

to get into that mindset?

711

00:37:20,304 --> 00:37:24,008

Is it creating like an innovation

incubator in your organization?

712

00:37:24,008 --> 00:37:27,912

Is it trying to start your own,

you know, kind of funded startups?

713

00:37:27,912 --> 00:37:30,615

Are there any kind of tactics

you recommend with organization?

714

00:37:30,615 --> 00:37:31,382

Absolutely.

715

00:37:31,382 --> 00:37:34,719

So I think I would encourage organizations

to be radical

716

00:37:34,719 --> 00:37:37,822

with their thinking and practical

with their approach.

717

00:37:38,689 --> 00:37:41,626

So there's there are too many people.

718

00:37:41,626 --> 00:37:45,196

So you kind of need to break burning

all the ground, start fresh.

719

00:37:45,830 --> 00:37:48,499

There's no enterprise

that says we're profitable.

720

00:37:48,499 --> 00:37:49,800

We're doing just fine.

721

00:37:49,800 --> 00:37:52,637

We want to disrupt that. Nobody says that.

722

00:37:53,871 --> 00:37:57,108

But what I do think is,

unless you are radical with your thinking,

723

00:37:57,108 --> 00:38:00,111

you will not be ready for the disruptions

that are going to come.

724

00:38:00,444 --> 00:38:04,148

So these technological transformations

that happen at GPT level.

725

00:38:04,148 --> 00:38:07,318

So general purpose technology

start at the infrastructure level.

726

00:38:07,752 --> 00:38:10,821

So we've seen disruption with technology

and the technology that we use.

727

00:38:10,855 --> 00:38:12,923

So electricity did the same thing.

728

00:38:12,923 --> 00:38:15,092

And OpenAI did the same thing with GPT.

729

00:38:15,092 --> 00:38:16,927

So we know now we're all using it.

730

00:38:16,927 --> 00:38:19,697

But over time those disruptions move up

731

00:38:19,697 --> 00:38:22,833

a level from infrastructure

to application to industry.

732

00:38:23,567 --> 00:38:25,936

So if you're not

733

00:38:25,936 --> 00:38:28,939

okay I guess I guess it is explosive.

734

00:38:29,807 --> 00:38:32,209

But if you're not thinking radically

735

00:38:32,209 --> 00:38:35,279

about the transformation that can happen

at each one of those levels,

736

00:38:35,279 --> 00:38:38,482

and also the transformation

that can happen to your industry,

737

00:38:38,883 --> 00:38:41,852

and you're just focused on the data,

what you have now,

738

00:38:42,153 --> 00:38:44,822

you're missing one of the critical shifts

of transformation in the business.

739

00:38:44,822 --> 00:38:45,723

And there's a,

740

00:38:47,258 --> 00:38:48,092

theme that's becoming

741

00:38:48,092 --> 00:38:51,095

more popular right now

is going moving from insight to foresight.

742

00:38:51,862 --> 00:38:56,634

And when everything is changing around

you, insights valuable, it's

743

00:38:56,634 --> 00:38:59,770

how you create structure around a business

that you can take to market.

744

00:39:00,271 --> 00:39:03,274

Foresight

is about how you avoid getting disrupted.

745

00:39:03,507 --> 00:39:06,677

If we're not looking forward

and we're still letting yesterday's

746

00:39:06,677 --> 00:39:10,414

mental models collide with tomorrow's

technologies, that is how we lose.

747

00:39:10,981 --> 00:39:14,985

But if we are radical

with the way we think, with the IT ability

748

00:39:14,985 --> 00:39:16,754

to test different business models,

749

00:39:16,754 --> 00:39:20,257

put things to market faster

when we might not previously

750

00:39:20,524 --> 00:39:23,427

get that data and that feedback loop

as fast as possible,

751

00:39:23,427 --> 00:39:26,731

we're going to learn more

about that unexplored terrain way faster.

752

00:39:27,164 --> 00:39:32,069

So I wouldn't say go and disrupt your

your $1 billion, you know, revenue line,

753

00:39:32,336 --> 00:39:35,272

but you absolutely

should be incubating things that will

754

00:39:35,272 --> 00:39:36,941

because there are hundreds

755

00:39:36,941 --> 00:39:39,944

and eventually thousands of other startups

that are doing exactly that.

756

00:39:40,144 --> 00:39:42,847

And you have no defense against that

if you're not thinking in that way.

757

00:39:42,847 --> 00:39:45,816

So think radically approach practically.

758

00:39:45,816 --> 00:39:47,618

So that next step goes, okay.

759

00:39:47,618 --> 00:39:49,487

So what do we do to implement this?

760

00:39:49,487 --> 00:39:52,223

Is it Tiger teams. Is it small skunkworks.

761

00:39:52,223 --> 00:39:53,491

All of those are viable.

762

00:39:53,491 --> 00:39:54,959

I do believe that having

763

00:39:55,893 --> 00:39:59,196

in its transformation,

you need to find people who are leaning in

764

00:39:59,196 --> 00:39:59,730

and are

765

00:39:59,730 --> 00:40:03,300

self-selecting as the people who are like,

I'm all about this, I want to do this.

766

00:40:03,667 --> 00:40:07,338

Don't try and convince a bunch of people

who might not be invested

767

00:40:07,338 --> 00:40:09,740

in the nest

to be the first ones through the door.

768

00:40:09,740 --> 00:40:11,308

They will be unenthusiastic about it.

769

00:40:11,308 --> 00:40:13,611

They don't have the willpower

to get through the challenges.

770

00:40:13,611 --> 00:40:14,879

It's going to be hard,

771

00:40:14,879 --> 00:40:17,882

and they're going to fail a million times

before they get it right.

772

00:40:17,882 --> 00:40:20,818

If they're not already passionate

about this,

773

00:40:20,818 --> 00:40:23,287

they're going to stop

at the first sign of trouble.

774

00:40:23,287 --> 00:40:26,524

Those people can be followers

of the people who lead the way.

775

00:40:26,524 --> 00:40:27,925

It's not that they're irrelevant.

776

00:40:27,925 --> 00:40:29,326

You need to find the people who are like,

777

00:40:29,326 --> 00:40:31,262

I want to be

the person who kicks the door down.

778

00:40:31,262 --> 00:40:34,365

I want the first person in the room,

and those are the ones you want to build

779

00:40:34,365 --> 00:40:37,802

your teams around to, to think about

these things and build different ideas

780

00:40:38,469 --> 00:40:39,870

and find the tinkerers.

781

00:40:39,870 --> 00:40:42,006

Find the people who may not be

782

00:40:42,006 --> 00:40:45,342

the developers or the engineers

who are already tinkering with the stuff.

783

00:40:45,609 --> 00:40:48,612

There are so many people who are using AI

and building their own agents

784

00:40:48,612 --> 00:40:51,482

or creating,

you know, side businesses on the weekends

785

00:40:51,482 --> 00:40:52,983

who could also be resources for this.

786

00:40:52,983 --> 00:40:57,421

And that's the culture that will create

new opportunities, new business models.

787

00:40:57,688 --> 00:40:58,656

And they're going to learn

788

00:40:58,656 --> 00:41:02,493

what these new paradigms will look like

by doing the work in that space.

789

00:41:02,860 --> 00:41:05,729

That then can be diffused

across the organization.

790

00:41:05,729 --> 00:41:07,731

And that's the second most important part.

791

00:41:07,731 --> 00:41:10,968

Once you have the knowledge,

do you have the infrastructure

792

00:41:10,968 --> 00:41:14,104

set up to diffuse

that knowledge as fast as possible

793

00:41:14,305 --> 00:41:17,141

and as thoroughly as possible

across the organization?

794

00:41:17,141 --> 00:41:18,409

Otherwise, it just is.

795

00:41:18,409 --> 00:41:20,611

Compartmentalize it. Compartmentalize

it. It dies on the vine.

796

00:41:22,012 --> 00:41:22,446

Right.

797

00:41:22,446 --> 00:41:22,980

And I'm glad.

798

00:41:22,980 --> 00:41:25,983

I'm glad. Ian, you used the word culture.

799

00:41:26,450 --> 00:41:28,652

Because I'm curious.

We talked about martech law.

800

00:41:28,652 --> 00:41:30,120

We talked about the need to.

801

00:41:30,120 --> 00:41:33,290

I don't know if we use these word,

but bend the curve upward

802

00:41:33,591 --> 00:41:36,660

to try to keep pace with technology,

to try to compete,

803

00:41:37,194 --> 00:41:39,296

you know, to what degree does

culture play a role there?

804

00:41:39,296 --> 00:41:42,333

Is it the most important thing

is that in the top like

805

00:41:42,433 --> 00:41:45,102

and if it's not the most important,

what is the most important?

806

00:41:45,102 --> 00:41:49,640

I do think it's the most important thing

because if you if you don't have a culture

807

00:41:49,640 --> 00:41:53,777

or can't create a culture

that is willing to lean in and say, hey,

808

00:41:54,178 --> 00:41:57,781

things are going to look so different

in the next couple of years

809

00:41:57,781 --> 00:41:59,383

that we won't even recognize it.

810

00:41:59,383 --> 00:42:01,719

It's up to us to make that change.

811

00:42:01,719 --> 00:42:04,922

You're not going to get there

if everyone is waiting for the vision

812

00:42:04,922 --> 00:42:08,225

to be given to them to take action,

it's already too late.

813

00:42:08,859 --> 00:42:11,562

And that's one of the biggest challenges,

is a lot of organizations.

814

00:42:11,562 --> 00:42:14,565

We built this expectation

that when the CEO

815

00:42:14,565 --> 00:42:17,835

gives the vision,

then people act and people stand there.

816

00:42:18,335 --> 00:42:23,073

If people aren't leaning in and saying,

I'm in R&D too, like I, I'm actively

817

00:42:23,073 --> 00:42:26,310

in research and development of what

my own role looks like in my organization.

818

00:42:26,477 --> 00:42:28,746

My own profession looks like

819

00:42:28,746 --> 00:42:31,382

because you're going to encounter this

no matter what role

820

00:42:31,382 --> 00:42:34,051

you have or what company you work at,

you go work somewhere else.

821

00:42:34,051 --> 00:42:35,586

It's still going to find you.

822

00:42:35,586 --> 00:42:38,589

So we as individuals

have to take ownership over this

823

00:42:38,689 --> 00:42:40,491

if we want to maintain relevance

in this space.

824

00:42:40,491 --> 00:42:42,493

This is not an us

versus them up versus down

825

00:42:42,493 --> 00:42:45,429

organization versus an individual issue.

It's a collective one, right.

826

00:42:45,429 --> 00:42:49,800

So if that's recognized in a healthy way

within an organization,

827

00:42:49,800 --> 00:42:53,904

that creates a camaraderie, a collectivism

that can move an organization forward,

828

00:42:55,406 --> 00:42:55,806

right?

829

00:42:55,806 --> 00:42:58,042

If everybody's kind of,

830

00:42:58,042 --> 00:43:01,245

sorry, I'm going to use the silly like,

you know, the silly idiom

831

00:43:01,245 --> 00:43:02,613

about rowing in the same direction,

832

00:43:02,613 --> 00:43:05,215

but having that purpose

and everybody kind of banding

833

00:43:05,215 --> 00:43:06,417

together to move the organization.

834

00:43:06,417 --> 00:43:09,420

But it's so true and so, so spot on. Yeah.

835

00:43:09,987 --> 00:43:13,958

I want to, you know, with that,

I want to come back to, you know, another

836

00:43:14,325 --> 00:43:16,961

kind of quote you had which is moving

from insight to foresight, which I, which

837

00:43:16,961 --> 00:43:21,999

I love, by the way, where does foresight

come from and can it come from?

838

00:43:22,299 --> 00:43:25,302

I because my sense is

it's like a lot of these tools,

839

00:43:25,569 --> 00:43:27,871

they can summarize what's already known.

Right?

840

00:43:27,871 --> 00:43:32,042

Like they aren't necessarily taking

you forward, or they're just telling you

841

00:43:32,176 --> 00:43:35,446

the sum of what we know up into this point

where where does foresight come from?

842

00:43:35,446 --> 00:43:37,581

Right. So I would actually disagree

with that a little bit.

843

00:43:38,616 --> 00:43:39,049

Okay.

844

00:43:39,049 --> 00:43:44,288

The the my perspective is that, large

language models are commodifying like they

845

00:43:44,321 --> 00:43:46,824

if you just use the large language models,

846

00:43:46,824 --> 00:43:49,493

there's a period of probably

two more years where

847

00:43:49,493 --> 00:43:52,496

you can have an advantage over

many of your your colleagues,

848

00:43:52,730 --> 00:43:57,201

but over time, it's just gonna be like,

I use email, think big whoop.

849

00:43:57,201 --> 00:43:58,502

So does everybody else.

850

00:43:58,502 --> 00:44:00,404

It's literally a commodity.

851

00:44:00,404 --> 00:44:03,140

And the difference is going to be

how do you use it?

852

00:44:03,140 --> 00:44:05,909

And then how have you encoded

your knowledge into doing that.

853

00:44:05,909 --> 00:44:09,179

But specifically on the foresight piece,

it's it's

854

00:44:09,179 --> 00:44:12,650

about searching for signals

and how you combine things as the user.

855

00:44:12,650 --> 00:44:15,653

This is a place where

we're still very much in control.

856

00:44:15,753 --> 00:44:18,422

I don't think this is the kind of thing

you want to automate.

857

00:44:18,422 --> 00:44:21,125

What you can't automate

is searching for signals of change.

858

00:44:21,125 --> 00:44:24,128

So foresight is really about finding

those,

859

00:44:24,762 --> 00:44:27,798

those data points that are outside

of the normal distribution that say,

860

00:44:28,232 --> 00:44:29,066

this is different.

861

00:44:29,066 --> 00:44:32,870

Like you should you should pay attention

over here and validate whether or not

862

00:44:32,870 --> 00:44:35,906

this is something that you should be

investing your time in or concerned about

863

00:44:36,473 --> 00:44:37,808

and in foresight.

864

00:44:37,808 --> 00:44:39,143

If you talk about formal foresight,

865

00:44:39,143 --> 00:44:41,278

there's probable, plausible and possible

futures.

866

00:44:41,278 --> 00:44:42,346

There's a whole bunch of

867

00:44:42,346 --> 00:44:45,482

structure around it to create really good

thinking about what's to come.

868

00:44:46,083 --> 00:44:48,786

But I think that can overwhelm

and overcomplicate people.

869

00:44:48,786 --> 00:44:51,989

We all have a responsibility

to think about foresight.

870

00:44:52,156 --> 00:44:53,824

What does my role look like

871

00:44:53,824 --> 00:44:56,627

in a world where I actually don't

have to go to six meetings a day?

872

00:44:56,627 --> 00:44:57,928

Oh my gosh, sounds amazing.

873

00:44:57,928 --> 00:44:59,430

But what's my new responsibility?

874

00:44:59,430 --> 00:45:01,131

Because it's more on me now, right?

875

00:45:01,131 --> 00:45:05,035

And like not thinking that through puts

you on your back foot

876

00:45:05,536 --> 00:45:08,772

and it makes you subservient

to the vision of whatever else

877

00:45:08,772 --> 00:45:10,374

is happening around you.

878

00:45:10,374 --> 00:45:12,810

So when it comes to foresight,

we should be thinking about,

879

00:45:12,810 --> 00:45:15,179

well, what if this happened?

How would I react?

880

00:45:15,179 --> 00:45:18,382

And it's not about fortune

telling or predicting the future.

881

00:45:19,049 --> 00:45:22,219

It's about seeing the signals and patterns

that are starting to arrive

882

00:45:22,653 --> 00:45:26,223

and understanding the scenarios

of how might that affect me?

883

00:45:26,490 --> 00:45:27,691

How might I react

884

00:45:27,691 --> 00:45:30,661

so that when something does actually come

your way, you can say, oh, you know,

885

00:45:30,994 --> 00:45:34,965

I've seen something that looks like this

before, or this rhymes with something else

886

00:45:34,965 --> 00:45:38,702

we've already thought through,

and you're adapting versus reacting.

887

00:45:38,702 --> 00:45:41,071

You're proactive versus reactive.

888

00:45:41,071 --> 00:45:44,374

And I think the best organizations in

the world do an enormous amount of that.

889

00:45:44,875 --> 00:45:48,679

The ones that don't are the ones

that really do get caught by surprise.

890

00:45:48,679 --> 00:45:51,415

And we see a lot of enterprises

in that space right now.

891

00:45:51,415 --> 00:45:56,253

But I do think that the

the foresight is where we need to lean,

892

00:45:56,487 --> 00:45:59,289

because it's also where we can have

a lot more of our human agency

893

00:45:59,289 --> 00:46:03,627

using the models and the AI

and the tools to bring the data into us,

894

00:46:03,627 --> 00:46:05,462

to help us identify what those what our

895

00:46:05,462 --> 00:46:08,198

what's different and say,

what does it actually mean to me?

896

00:46:08,198 --> 00:46:11,702

And using as a thought partner

in getting to getting to clarity.

897

00:46:12,903 --> 00:46:13,637

Right.

898

00:46:13,637 --> 00:46:16,874

So, you know, on the note

of what it means to me and to,

899

00:46:17,141 --> 00:46:19,943

to be honest, you know, I'm, I'm surprised

900

00:46:19,943 --> 00:46:22,946

and very intrigued to hear you say that

more of the foresight

901

00:46:23,180 --> 00:46:26,617

can be done by these tools

than maybe we imagined before.

902

00:46:26,917 --> 00:46:31,688

And I'm curious, and this is sort of a

self-serving question, for for both of us.

903

00:46:31,688 --> 00:46:37,561

But what role does an organization

like Signal and Cipher play in this world?

904

00:46:37,561 --> 00:46:39,463

Right. Is this something

that all other tools can do it.

905

00:46:39,463 --> 00:46:40,998

I can do it.

906

00:46:40,998 --> 00:46:43,333

You know, we don't need partners

to help us with this.

907

00:46:43,333 --> 00:46:46,336

Where does an organization like yours

come into play to help

908

00:46:46,603 --> 00:46:49,640

actually accelerate,

you know, traditional enterprises?

909

00:46:49,640 --> 00:46:50,340

Absolutely.

910

00:46:50,340 --> 00:46:53,177

So the to create a little more clarity

around that.

911

00:46:53,177 --> 00:46:56,180

I don't believe that the AI tools can do

them, do this on their own.

912

00:46:56,613 --> 00:47:00,150

But I think that they can facilitate

our own work in coming to

913

00:47:00,150 --> 00:47:03,153

an understanding of what possible

and plausible futures could look like.

914

00:47:03,420 --> 00:47:07,291

So a lot of the research

that one would do to do, you know,

915

00:47:07,357 --> 00:47:09,560

future scanning and signal scanning

916

00:47:09,560 --> 00:47:13,363

to find these opportunities

we should be looking into can be massively

917

00:47:13,363 --> 00:47:16,800

accelerated, scaled

and assisted using large language models.

918

00:47:16,800 --> 00:47:19,503

It's still up to us to say,

how does this fit with my strategy?

919

00:47:19,503 --> 00:47:23,040

How does this fit with the market dynamics

that I'm seeing play out?

920

00:47:24,007 --> 00:47:24,474

So it

921

00:47:24,474 --> 00:47:27,511

expands and augments

our capability to do it, and it makes it

922

00:47:27,511 --> 00:47:31,648

so people who are unfamiliar with

this can dive in even faster.

923

00:47:31,815 --> 00:47:34,818

So it's less intimidating

to get into that space.

924

00:47:34,952 --> 00:47:38,822

There will be more and more automation

of that as time goes on.

925

00:47:39,156 --> 00:47:43,627

And who knows, maybe in five seven years

we could actually say, okay,

926

00:47:43,627 --> 00:47:45,562

just go run and create,

927

00:47:45,562 --> 00:47:47,397

you know, do a monte

Carlo simulation times

928

00:47:47,397 --> 00:47:49,199

a thousand for me

and pull this all together

929

00:47:49,199 --> 00:47:52,202

and then give me that data

and tell me what my future looks like.

930

00:47:52,302 --> 00:47:54,304

I don't think it'll be that simple, but

931

00:47:54,304 --> 00:47:57,307

there could be a world that looks like,

932

00:47:57,374 --> 00:48:00,244

but for the work that we're doing,

933

00:48:00,244 --> 00:48:04,848

our focus is on helping organizations

get that to become part of their culture.

934

00:48:04,848 --> 00:48:06,316

So it comes from training

935

00:48:06,316 --> 00:48:08,919

that comes from building that data layer

that goes on top.

936

00:48:08,919 --> 00:48:11,321

A large language model

encoding their knowledge

937

00:48:11,321 --> 00:48:14,057

so that they can understand

how the signals that come in from

938

00:48:14,057 --> 00:48:15,926

the outside

world are going to impact them.

939

00:48:15,926 --> 00:48:17,861

How might they respond to that?

940

00:48:17,861 --> 00:48:20,864

And also scaling

the internal workings of the organization

941

00:48:20,864 --> 00:48:23,767

so they can be more efficient

and effective?

942

00:48:23,767 --> 00:48:26,770

Things we talked about at the very

beginning, we're not eliminating that,

943

00:48:27,070 --> 00:48:30,440

but what we're doing

is expanding the capacity and ability

944

00:48:30,440 --> 00:48:33,443

for them to operate in spaces

they never could have before.

945

00:48:33,443 --> 00:48:38,215

So were that changes is organizations

might say, well, okay, I can use this.

946

00:48:38,215 --> 00:48:41,385

And now I only need a three person

marketing team instead of a 25 person

947

00:48:41,385 --> 00:48:43,620

marketing team. Company A might do that.

948

00:48:43,620 --> 00:48:47,491

Company B might say, hey,

for the last three years we probably had

949

00:48:47,491 --> 00:48:52,296

if we go back and look at our backlog,

3 or 400 products or projects

950

00:48:52,462 --> 00:48:55,799

that we would love to pursue, tested

and gotten data on,

951

00:48:56,133 --> 00:48:59,703

that there's no way we'd

have a team of 500 that we would need.

952

00:48:59,970 --> 00:49:01,538

But you know what?

953

00:49:01,538 --> 00:49:06,143

Now we could do that with 25 and all of a

sudden running simulations, right?

954

00:49:06,176 --> 00:49:09,613

Putting products together, testing things,

getting that data becomes

955

00:49:09,613 --> 00:49:12,616

possible

at an enterprise scale from a small team.

956

00:49:12,916 --> 00:49:16,353

And you're exploring new opportunities

in unknown territories.

957

00:49:16,987 --> 00:49:20,290

So you have this expansive

mindset versus a contracting mindset.

958

00:49:20,490 --> 00:49:23,427

One works very well

with industrialist capitalist mindset.

959

00:49:23,427 --> 00:49:25,796

One works

very well in a time of transition

960

00:49:25,796 --> 00:49:28,832

where new markets, economies, and form

factors are starting to develop.

961

00:49:28,932 --> 00:49:30,567

But we don't know what they look like yet.

962

00:49:30,567 --> 00:49:34,104

So that's what we encourage companies

to do, is say, rather than saying,

963

00:49:34,104 --> 00:49:38,408

you're going to lay off 50% of workforce

and do more with less, do more

964

00:49:38,408 --> 00:49:43,213

with the same expansive skill sets, right,

expand capacity, expand possibility.

965

00:49:43,613 --> 00:49:45,816

And that is really where

we see the most value and

966

00:49:46,883 --> 00:49:48,051

I want to talk.

967

00:49:48,051 --> 00:49:51,388

I love the I love the dual approach there.

968

00:49:51,388 --> 00:49:53,323

And it makes it makes complete sense

to me.

969

00:49:53,323 --> 00:49:57,361

I'm curious with the the second scenario

you talked about where it's 25 people

970

00:49:57,361 --> 00:50:01,064

or 500 new products or tests or what

have you.

971

00:50:02,065 --> 00:50:03,433

One of the things I've found,

972

00:50:03,433 --> 00:50:06,603

and I'm curious if you've seen it too,

or you've seen something different, is

973

00:50:07,537 --> 00:50:11,908

in this emerging world where technology

isn't the limiting factor anymore.

974

00:50:11,908 --> 00:50:16,013

And it's like, if you can dream it,

you can build it, you can test it

975

00:50:16,680 --> 00:50:21,752

at some point, the like,

the bottleneck becomes the market,

976

00:50:21,752 --> 00:50:26,023

or it becomes your staff,

or in some sense, it's people's ability

977

00:50:26,023 --> 00:50:29,026

to to like,

actually try and digest new things.

978

00:50:29,493 --> 00:50:35,198

And my sense is you have to still get back

to like prioritization in some capacity.

979

00:50:35,198 --> 00:50:38,535

Because even if the technology

can give you 500 new things,

980

00:50:38,735 --> 00:50:40,670

you're going to be limited somewhere.

981

00:50:40,670 --> 00:50:44,641

Do you buy that

and what are the implications?

982

00:50:44,641 --> 00:50:46,076

I absolutely do.

983

00:50:46,076 --> 00:50:49,479

I think that what that does is

it shows another weakness

984

00:50:49,479 --> 00:50:53,116

in the current paradigm for the future

that we're trying to create.

985

00:50:53,483 --> 00:50:57,954

We go through these phases of oftentimes

150, 200,

986

00:50:57,954 --> 00:51:01,224

300 years,

where the economic paradigm also shifts.

987

00:51:01,458 --> 00:51:05,829

So the one that we're currently in

is identical to the one where

988

00:51:05,829 --> 00:51:09,766

we built the steam engine and connected

geographically disparate places

989

00:51:10,467 --> 00:51:13,637

are the metrics that we use are

still the same ones that we used with

990

00:51:13,637 --> 00:51:17,107

some modifications when the steam engine

was a cutting edge technology.

991

00:51:17,474 --> 00:51:18,708

So what that does,

992

00:51:18,708 --> 00:51:21,711

it shows that the paradigm that we're in

is kind of the ultimate bias.

993

00:51:22,279 --> 00:51:24,047

A paradigm shows you what's important.

994

00:51:24,047 --> 00:51:26,383

What do you measure,

what questions are worth asking.

995

00:51:26,383 --> 00:51:28,285

And all of those are still very much

996

00:51:28,285 --> 00:51:32,055

directed towards the capitalist system

that we have now.

997

00:51:32,055 --> 00:51:33,690

And I'm not saying this to capitalism

versus

998

00:51:33,690 --> 00:51:35,525

socialism versus Marxism type of argument.

999

00:51:35,525 --> 00:51:38,528

It's what is capitalism 8.0 look like

1000

00:51:38,562 --> 00:51:42,065

in order

to start to expand its, environment.

1001

00:51:42,065 --> 00:51:44,668

So these new types of businesses

could become possible.

1002

00:51:44,668 --> 00:51:47,070

So there will be fully autonomous

organizations

1003

00:51:47,070 --> 00:51:48,872

that have zero humans evolved.

1004

00:51:48,872 --> 00:51:50,941

And what does that look like?

1005

00:51:50,941 --> 00:51:53,443

It's not a full replacement for humans.

1006

00:51:53,443 --> 00:51:56,446

That would be like saying

the digital office replaced paper.

1007

00:51:57,180 --> 00:51:59,249

It obviously did not.

1008

00:51:59,249 --> 00:52:02,953

That digital killed analog

analog is still is absolutely decreasing.

1009

00:52:02,953 --> 00:52:05,789

But it's not zero.

And it won't ever be zero in my opinion.

1010

00:52:05,789 --> 00:52:10,527

But it creates this fragmentation of what

we saw as like the dominant paradigm.

1011

00:52:10,861 --> 00:52:13,897

And it creates space for coexistence

of all these new middle,

1012

00:52:14,131 --> 00:52:17,167

models, mental models,

operational models and economic models.

1013

00:52:17,601 --> 00:52:19,469

We don't know what those look like

just yet

1014

00:52:19,469 --> 00:52:21,872

because we haven't seen many of them

succeed.

1015

00:52:21,872 --> 00:52:25,175

We're seeing some signals

when we look at companies that are,

1016

00:52:26,042 --> 00:52:28,612

let's say, on the lean AI leaderboard,

which is a reference I love,

1017

00:52:29,579 --> 00:52:29,913

you know, the

1018

00:52:29,913 --> 00:52:33,350

average 3.3 million average revenue

per employee.

1019

00:52:34,284 --> 00:52:36,553

You know, time to scale

is absolutely insane.

1020

00:52:36,553 --> 00:52:39,422

And we look at these organizations

that are AI native,

1021

00:52:39,422 --> 00:52:42,259

they're starting to show what

some of those paradigms could look like.

1022

00:52:42,259 --> 00:52:46,630

If you extrapolate that from, you know,

ten people, 50 million are and say,

1023

00:52:46,630 --> 00:52:49,633

what would it look like with one person,

150 million are

1024

00:52:50,167 --> 00:52:53,003

what apparatus and infrastructure

would you need?

1025

00:52:53,003 --> 00:52:56,006

What would it look like to operate

as that individual?

1026

00:52:56,039 --> 00:52:57,641

And that can give you

some of those signals.

1027

00:52:57,641 --> 00:52:58,975

I was talking about earlier

1028

00:52:58,975 --> 00:53:01,978

of what possible problem

plausible futures could look like.

1029

00:53:03,380 --> 00:53:05,482

But I do think that

1030

00:53:05,482 --> 00:53:09,052

how we look at capitalism

today is going to change dramatically.

1031

00:53:09,052 --> 00:53:12,689

And it's not just a technological

question, it's a social question.

1032

00:53:12,756 --> 00:53:15,192

It's an economic question,

geopolitical question.

1033

00:53:15,192 --> 00:53:17,761

And that's why I as all of those as well.

1034

00:53:17,761 --> 00:53:20,697

So these things are all coming together

at the same time.

1035

00:53:20,697 --> 00:53:22,065

And that's another reason

people kind of feel

1036

00:53:22,065 --> 00:53:25,802

like they're being thrown off balance

in every direction, because everything is

1037

00:53:25,802 --> 00:53:26,803

changing all at once.

1038

00:53:28,171 --> 00:53:29,105

Right?

1039

00:53:29,105 --> 00:53:32,342

So throughout this conversation,

I feel like I've started to be able

1040

00:53:32,342 --> 00:53:36,446

to put together a mosaic

of like your view of the future through,

1041

00:53:36,446 --> 00:53:39,849

you know, a series of different lenses

and also some spaces where you say,

1042

00:53:39,849 --> 00:53:42,852

you know what, there's still too much

uncertainty here.

1043

00:53:43,720 --> 00:53:45,055

Is there anything you can tell me

1044

00:53:45,055 --> 00:53:48,258

about, like your predictions

for the next 5 to 10 years

1045

00:53:48,258 --> 00:53:52,529

that we haven't covered that, like, you're

pretty confident we're going to see?

1046

00:53:52,562 --> 00:53:54,064

Yeah.

1047

00:53:54,064 --> 00:53:55,966

I would say that the, the paradigm around

1048

00:53:55,966 --> 00:53:59,002

training, skill sets and education

is going to change dramatically.

1049

00:53:59,369 --> 00:54:00,870

And that has profound implications

1050

00:54:00,870 --> 00:54:03,840

for the work that we do

and how we go about that.

1051

00:54:03,907 --> 00:54:04,808

One of the things I talk about

1052

00:54:04,808 --> 00:54:08,678

is skill flux, and it's this concept

that we go from this paradigm of,

1053

00:54:08,712 --> 00:54:11,248

you know, 30 years ago,

you could have a skill set

1054

00:54:11,248 --> 00:54:14,251

that lasted you 30 years before a shelf

life was obsolete.

1055

00:54:14,818 --> 00:54:19,089

Now, you know, someone like me, I had

a skill set that was, you know, ten years.

1056

00:54:19,089 --> 00:54:20,357

It was, valuable.

1057

00:54:20,357 --> 00:54:24,294

I started off as a mobile strategist for,

an agency.

1058

00:54:24,661 --> 00:54:26,263

You don't hire those anymore.

1059

00:54:26,263 --> 00:54:28,298

It just doesn't happen. Right?

1060

00:54:28,298 --> 00:54:29,432

You might at an enterprise level,

1061

00:54:29,432 --> 00:54:32,802

if you're like Cisco and doing software,

but not in that environment.

1062

00:54:33,136 --> 00:54:37,607

And the skill sets that are valuable

are shortening on their shelf life.

1063

00:54:37,841 --> 00:54:39,843

And for more technical skill sets,

1064

00:54:39,843 --> 00:54:42,412

those are a rising

and disappearing faster than ever.

1065

00:54:42,412 --> 00:54:45,415

So now we're at like two and a half years

for technical skill set

1066

00:54:45,615 --> 00:54:48,451

and I could see that shrinking

more and more and more is the point

1067

00:54:48,451 --> 00:54:52,222

where many of them are rising very quickly

and gone the next day, six months.

1068

00:54:52,989 --> 00:54:55,458

To give you an example, I think coding

1069

00:54:55,458 --> 00:54:58,395

and, prompt engineering

are two versions of that.

1070

00:54:58,395 --> 00:55:01,398

So prompt engineering became something

it was relevant about two years ago.

1071

00:55:01,731 --> 00:55:03,600

I would give that maybe a five year

1072

00:55:03,600 --> 00:55:07,437

shelf life

max before it's no longer relevant at all.

1073

00:55:07,437 --> 00:55:10,440

And we're already seeing agents

being able to take on a lot of that work.

1074

00:55:12,042 --> 00:55:14,944

But there will also be a new skill set

that you'll have to learn in order

1075

00:55:14,944 --> 00:55:18,415

to operate in a new paradigm

with new technology and new objectives.

1076

00:55:18,815 --> 00:55:22,452

So we're going to see this exponential

increase in importance and value.

1077

00:55:22,852 --> 00:55:25,989

And a ChatGPT moment that comes in

says that's not valuable anymore.

1078

00:55:25,989 --> 00:55:27,157

That's gone right.

1079

00:55:27,157 --> 00:55:30,960

And that's going to have this almost like

whiplash effect for us as we go along.

1080

00:55:30,960 --> 00:55:35,098

That changes how we educate ourselves

is if we're frontloading education

1081

00:55:35,098 --> 00:55:37,434

for the first quarter of our lives,

we're out of date.

1082

00:55:37,434 --> 00:55:39,035

By the time we walk out of university.

1083

00:55:39,035 --> 00:55:42,972

And this is not a new discussion at all,

but it becomes exacerbated by that.

1084

00:55:43,206 --> 00:55:44,841

So the idea of lifelong learning,

1085

00:55:44,841 --> 00:55:47,510

you know, very cliche,

but micro credentialing,

1086

00:55:47,510 --> 00:55:50,480

we call it surge skilling, where it's like

you're actually having to get very deep

1087

00:55:50,480 --> 00:55:53,516

into something very, very quickly

to create competitive advantage.

1088

00:55:53,917 --> 00:55:57,320

And then you just know

that this is going to be less valuable

1089

00:55:57,620 --> 00:55:58,922

in a certain period of time.

1090

00:55:58,922 --> 00:56:02,392

But what is valuable

is being that first mover and creating

1091

00:56:02,392 --> 00:56:05,462

value with it as fast as possible

before it before comes obsolete.

1092

00:56:05,595 --> 00:56:08,598

So that's where I see education changing,

1093

00:56:08,698 --> 00:56:11,801

where I see people shifting their focus

for competitive advantage.

1094

00:56:12,202 --> 00:56:15,972

And this the culture of an organization

changing too, because you're going

1095

00:56:15,972 --> 00:56:17,440

to have to keep learning on the job.

1096

00:56:17,440 --> 00:56:20,710

And the tools and the

AI as you're using, will have to teach you

1097

00:56:21,077 --> 00:56:23,380

how to work with it as they change.

1098

00:56:25,382 --> 00:56:27,050

So I'm really glad, Ian,

1099

00:56:27,050 --> 00:56:28,985

that that was your answer,

because that was on my list of things

1100

00:56:28,985 --> 00:56:31,988

that I wanted to talk to you about that

we hadn't gotten to yet.

1101

00:56:32,922 --> 00:56:36,960

With that in mind, these the

the shortening time horizon of skills

1102

00:56:36,960 --> 00:56:42,098

you mentioned, you know, it's going

to have massive implications on education.

1103

00:56:42,232 --> 00:56:43,733

What do you see as being the risks

1104

00:56:43,733 --> 00:56:47,370

and the opportunities

for the traditional education system?

1105

00:56:48,037 --> 00:56:52,308

And also, what does it mean for like

the hiring process of organizations?

1106

00:56:52,475 --> 00:56:53,343

Absolutely.

1107

00:56:53,343 --> 00:56:56,379

So it completely disrupts

the one to many broadcast model,

1108

00:56:56,379 --> 00:56:59,382

like the idea of a teacher

standing in front of a room and speaking

1109

00:56:59,382 --> 00:57:02,385

for an hour

and a half to three hours is gone.

1110

00:57:03,420 --> 00:57:05,088

The which is great for people like me.

1111

00:57:05,088 --> 00:57:07,590

I was a terrible student,

super neurodivergent.

1112

00:57:07,590 --> 00:57:09,793

I can't sit in a class on the lesson

for more than five minutes.

1113

00:57:09,793 --> 00:57:11,127

I have to be engaged.

1114

00:57:11,127 --> 00:57:14,130

So what this is going to do,

it will disrupt the current model,

1115

00:57:14,164 --> 00:57:17,000

but it will make it amenable

to a much larger

1116

00:57:17,000 --> 00:57:21,438

group of people who are not built

for the more industrial ask

1117

00:57:22,539 --> 00:57:25,141

manufacturing like education model.

1118

00:57:25,141 --> 00:57:27,610

The challenge, though,

and I don't say that with

1119

00:57:27,610 --> 00:57:31,214

with any malice towards

teachers and educators.

1120

00:57:31,214 --> 00:57:34,451

They are some of the most underresourced,

overtaxed and over

1121

00:57:34,484 --> 00:57:36,319

expected people in the world.

1122

00:57:36,319 --> 00:57:39,322

Then you take a look at the dynamic

in the US and how hostile it is.

1123

00:57:39,522 --> 00:57:42,325

I have so much empathy

for people who choose

1124

00:57:42,325 --> 00:57:45,328

to go into a life of service

for the next generation.

1125

00:57:45,462 --> 00:57:48,998

We need to be spending

a lot more time and money in that space.

1126

00:57:48,998 --> 00:57:51,501

And I make a comment in my keynote

where I say

1127

00:57:51,501 --> 00:57:54,504

the land budget should be as big

as your technology budget,

1128

00:57:55,338 --> 00:57:57,841

and that kind of like, people

look bug eyed at me.

1129

00:57:57,841 --> 00:57:58,741

Like what?

1130

00:57:58,741 --> 00:57:59,843

Like what we're spending.

1131

00:57:59,843 --> 00:58:01,811

So we're spending trillions of dollars

on technology.

1132

00:58:01,811 --> 00:58:04,080

I love that, I love that, yeah.

1133

00:58:04,080 --> 00:58:07,884

But if we don't like the technology's

moving faster than any other sector,

1134

00:58:07,884 --> 00:58:09,619

faster in the economy, fashion,

1135

00:58:09,619 --> 00:58:11,955

the society is moving

faster and education's moving.

1136

00:58:11,955 --> 00:58:16,025

And if we truly want to understand

where humans play in that picture,

1137

00:58:16,626 --> 00:58:19,462

the fact that we're investing

everything we have in technology

1138

00:58:19,462 --> 00:58:22,832

has already indicated our preference

for technology over humans,

1139

00:58:23,800 --> 00:58:26,669

so that math has to balance out a bit.

1140

00:58:26,669 --> 00:58:31,174

We have to figure out how do we invest

so much more into education?

1141

00:58:31,174 --> 00:58:33,243

Not so much less.

1142

00:58:33,243 --> 00:58:36,179

And until we do that,

we are going to be behind the ball.

1143

00:58:36,179 --> 00:58:38,214

We are going to have a target on our back

in many ways,

1144

00:58:38,214 --> 00:58:41,751

because if the paradigms don't change,

the technology just gets better.

1145

00:58:42,018 --> 00:58:44,087

We're going to suffer the consequences.

1146

00:58:44,087 --> 00:58:47,524

But if we put ourselves

front and center of that equation,

1147

00:58:47,857 --> 00:58:50,860

we have the chance and the opportunity

to figure that out.

1148

00:58:51,594 --> 00:58:53,396

Right? It's wow.

1149

00:58:53,396 --> 00:58:57,467

Yeah, it's

it's as you said it like this is not

1150

00:58:58,535 --> 00:58:59,569

an incremental shift.

1151

00:58:59,569 --> 00:59:03,172

This is like a complete disruption

of the model from end to end,

1152

00:59:03,473 --> 00:59:04,440

without a doubt.

1153

00:59:04,440 --> 00:59:07,577

And even for people who live and breathe

it like it's overwhelming for me,

1154

00:59:07,977 --> 00:59:10,413

I do this 24 seven.

I love it, I'm passionate about it.

1155

00:59:10,413 --> 00:59:12,148

I'm excited about where we're going

1156

00:59:12,148 --> 00:59:15,151

and net net,

I'm optimistic about the long term future,

1157

00:59:15,818 --> 00:59:19,022

but we are all pioneers right now,

whether we want to be or not.

1158

00:59:19,556 --> 00:59:23,026

And when people we've kind of bastardized

the term pioneer,

1159

00:59:23,026 --> 00:59:25,194

we've made it seem like,

oh, it's Richard Branson on the cover

1160

00:59:25,194 --> 00:59:28,197

of entrepreneur magazine with his billions

of dollars of success, like

1161

00:59:28,231 --> 00:59:30,867

he was a pioneer at one point in time.

1162

00:59:30,867 --> 00:59:34,170

But yeah, high nears

through really hard shit

1163

00:59:34,170 --> 00:59:37,574

and they go to places

where there's no infrastructure.

1164

00:59:37,740 --> 00:59:41,477

They suffer the consequences of,

you know, decisions that they didn't know

1165

00:59:41,477 --> 00:59:42,211

they'd have to make.

1166

00:59:42,211 --> 00:59:45,181

They are attacked by the environment

that they're in.

1167

00:59:45,181 --> 00:59:47,584

Nature tries to kill them

in a number of different ways. Yeah.

1168

00:59:47,584 --> 00:59:51,321

And as a super resilient species,

we still make a way forward.

1169

00:59:51,554 --> 00:59:54,157

We construct the environment

after we figure it out.

1170

00:59:54,157 --> 00:59:55,658

You know, we might show up in Hawaii

1171

00:59:55,658 --> 00:59:59,362

with no shoes on and realize, oh, crap,

I'm not properly equipped for this.

1172

00:59:59,629 --> 01:00:02,332

And then we figure a way out that pattern.

1173

01:00:02,332 --> 01:00:03,433

Time to go from

1174

01:00:03,433 --> 01:00:07,170

not knowing to knowing can be really hard,

painful, and challenging.

1175

01:00:07,437 --> 01:00:11,541

But the way we thrive

once we do is absolutely amazing.

1176

01:00:11,874 --> 01:00:15,278

So I would say that we are going

to have amazing things happen,

1177

01:00:15,578 --> 01:00:19,082

but we're also going to have to encounter

some really tough growing pains

1178

01:00:19,349 --> 01:00:21,417

individually

and collectively to get there.

1179

01:00:21,417 --> 01:00:24,187

So if anyone is saying otherwise,

it's absolutely smoke and mirrors,

1180

01:00:25,421 --> 01:00:26,222

right?

1181

01:00:26,222 --> 01:00:29,192

Right. Wow. Exciting times ahead.

1182

01:00:29,292 --> 01:00:30,393

There's one more question

1183

01:00:30,393 --> 01:00:32,629

that I wanted to ask you

that I haven't had a chance to yet,

1184

01:00:32,629 --> 01:00:35,632

which is I wanted to ask you the

the inverse of what I just asked you,

1185

01:00:35,698 --> 01:00:36,633

which is, you know,

1186

01:00:36,633 --> 01:00:39,636

aside from, like, what is going to happen

and what's going to disrupt us,

1187

01:00:40,770 --> 01:00:43,373

is there anything you're hearing right

now, hype wise,

1188

01:00:43,373 --> 01:00:46,542

technology wise,

trend wise, that you're like, that's B.S.

1189

01:00:46,576 --> 01:00:48,845

like that's

not actually going to come to pass.

1190

01:00:48,845 --> 01:00:51,481

We're being sold a bill of goods.

1191

01:00:51,481 --> 01:00:54,984

Yeah, I actually I think the agents

conversation is way over heights.

1192

01:00:56,152 --> 01:00:58,321

I think they are transformative.

1193

01:00:58,321 --> 01:01:01,324

I don't know, a single organization

that is going to say, I'm

1194

01:01:01,324 --> 01:01:04,861

going to let an autonomous

series of agents run my enterprise

1195

01:01:04,861 --> 01:01:08,498

that I've spent decades building,

without the oversight necessary.

1196

01:01:08,498 --> 01:01:10,833

Like, we've

we've been working with agents for years,

1197

01:01:10,833 --> 01:01:14,404

and we've been building setups

where agents will work with other agents

1198

01:01:14,404 --> 01:01:17,407

and giving them autonomy and creating

virtual environments to see what happens.

1199

01:01:17,540 --> 01:01:18,975

And every time we let them run amok,

1200

01:01:20,043 --> 01:01:21,010

it's frightening.

1201

01:01:21,010 --> 01:01:24,580

Like it is absolute, like jaw dropping.

1202

01:01:24,580 --> 01:01:26,349

Oh my gosh,

I can't believe that would have happened.

1203

01:01:26,349 --> 01:01:27,617

So glad I didn't get them.

1204

01:01:27,617 --> 01:01:30,620

Freedom to access real live data.

1205

01:01:30,687 --> 01:01:31,654

Yeah.

1206

01:01:31,654 --> 01:01:33,790

And that that infrastructure

needs to be built.

1207

01:01:33,790 --> 01:01:37,794

The there are actions that agents can do

that are absolutely mind blowing.

1208

01:01:38,094 --> 01:01:39,529

But they're narrow.

1209

01:01:39,529 --> 01:01:41,831

They're specific. They're structured.

1210

01:01:41,831 --> 01:01:44,267

And they have strong guardrails.

1211

01:01:44,267 --> 01:01:47,303

The idea that we can kind of

have this almost,

1212

01:01:47,970 --> 01:01:50,573

reinforcement learning, you know,

give it a million different examples,

1213

01:01:50,573 --> 01:01:53,576

let it kind of like bang around,

figure its way through approach

1214

01:01:53,710 --> 01:01:57,780

to unleashing it in

the organization does not work.

1215

01:01:58,781 --> 01:02:00,516

Because the infrastructure is

just not there yet.

1216

01:02:00,516 --> 01:02:03,319

It hasn't caught up

with the promise of the technology.

1217

01:02:03,319 --> 01:02:05,621

So I think we're very much at the top

of the hype cycle of agents.

1218

01:02:05,621 --> 01:02:08,458

We're going to have this crash

into the trough of disillusionment,

1219

01:02:08,458 --> 01:02:12,261

which in my opinion, is the best place

for a nascent technology to be.

1220

01:02:13,096 --> 01:02:15,264

A lot of people say less bad,

but what it means is

1221

01:02:15,264 --> 01:02:18,134

the people who are making promises,

who don't know what they're talking about.

1222

01:02:18,134 --> 01:02:21,904

And let's face it, there's an enormous

amount of people who are rushing to find

1223

01:02:21,904 --> 01:02:25,842

the gold that have no business being here

and making promises.

1224

01:02:25,842 --> 01:02:27,944

They disappear

because it's now it's getting hard.

1225

01:02:27,944 --> 01:02:29,612

You actually have to deliver.

1226

01:02:29,612 --> 01:02:33,416

And in the trough of disillusionment,

it pulls all the pundits out.

1227

01:02:33,783 --> 01:02:36,319

And now the people who are committed

to doing the work,

1228

01:02:36,319 --> 01:02:38,521

who are there for the right reasons,

they get to work

1229

01:02:38,521 --> 01:02:40,890

and they build that infrastructure

that's necessary

1230

01:02:40,890 --> 01:02:43,893

to deliver on all those promises

we were making back here.

1231

01:02:43,893 --> 01:02:46,662

So it takes time,

and I'm just kind of waiting

1232

01:02:46,662 --> 01:02:49,665

for that to kind of implode on itself

1233

01:02:49,732 --> 01:02:52,335

and for people to see like,

oh yeah, these are very, very powerful.

1234

01:02:52,335 --> 01:02:54,637

This is absolutely

the paradigm of the future.

1235

01:02:54,637 --> 01:02:57,840

But the future is still the future,

not the present.

1236

01:02:57,907 --> 01:02:59,308

We need to get there first.

1237

01:03:00,676 --> 01:03:01,310

Right?

1238

01:03:01,310 --> 01:03:02,478

I love that answer.

1239

01:03:02,478 --> 01:03:07,717

And, I think it's so appropriate right now

given where we are in that hype cycle.

1240

01:03:07,717 --> 01:03:10,887

So, thank you for taking some of the air

out of that one.

1241

01:03:11,053 --> 01:03:11,854

That's awesome.

1242

01:03:11,854 --> 01:03:13,589

One of the things I would

maybe I can put a finer

1243

01:03:13,589 --> 01:03:17,093

point on is the metrics piece, and that is

the expansive versus constructive.

1244

01:03:17,460 --> 01:03:20,463

So what I was talking about earlier,

as I was mentioning,

1245

01:03:20,830 --> 01:03:23,766

a lot of teams are going to say

let's let's do more with less.

1246

01:03:23,766 --> 01:03:26,469

Let's pull back the number of resources

we have and get along

1247

01:03:26,469 --> 01:03:29,972

and have higher efficiencies, greater

margins and better stockholder returns.

1248

01:03:30,473 --> 01:03:34,277

And a challenge that we have

is we're moving into a paradigm

1249

01:03:34,277 --> 01:03:37,313

that is going to shape

what matters and what matters,

1250

01:03:37,313 --> 01:03:40,316

and what's valued in the work

that we do is going to be different.

1251

01:03:40,516 --> 01:03:43,886

But when what matters changes,

but the metrics do

1252

01:03:43,886 --> 01:03:47,223

not and the incentives do not. Yeah, yeah.

1253

01:03:47,223 --> 01:03:50,726

That means you run right into a paradigm

that is going to push back on

1254

01:03:50,726 --> 01:03:54,096

you and potentially hurt you

as an organization.

1255

01:03:54,564 --> 01:03:57,700

So we encourage organizations

in time of change

1256

01:03:58,234 --> 01:04:01,103

to also understand

how is this going to change the incentives

1257

01:04:01,103 --> 01:04:04,440

and the metrics that are used to measure

that change as it's happening.

1258

01:04:04,707 --> 01:04:08,311

So we're thinking more about growth

metrics, metrics of innovation, metrics

1259

01:04:08,311 --> 01:04:12,949

that are about charting the unknown versus

optimizing the known.

1260

01:04:13,382 --> 01:04:16,686

We've come from a paradigm of optimizing

the known for the last 150 years.

1261

01:04:16,686 --> 01:04:18,187

We're really good at it.

1262

01:04:18,187 --> 01:04:21,290

The problem is how much is known

about the next five years.

1263

01:04:21,791 --> 01:04:25,862

So if we're doing 95% of our metrics

on optimizing the known,

1264

01:04:25,862 --> 01:04:29,732

5% on exploring the unknown,

that means you're already out of date.

1265

01:04:30,399 --> 01:04:33,536

If we're starting to push more of that

towards exploring and charting

1266

01:04:33,536 --> 01:04:37,974

this unknown territory, this makes us more

prepared for what's going to be coming.

1267

01:04:37,974 --> 01:04:41,244

This gives us the opportunity

to think about innovation quotient

1268

01:04:41,611 --> 01:04:45,615

in, knowledge diffusion across

the organization, building the structures

1269

01:04:45,781 --> 01:04:48,818

that will make you resilient

in this future paradigm.

1270

01:04:49,118 --> 01:04:52,121

Because right

now, optimization organization is scale

1271

01:04:52,421 --> 01:04:55,558

by definition, require

some calcification of the organization.

1272

01:04:55,558 --> 01:04:59,395

It needs to be rigid in some ways

in order to be efficient.

1273

01:05:00,029 --> 01:05:03,933

And rigidness against

an oncoming wave is a recipe for disaster.

1274

01:05:04,200 --> 01:05:06,702

So that's one of the things

we encourage organizations to think up to.

1275

01:05:06,702 --> 01:05:11,007

And we get very deep into

what is that metric, what matters for you?

1276

01:05:11,007 --> 01:05:13,209

How is it specific to your context?

1277

01:05:13,209 --> 01:05:14,610

What are the things that you measure?

1278

01:05:14,610 --> 01:05:16,646

How do you actually do that work?

1279

01:05:16,646 --> 01:05:20,082

And when that clarity is there, all of a

sudden it goes from, well, we don't know.

1280

01:05:20,082 --> 01:05:23,586

The future brings to at least

we know how to move in that direction.

1281

01:05:25,054 --> 01:05:25,888

Right.

1282

01:05:25,888 --> 01:05:28,891

And with respect to the fact that I'm sure

there's lots of different metrics

1283

01:05:28,891 --> 01:05:30,393

for different organizations,

1284

01:05:30,393 --> 01:05:34,830

is the answer to like,

just move to a new set of hard metrics

1285

01:05:34,997 --> 01:05:38,534

or get more comfortable with the notion

that we need to be flexible

1286

01:05:39,001 --> 01:05:42,271

and measure things with a little bit

more flexibility than we have in the past.

1287

01:05:42,271 --> 01:05:44,674

Absolutely.

That that's typically the first step.

1288

01:05:44,674 --> 01:05:48,811

You never want to shift entirely because

you kind of want to leave what's working?

1289

01:05:48,811 --> 01:05:49,645

Working.

1290

01:05:49,645 --> 01:05:52,648

So we don't say you've measured this way,

don't do that anymore,

1291

01:05:52,848 --> 01:05:56,285

but at least a portion of the work

that's being done needs to be done

1292

01:05:56,285 --> 01:05:57,653

in this forward facing way.

1293

01:05:57,653 --> 01:06:00,656

And that type of work

needs to be measured differently.

1294

01:06:00,890 --> 01:06:04,293

Because if you were measuring,

for example, a lot of teams,

1295

01:06:04,627 --> 01:06:07,563

a lot of tiger teams, a lot of innovation

teams are measured by ROI

1296

01:06:07,563 --> 01:06:10,733

on their first run,

which is mind boggling to me.

1297

01:06:10,733 --> 01:06:11,434

Okay, right.

1298

01:06:11,434 --> 01:06:14,704

You're going to have impact on margin

the first time you touch ChatGPT

1299

01:06:15,705 --> 01:06:18,040

know that that doesn't happen.

1300

01:06:18,040 --> 01:06:20,309

And yeah,

I think that's almost a bad example

1301

01:06:20,309 --> 01:06:22,244

because that's just ludicrous

on all levels.

1302

01:06:22,244 --> 01:06:24,246

But if you're thinking

about scale efficiency,

1303

01:06:24,246 --> 01:06:27,883

margin impacts on things

that are by definition going to require

1304

01:06:27,883 --> 01:06:32,021

investment and time,

you're already impeding the work

1305

01:06:32,021 --> 01:06:35,024

that is going to help you

explore unknown territory.

1306

01:06:35,291 --> 01:06:37,259

Yeah. Now it's it's super interesting.

1307

01:06:37,259 --> 01:06:40,730

And yeah, I'm sure we could talk

for another hour just on just on that.

1308

01:06:41,397 --> 01:06:42,631

With that in mind, though,

1309

01:06:42,631 --> 01:06:45,601

you know, I did want to say a big

thank you for joining me today.

1310

01:06:45,801 --> 01:06:47,370

This has been super, super interesting.

1311

01:06:47,370 --> 01:06:48,637

And it's honestly been a real treat.

1312

01:06:48,637 --> 01:06:52,441

I talk to a lot of people in this space,

and I'm just continuously blown away

1313

01:06:52,441 --> 01:06:55,411

by the breadth

and the depth of insights that you have.

1314

01:06:55,778 --> 01:06:57,613

In this space. So I wanted to say a big

thank you.

1315

01:06:57,613 --> 01:06:59,682

Thanks, Jeff. It's been an honor to join

you. I really enjoyed it.