I have an AI workforce [music] with 34

AI agents that are working around the

clock for me.

>> 34 agents?

>> And I'm [music] now saying, "Actually,

that was two chapters." There are AI

super users, they have higher risk

tolerance, and [music] they are going to

sprint past you.

>> The majority of CEOs I talked to

>> They might actually show up pretty well

on these shareholder calls, but that's a

speech that was written by someone else.

The pace of change is going [music] to

be faster than I think it is. It is

always faster.

>> Should this be forced on workers?

>> [music]

>> the heck out of your workforce and

inspire them and motivate them and make

sure that they're seeing positive

examples so that they want to do this.

>> How has this changed corporate America?

>> Ooh, so many things. One [music] that is

starting to happen right now

>> All right, welcome to new episode of

Power Players. I'm really excited for my

next guest here. We're going to talk

about all things AI and how I'm probably

using it totally, absolutely, completely

wrong. Allie K. Miller is here, Open

Machine CEO. Good to see you.

>> Good to see you. I That is the purpose

of this podcast, actually, [laughter]

to make fun of you.

>> Well, also too, like like you are real.

You're not your AI agent. You're real,

I'm real,

like

>> There are a lot of social comments

asking me if I'm AI. This is real.

>> [laughter]

>> So So, for those not familiar with the

company, talk to me about Open Machine.

>> I work with a lot of Fortune 500

companies, private financial

institutions, AI labs, AI startups, and

just help everyone transform into the

business that they're meant to be

leading or career that they're supposed

to be leading in the AI age. So, it's a

lot of There's some education, there's a

lot of advising,

uh it's a lot of conversations behind

closed doors that I try and bring the

learnings onto chairs like these.

>> What did you What got you to Open

Machine? Where did you start your

career?

>> Oh, I started in AI almost 20 years ago

and was doing

>> Yeah.

>> [laughter]

>> Just more acronyms.

Uh so, I started doing uh ML research in

college and I was doing stuff in natural

language processing and um about 10 more

than 10 years ago decided to a like the

rest of my life to AI and every single

day for the last decade plus I've been

working in it. So I was at IBM, launched

the first multimodal AI team there, was

at AWS, was the head of

AI for startups and venture capital,

built that into a multi-billion dollar

business. And then summer 2022, I was

like the next model is going to blow our

minds, right? Because GPT

3 had come out end of 2020 and it was

just so obvious what the scaling law was

looking like. It was so obvious to

people in the space every day. And so I

quit my job to build a startup and then

the next thing that came out was ChatGPT

and not a model. And I literally burned

our business model, like took the

business plan, lit it on fire on a

stove, moved to New York 5 days later

because I was on a road trip and from

that point on I don't think I've slept.

>> [laughter]

>> Like I know it goes like that. I feel

you. I feel you. So I feel as though a

lot of people that are watching this or

listening to this, they

still not very familiar with like where

did AI even come from. Someone who's

been doing this for decades, like

decades like 20 years like what 20 years

um

how's it changed over that time period?

>> So we've had the term AI for 70 years

and for the first many decades it was

a lot of rules-based systems hoping to

make computers look and behave like

humans would. But a lot of it was you

take this in and every time you see

this, please give me that. And it was

again meant to appear as if it were

doing human tasks. Um starting really

around like I would say 2012,

we started to have some big shifts

around very large data sets where

we started to have a lot more learnings

around deep learning. And so you could

take these really really large data sets

and start to extract some interesting

patterns which then when faced with

brand new data, you went wait a second,

I've seen stuff like that before.

Let me jump in and help. And so maybe it

was in spaces like image understanding

or maybe reading comprehension. And

really in the last couple years we've

seen an explosion in image generation,

video generation, video editing, uh

coding for certain

um and so that that generative AI has

been around for decades, but like good

generative AI because of the scale,

because of algorithms, because of how

much data we have and cleaning process,

all that stuff really only in the last

couple years. I would say since, you

know, GPT-2 have we been able to see

this like really big hockey stick

moment. And then basically we've had a

hockey stick moments every 6 months

since. Like ChatGPT, I think so many

people thought of ChatGPT as like, "Oh,

that was the thing." And now it is

mid-2026 and now it's changing again.

No, we had a really big change end of

2024 and another really big change end

of 2025. And the average consumer and

the average business leader did not

notice that.

>> What changes should they expect next?

What are you seeing?

>> So, it's it's easy when we think about

what has happened up until now and then

you can kind of predict the future a

little bit more easily. Uh and for what

it's worth, I do uh publish my AI

predictions every year. I've done it for

the last 8 years. So, you can see what I

predicted.

>> They've all been right. I they've all

been right. I Listen, my batting average

is actually really strong. I look, I was

doubting you

I WAS DOUBTING

>> WANT to draft me.

>> [laughter]

>> I WAS DEFINITELY not doubting you at

all.

>> Um okay, so so end of 2022 we get

ChatGPT, which is also getting new model

in there. It was GPT-3.5

and all of a sudden you have this model

that can yap back and forth with you for

thousands of tokens, doesn't forget

every single thing you've ever said, has

some guardrails where it's not telling

you how to make bombs, whatever. And so

it's it's decent.

End of 2024 we start to get reasoning

models. These are models who would kind

of be like, "Thank you, Brian, for your

question." And would kind of go off

here, start to think through

step-by-step things on its own, um then

would come back to you with uh hopefully

a better answer. Because of those

reasoning steps, as these models got uh

were able to take on more information at

once and were able to kind of paralyze

out different workflows and bring it

back to itself. We got the ability for

AI agents to actually perform, because

you would give me a very vague task, me

being the the AI. I would go over here

and I would go, "Okay, Brian wants me to

plan for this interview with Ali." which

I'm sure you did it on your own, but

let's just say this. So, once me to plan

for my interview with Ali, first thing I

got to figure out who Ali is and so

therefore I might fire off a research

task. Then I should figure out what

episodes have performed well. So, I'm

going to look at the YouTube and see all

the ones that got over 100,000 views,

whatever.

And so, that end of 2025 was really

taking the harnesses that we have, which

is like the cloud code codex of the

world,

combining it with very, very strong

reasoning models and the combination of

those two now gets us to

I have an AI workforce with 34 AI agents

that are working around the clock for

me. Right? I I literally, even if I had

had that idea 2 years ago,

>> I couldn't manage 34 agents.

>> So, I only have to manage one,

technically. Like the the whole thing

that people should be doing right now.

If you want to be the most up-to-date in

2026 in AI, what should you be doing?

You should be building the system that

allows for work and tasks and goals and

whatever to be optimized. And so, you

should be thinking, how am I putting

goals into this system? That's a really

big one. How am I connecting the system

into context? So, for the example with

you, does it connect into YouTube and

can it see all your previous things?

Does it connect to your desktop and can

it see all the upcoming shows that are

not yet published on YouTube, but that

you're working on? Does it have access

to your email so that it can see all the

conversations that you've had with your

producers to see what shows are getting

delayed or what topics are really hot if

it's looking, you know, at Reddit or

online forums to be able to see what's

trending.

So, as you're thinking about giving it

goals, gathering context, that is really

that system that I'm building up. So, I

manage just my AI chief of staff, who is

my AI chief of staff.

>> I do.

>> You're You're badass as

>> You can't You can't hire him.

>> I'm trying not to curse. I like have to

realize like I'm not in a bar right now.

Like I mean I don't want to curse.

>> I I curse.

>> That's effing awesome. That's just

really cool.

>> And and I think what is cooler, because

any anyone can have that like single AI

agent that's doing

um

uh wide tasks for them. I think where it

gets interesting is that so Simon has

six directs that are named after the

Friends characters.

>> Simon's your chief of staff.

>> Simon's the AI chief of staff. Yeah. And

then underneath Simon, there's Chandler,

Joey, Monica, Rachel.

>> From Friends for you folks out there.

>> Rachel does the client work because she

handles clients very well. Monica is

obviously operations. Phoebe is just

like the wackadoo in the corner just

like dreaming. Ross is education. Joey's

product. Chandler's marketing. And

underneath them, they have

to like task-based agents.

The coolest person, AI person, that I

brought into the workforce

is not anyone that I've already named.

I've named 33 now. The 34th is that I

gave Simon an AI assistant. And so this

AI assistant's entire job is just to be

like a watchdog looking over the whole

system going, "That's wrong. That's a

lot of friction. How come every single

time we do this task, she keeps giving

us feedback like this? Every time we do

this task, how come we're missing memory

on this?" And so it's like a gap

analyzer. It's a watchdog. And I think

what people are realizing now is that we

used to hire jobs like marketing manager

or producer or whatever. And because of

AI, because at the margin you can

basically hire any AI agent you want.

All of a sudden you can hire for any

role ever.

Right? Maybe you're only getting 5% of

the value.

>> I love you all. You're all you're all

human and you're all my favorite.

>> to have

>> [laughter]

>> this. Love you guys.

But but in addition to that like human

producer, maybe that human producer

wishes that they had this research

watchdog that could look over all of

your competitors or contemporaries to

see what they're doing. They wouldn't be

able to hire a human for that, right?

Because maybe the revenue didn't make

sense or the time for how long a human

would take to do that task didn't make

sense. But now you can just bring that

in. And then by the way, if there's no

value behind it, you can spin it down.

But all these things are fractions of a

dollar to be able to test out all of my

agents run within my $200 a month

subscription. So this is not like the

stories, you know, tokenomics of like,

"Oh my god, she's burning million." No.

Everyone in my company, we spend about

like 6, 7K per head. And all of the

workforce stuff that I'm talking about

is within that subscription.

>> one agent, let's say I'm new to AI

today, how do I create an agent?

>> Yeah.

Like like truly new, you've never opened

up Chat GPT.

>> know anything about really technology.

Let's say

>> god.

>> Let's say I'm my mom. I'm not going to

give my mom the age away Let's just say

she's older than me for obvious reasons.

How would she go about creating an

agent?

>> Okay. If I am Mrs. Sassy.

>> Yes.

>> Um which what a dream.

>> [laughter]

>> I

I thought she was amazing. Okay, I'm

going to step one, open up my laptop.

>> Okay.

>> Uh I'm going to probably navigate to

something like Claude.ai or

chat.openai.com as a default just to

create an account. Then I would download

the desktop app for either of these

things. And for, you know, ease of the

rest of the example, let's just say it's

Claude. So you download the Claude

desktop app. There's going to be tabs

that you can switch between. You switch

into Claude code. Now basically you're

sitting in the agentic platform. Instead

of sitting in chatbot land, you're

sitting in agent land. You're sitting in

task land.

The next thing that I would do if I was

your mom or someone like that is I would

open it up and I would literally just

say into that black box, white box, tan

box, whatever, "What do you do?"

Right? I think a lot of people jump in

and they think that they should prompt

with like, "Build me an AI agent that

every morning at 9:17 a.m. tracks my

daily morning briefing and summarizes my

count."

Like, the average person, the best first

step that you can do is open this and

just rant about a problem. Like, switch

to dictation mode, rant about a problem,

and then end it with, "Help me think of

something really creative, interview me,

ask me questions, learn about me, you

know, don't jump into action, take your

time, plan." And the way to build an

agent is literally in any of these

systems, you say the word "build me an

agent that".

I had a a session with some CHROs

yesterday. So, heads of HR of companies

that have tens of thousands of people.

And I showed them a screenshot of a

prompt where I said, you know, "Build me

an AI agent that." And I literally got a

text afterwards going,

"I have heard the term AI agent for now

over a year.

No one told me that I just open up this

thing and say, 'Build me an AI agent

that.'"

All these things are very natural

language-based. And again, in the

absence of your mom knowing exactly what

problem she wants to solve, I just tell

people complain. And then ask the AI how

you can be supported.

>> you keep your 34

employees, including your chief of

staff, your AI chief of staff, how do

you keep them current? How do they stay

updated?

>> So, when that assistant finds faults,

then I'll jump in. But I also, again, at

the margin, you can hire anyone, I have

constant watchdogs look AI watchdogs

looking over my workflows. So, at the

end of every single week, it's tracking

all the things that I worked on and

comparing it to my goals.

And saying, "Did we just get closer? If

not, why not? What are the gaps? What

should we be solving for? What could

solve for that? Should we redo a

workflow that isn't working anymore? Did

she used to use this workflow five times

a week and now she hasn't used it in the

last month and we can spend it down.

So, it is constantly analyzing that on a

weekly basis. And so, my Fridays are

actually kind of crazy because I get all

this influx from my AI systems. I get a

readout of how goal-aligned I am, a

readout of every single urgent email I

haven't replied to. I have a revenue

engineering workflow where every single

week, I think on Tuesday mornings, I get

a readout of how much money is waiting

for me in my inbox. And it tracks where

every single dollar is in my business.

And it is calculating likelihood of

close, likelihood of joy, right? I'm not

just chasing revenue, I'm chasing

whether that revenue is ally-aligned.

>> to be joyful.

>> Yes. Yes.

>> How do you Do you unplug at all? How do

you like Do you ever pull yourself out

of this AI digital world?

>> so um what what I have learned that as I

talk to more people that are, you know,

these AI superusers, which I would

absolutely put myself in that category.

Um what I've heard from them and what I

feel too is that as our work lives

become very, very, very AI-enabled, it

is actually allowing us to completely

separate when we want to separate. So,

like I went on a 1-month expedition to

Antarctica and didn't have internet that

entire time and had technically for that

I had AI like posting for me while I was

gone.

>> Your team is still working hard for you.

These 34 AI this this team of AI.

>> And so, I think like I, you know, again,

I'm going on hikes, I'm stepping away,

and things like AI on my mobile phone,

AI through dictation, I am able to now

walk like I feel like I'm more

physically fit than I was a couple years

ago because I'm able to bring this stuff

away from my laptop. Like I think if you

had looked at me working at a very large

tech company, you know, a couple years

ago, I was glued to my chair until 2:00

a.m. and now I can bring that work, not

that I, you know, always want to bring

my work out, but I can get outside, I

can be more active. So, I think that

that's helpful.

Um and the the bigger change, which um

is, you know, you can decide whether to

have a good work-life balance or not,

but the bigger change is in 2026, the

really, really intense superusers

are not actually delegating work off to

AI.

>> [clears throat]

>> This is a really weird thing, right?

Because most people haven't even built

AI agents. And I'm now saying,

"Actually, that was two chapters ago."

So, build AI agents, build multiple AI

agents, run it as a workforce, delegate

stuff to the workforce. The next step

that almost no one has gotten to is that

actually you're building the system

where the AI agents are going, "Let me

check on that. Let me take this off her

plate. Why did this just come in? Let me

go ahead and handle that for her."

And I am managing the escalations that

come back to me.

So, I might have four or five parallel

workstreams happening, and then I might

be on a walk, and my AI agent is going

to say, "Hey, we just found these five

things. We went ahead and drafted these

four replies. How do you want to manage

this last one?" So, it feels a little

bit less like I am the direct manager of

this system, and more that I'm like the

SVP above the system.

>> were having this conversation

40 years ago, your 34

>> 40 years ago?

>> I'm just saying 40 years. 40 years.

>> Your 34 agents would have been humans.

Like, when you're inside these big

companies,

>> My 34 agents would have been humans, and

I only would have had a couple of them

because of how much I could afford, of

how much I could manage, of how many

resources they had. So, I wouldn't have

had 34.

>> does this what does this AI agent world

mean for the future of the workforce?

Especially as you're talking to HR

departments, these in in a lot of cases

where these layoffs are coming is HR,

it's backroom technology, it's support

functions.

>> Yeah, and I don't believe that the

layoffs are attributed to I don't

believe that they're actually caused by

AI. I believe that they're heavily

attributed to AI because it helps stock

prices, but um I think that if I were to

look at the AI agents and conversations

that I've had with people and HR leaders

and also finance leaders, marketing

leaders. The the general sense that

people have right now is that we're

going to have a hybrid workforce. And

that if you look at systems today like

the ability to run something called

dynamic workflows inside of cloud if

anyone wants to look it up,

it's kind of the ability to run massive

parallel workflows that can spin up

thousands of agents.

So right now I told you that my AI chief

of staff has a name and his directors

have names.

Within that they, Rachel or Ross, might

fire off a request for a thousand agents

to all run in parallel to all search,

you know, different forms, different

websites.

Um maybe like

uh if you're going to a conference and

you have 500 names that are attending

the conference,

you could ask ChatGPT to look up name

one. Wait, wait, wait. Look up name two.

Wait, wait. Or you could ask Codex and

say, "Here's the list. Fire off 500

agents and you get back the answer in 30

seconds instead of waiting an hour for

everything to finish."

So that hybrid workforce, some of them

are are named and shared entities where

you and I are teammates, human

teammates, and we are both

uh enabled and supported by AI and I

want to talk more about that.

And also there's these temporary agent

support systems of thousands of agents

that are being spun up to help on coding

projects or whatever.

>> Where

you know, I think I really do believe

this is going to require a massive

retraining of the workforce.

>> Yeah, and not just the tool part. It's

so much more on the mindset should

>> Should should this be like should this

be forced on workers? Like you need to

know how to make a freaking agent or you

shouldn't be here because I'm listening

to you and these agents are driving

massive productivity and if I'm the CEO

or the CFO of a company, I'm like

everybody needs to know how to create

15,000 agents.

>> Yeah. If it were forced on you, would

you do it joyfully?

>> I

Well, if I want to keep my job, yeah. I

mean, force on me. I I want to I want to

learn. Because if if it's not forced on

me, I me maybe I don't try it.

>> Yeah, so I think here here is So, I I am

blessed with, you know, millions of

followers, and what that means is that

they DM me with what they're feeling.

>> Sure.

>> General sentiment is that when you come

from a work culture that has never

required any training other than like,

you know, don't bribe the government

type

>> type training.

>> Yes.

>> Good training.

>> Great training. Very important.

>> [laughter]

>> What happens in those workforces is that

they go, "Whoa, whoa, whoa. Why are you

requiring this? I feel like I'm being

forced into it. You're not letting me

move at my own pace." And there tends to

be a stronger hesitancy. Um and so, in

cultures that have never had that

requirement, I I actually don't

recommend that it gets required. I

recommend that you incentivize the heck

out of your workforce and inspire them

and motivate them and make sure that

they're seeing positive examples so that

they want to do this. Right? And then I

think you'll be able to inspire them,

and I can give tips there. The um the

other piece though is that I have worked

at companies like Amazon, we were

required to take quizzes, tech quizzes

every single month. Our VPs were

measured on that. If we finished it

earlier, they might have gotten a bonus

from it. Like, that was part of the

culture. Was like, hardcore test-takers.

And of course, you would have required

that sort of training at a company like

that cuz it was already baked into the

culture. So, I wouldn't need to take

advantage of that. Vast majority of

companies are not going to fully require

it, but they might incorporate it into

their performance management system,

where they say, "Part of the way that

you're getting evaluated is how you're

using AI to multiply yourself or to

improve the quality of your work or to

improve the morale of other people

around you or to

grow the revenue that your team is

pulling in or to decrease churn rate."

Like, whatever other metrics matter, but

you would expect that they make it easy

for you to get the actual training, make

it easy for you to see great examples,

make it easy for you to access agentic

platforms and not just chatbots.

And make it easier for you to do the

right thing. And that means also having

good governance in place. But most

companies have not given all those

things on a silver platter. And so they

still have low low high-quality

adoption.

>> How do you see this these agents or this

technology changing the role of the CEO?

>> Well, okay. So right now, well, forever,

this the role of the CEO is I set the

vision,

I am corralling the system, right? Which

largely is people to be able to drive

toward this, and I am responsible for

shareholder return or stakeholder if

it's more privately held.

If I'm the CEO, the first thing that I

have to think about is how does my

vision change or how does the velocity

of that vision change with AI in mind?

And that is a very

uh uh not a hollow view, but it is a

very like uh blind blinders view, where

I am wholly focused on what I do as a

company, me me me.

What I think the majority of CEOs are

not paying enough attention to is the

fact that if you have AI and you're

enabling everyone and everyone just got

10% more productive and you feel really

good about that,

what you're forgetting is that there are

AI superusers who are much higher, you

know, they have higher risk tolerance,

they are way deeper into these tools

than your workforce is, and they are

going to sprint past you. So the threat

of smaller businesses against incumbents

is higher than it has ever been and will

only continue to increase. The motes of

what that CEO is thinking of are

plummeting.

And so if you're only thinking about

this in CEO vacuum, and you're only

thinking about how do I make my

workforce more effective so that we can

drive more shareholder value, how can I

think about our customers and how to

serve them more efficiently or

effectively, you are going to lose the

the bullet train like flying by you. Um

and you're only going to focus on like

the very slow bike that you're on. So if

I'm a CEO, one of the most important

things is actually to test out these

tools. Majority of CEOs I talk to have

never built an AI agent. And they talk a

big game like they're in these

boardrooms and

>> I think they're still stuck in the a

decade, you know, past. You know, they

they have at least a public company.

Earnings calls this way, they're going

to meet investors, they're going to do

they they still have not

adapted to this day and age. And they're

not going to.

>> And they might actually they might

actually show up pretty pretty well on

these shareholder calls and talk about

AI and talk about how they're using it,

but that's a speech that was written by

someone else.

>> That's correct.

>> And so if I'm presenting I speak in

board meetings, I speak with execs and

exec teams. If I sit down with an

executive team,

I might hear, "Oh, we're all in. We

can't wait." And then I pull them into

one-on-one meetings and I learn two

things very very quickly. Number one,

they have or three things I guess.

Number one, they have not yet caught up

to 2026 AI. And enterprises are always

going to have a little bit of a lag, so

that's to be, you know, expected. So

they're not yet at today's AI levels.

Number two is at least one person in

that excom on the leadership team, the

executive committee, is definitely not

using AI and probably a detractor and

doesn't want their department using it

and they think their whole department's

going to go away if they don't use it.

>> And the third is that it's probably

it's probably the case that the point

person or one of the point people,

again, assuming they're it's outside the

CTO role, but a non-technical executive,

I pull them aside and they go, "Friend

to friend, what the hell's an AI agent?"

Right? And these are brilliant business

minds that are running

companies that are making tens of

billions, a hundred billion plus

dollars,

and they are brilliant. They just are so

busy that they're looking for that

signal among noise. And so, one of the

things that I do as an advisor is I go,

"Let me summarize the last 5 months for

you and give you the three things that

you actually have to know. Let us build

this thing together so that you I can

watch you have that aha moment, and then

you can go back to leading in the way

that you need to lead."

So, I think a lot of CEOs, again,

they're not using the tools. If they

are, they're not using it at 2026

levels. And if they're even doing that,

then they haven't figured out how the

motes and competitive advantages have

completely flipped toward compounding

gains. Right? My AI system and your

future AI system, cuz obviously we're

going to get you to build one out as

well.

>> you.

>> Of course.

>> [laughter]

>> As they say, we'll take that offline.

We'll take that offline, yeah.

>> Okay. You're going to have an AI system,

I have mine, and the the glorious part

of this, the delicious amazing part as a

business techie when I look at this, is

watching that system improve without me

whipping the hand of every single AI

agent going, "Uh, can you make this 2%

better?" It is improving without me

having to constantly jump in. Much in

the way that a human workforce does as

well, that a CEO doesn't have to

constantly jump in, that VPs and

directors and senior managers take that

on.

If you can imagine running a very, very

large enterprise, and your challengers

have these systems that are not only

allowing them to do the work of a

thousand people with only 30,

but that system is improving every day

or every week,

you are at a greater disadvantage with

every single coming week.

Like, it's crazy to me that people have

401ks and they can't figure out the idea

of compounding gains with AI.

>> Yeah.

One more for you. Um, and I'm going to

lean into your expertise at really good

predictions. Five years from now,

how has this technology changed

corporate America?

>> Ooh, so many things. Um

So, I think one that is starting to

happen right now is the blurring of

lines of jobs.

And so, there was a recent OpenAI report

that is fascinating that I encourage

everyone to read, where OpenAI they

looked into 800,000 ChatGPT messages.

And remember, this is standard chats,

not Codex, whatever. But, they looked

into 800,000 messages. And they looked

at the work-related messages. And what

they found is across the board

that nearly half of people's messages,

so like if I'm in whatever sales, nearly

half of my messages were not related to

sales, and they were related to other

functions.

And if you look at this graph, designers

are using AI more for engineering than

they are for design. Finance, they're

using AI more for marketing than they

are for finance. HR, they're using AI

more for finance than they are for HR.

So, all of these lines are getting

blurred. I have a really hard time

imagining that anyone is going to want

to hire someone with as niche of a title

as like SEO specialist or something in 5

years. Because what you're actually

trying to do right now, what workforces

are trying to aim toward, is getting as

many A players as possible and giving

them wider scope and giving them these

growth-oriented tasks, right? Not just

productivity. And that is kind of what

the the work of the future looks like.

I have very strange predictions around

voice. I think voice AI is actually the

interface of the future. I have a hard

time picturing that open offices are

going to work when you have a lot of

people yapping to their AIs. I went into

the headquarters of WhisperFlow in San

Francisco. All of them have gooseneck

microphones, and they're all just

whispering into their

>> Really? So, no more keyboard?

>> It's a I mean, they still have one. Um

but

>> I would I could chuck my mouse across I

like I just I use VR still. And like I

just want to like pinch, I want to do

the Minority Report, like zoom in, zoom

out. That is all I want. And so I think

I think in 5 years I can imagine there

a lot more voice

on subways, in the street, at work,

which I think has negative consequences.

Like I don't want to walk around hearing

people yap to their AIs all day. Um and

so companies are going to have to think

about that. I think we'll have a good

early sense of what an AI-first device

looks like. Right? So OpenAI has shared

that they're going to show what the

device looks like in 2026 and start

selling it in 2027. So

>> It's going to be a pendant. It's going

to be a pendant.

>> We'll we'll see.

>> One of the two.

>> Um So I think we'll get some senses of

device, a lot happening in voice,

blurring of jobs. Um those are those are

some of the stronger predictions, but my

my louder prediction that I hope every

single person feels is that

if I'm a CEO or CFO or or a busy parent

of five and I'm just trying to survive

my work day,

the number one thing that I would be

paying attention to is the pace of

change. Right? How fast are these models

getting better? How fast are new models

getting rolled out? How fast are we able

to add on new features inside of these

AI tools, etc.

And I would be looking at that pace of

change. And I would be thinking, how can

I build a little bit more flexibility, a

little bit more adaptation into my work

day, into my career plans? And I would

be

assuming that the pace of change is

going to be faster than I think it is.

If you had If we had had this

conversation 10 years ago, I would have

said that we would have been here in

like 2040.

And so even all of my friends where we

worked in AI every single day,

I have not talked to a single person

whose timeline [clears throat] has had

to get longer. Right? Maybe in a like

weeks, months sort of trade-off, fine.

But in terms of AI capabilities on an

annual let's check in with each other

basis.

It is always faster.

Things like robots, hardware, I think

it's way far off.

We should expect that these systems are

going to be very reliable

at a quarter's worth of work that it

would have taken an entire team to

accomplish and that it'll be able to

complete all of that in hours.

>> Sorry team, I know we're going to go

over time, but I can't help myself. Did

you have your agent like research me

before you came on here?

>> No.

>> No, I was just curious. I'm just

curious. I had to I had to It's like you

just like

>> I had to assume and I think that human

you say that.

>> [laughter]

>> I feel as though you just took me to

clue school on all of this.

Let's go create that AI system stuff.

>> [laughter]

>> Good to see you Ali. I appreciate it.

>> Thank you for having me.

>> That's it for this episode of Power

Players. Appreciate all that love.