Ryan Roslansky: Turning AI anxiety into skills for the future of work

It's an uncertain time right now in the world of work.

There's a lot of anxiety.

It feels like the old playbooks, you know, aren't relevant anymore.

Maybe the new playbooks haven't even been written yet.

And sometimes when you're mired in the technology, and especially with AI, and you kind of draw out where you know, where this could potentially going to go, it leads you to, you know, some dark places and some uncertain places.

And Aneesh and I wanted to take this moment to write the book not as a crystal ball of what's going to happen in the world, but more, I think, as a framework to help people start to think through how you can turn uncertainty into opportunity.

how you can turn uncertainty into opportunity.

The future isn't written on this.

It's in our hands.

That's Ryan Roslanksy, CEO of LinkedIn and a Microsoft executive vice president.

Ryan leads the LinkedIn platform that connects more than a billion professionals worldwide.

Ryan and his colleague, Aneesh Raman, have written a new book.

It's called “Open to Work.”

A practical guide to navigating your career in the age of AI.

We talk about AI’s potential impact on all our jobs and careers.

It's both a challenge and an opportunity.

After all, the human brain predates the Industrial Age by millennia, and human beings have shown an extraordinary ability to adapt to each technological advance.

But to make the most of this opportunity, we each need to combine a sense of where technology is going with practical advice.

And Ryan has a lot of good practical advice to share.

Including how to think about your current job not as a title, but a collection of tasks, and then use this understanding to build on your strengths and add to your skills.

The future may be a lot more promising than you think, if we get this right.

My conversation with Ryan Roslansky, up next on Tools and Weapons.

Ryan, it's great to sit down.

I have been looking forward to this conversation for a long time.

Because you and your colleague, Aneesh Raman at LinkedIn, have been working on a book that has now reached the shelf.

“Open to Work – How to Get Ahead in the Age of AI.”

I love the title, because a lot of times people are asking hard questions like, “Is there a way for me to get ahead?”

“Will I be left behind?”

You and Aneesh offer so many insights about where the world and where the world of AI are going.

Thanks for having me, Brad.

Thank you for, you know, the inspiration that you, kind of gave to write- to write the book as well.

And so my colleague, Aneesh Raman and I, from LinkedIn, had the idea basically to evolve what we've been doing for decades on the LinkedIn platform.

A platform that exists to create economic opportunity for every member of the global workforce.

And right now, there's a lot of uncertainty, a lot of anxiety with the world of work through AI.

And while this is by no means a crystal ball to what the future of work holds, it is a starting point to start a discussion, and to start giving people a framework for how they can think through what's happening around them right now. How they can, you know, connect

now. How they can, you know, connect some of the dots that, you know, maybe creating some of the anxiety or the uncertainty, and hopefully then turn that uncertainty into opportunity.

And, you know, I think one of the most important things that I've thought about in writing this book and talking to people about it, is the future isn't written on this.

It's in our hands as workers, as employees, as companies, as economies, as societies, to, to figure this out together, to find the opportunity, and to create a better, world of work moving forward.

So, it's exciting to get this book out there and I look forward to talk to you about it.

Well, I mean, one of the things I think your comments reflect is you, or you and Aneesh, really have in many ways, some unique perspectives, I will say uniquely broad perspectives, because of all of the data that you get from LinkedIn, from the LinkedIn Economic Graph, and not just the data about where the world is and where the world of work is today,

but I think the perspective gained over time.

Because, as you say, for two decades, the world has been changing, jobs have been changing.

You all have been seeing those changes.

So now, as you put it, we look ahead.

Let me start with where you started in the book, the introduction.

And I think you've already alluded to a little bit of this, but I even love the title “Failure is Not an Option.”

And what you start with is really the Apollo 13 story.

Many people know it, either having read about it or watched the movie and other things. This extraordinary

story of human ingenuity, people doing things that I don't think they thought were necessarily possible, having to do them in a few days to keep three astronauts alive.

And it really was about human ingenuity.

Why did you choose that as the story with which to begin?

Yeah, it's a great question.

As you said, I mean, it's this beautiful day in 1970.

You have a set of astronauts that are taking the fifth trip to the moon.

Things are going well, and out of nowhere, you know, in a quick stir of the oxygen tank, “Boom!”

And the astronauts start to realize that they are spewing oxygen out into space and send that now famous message back to Mission Control, “Houston, we have a problem.”

And, you know, it was the the flight director, Gene Kranz, who sat there in Mission Control, started to understand what was going on, and came to the conclusion that “Everyone, stay calm. And let's remember failure is not an option.”

And I think it just resonates so well at this moment in time, which is that when you're hit with this uncertainty, we have to come together to figure this out, to use human ingenuity to think creatively is the right mental framework to be in.

This is a great example of, technology wasn't going to solve this problem.

This is a set of astronauts that had to make do with what was literally, you know, what would right now would look at like super antiquated technology that exists on this, on this spacecraft.

You know, literally in certain cases, you know, fit a square peg into a round hole and figure out a way to save themselves.

And, you know, it's a bunch of people working together, across different, you know, departments and agencies, and in space and on the ground.

And they succeeded and they, you know, they, they brought it together.

They brought themselves home.

And it's just, it's just a great, in my view, a great story for what happens when, you know, you realize failure's not an option, you bring human ingenuity to the forefront, and you're able to do great things.

One of the interesting threads that you pull on is this notion that we don't know entirely where things are going, but that doesn't mean it’s predetermined and that we don't have agency.

I have to admit, I love this because, to be honest, I feel like it's sometimes missing in our industry.

In the world of technology people can be a futurist and make a lot of predictions about what is going to happen in five or ten years.

I don't know that there's a lot of accountability or even review.

I will admit, a few weekends ago I was thinking about this and I used the Researcher agent in Copilot, and I put in a lot of the names that everybody would recognize.

And I asked for an assessment and a grade of all of the, I'll just say, luminaries, and how well they did with their predictions about what would happen in defined periods of time.

And almost everybody got between 20 and 30%.

So, you know, nobody got a passing grade.

But rather than have people make fewer predictions, people just keep making them.

But this is not what you guys do.

You and Aneesh.

In fact, what you say is, “...we won't get a lot of these answers

“...we won't get a lot of these answers for some time, in some cases decades.

We don't need these answers, however, to know what to do right now.

The most important part of all of this is that these answers are not predetermined.

Nothing about this moment is. Where we go next comes down to one thing and one thing only: the choices we make right now as individuals, organizations economies societies...”

You use that to frame the mission and what you think the mission is for the two of you as authors, really, in my view, the view of LinkedIn and Microsoft, about human innovation.

Can you say a little bit about how you think about human innovation?

What is it, and what is it that makes it most special?

What makes so many of the, you know, the greatest technology thinkers great is this idea of what the future can become.

And sometimes when you're mired in the technology, and especially with AI, and you kind of draw out where, you know, where this could potentially go, it leads you to, you know, some dark places and some uncertain places sometimes.

But oftentimes that that assumes that nothing else changes around it.

That if we were to all to stay in one place and not change and let the technology, you know, run wild, we could end up in a place that seems uncertain or scary to us.

I don't believe in that.

I believe that, you know, that humans play such an integral role in shaping where that technology should go, and understanding not only, you know, what technology can bring to bear on the upside, but how people can adapt and evolve with that along the way as well.

So much of what's exciting about AI, the AI that we use every day right now, is its ability to take certain tasks that, you know, have somehow felt mundane to us in the past, maybe we didn't want to do them, and help us do them better, give us actually more agency.

But more importantly, I think we're all starting to realize that the set of what we historically maybe called “soft skills”, which didn't seem as important, these are really important, by the way.

You know, curiosity, courage, communication compassion.

Wow.

These turn out to be some really, really important skills to, you know, do your job well.

And the focus and emphasis on those, along with AI, is what I think gives us the opportunity to dream big and paint a much more positive picture that exists with humans and technology together moving forward.

And as you say, you don't have to know every step.

No one knows every step they're going to need to take.

The most important thing is to take the first step.

That’s right.

You know, if you're early in your career, if you're later in your career, if you're a parent wanting to think about what a career for your son or daughter might mean in the future, I think this book has very practical, helpful advice.

You have a title for a chapter, “Jobs Are Tasks, Not Titles.”

But you do put tasks into different buckets.

Can you say a little bit about the three buckets that you define?

It was maybe two and a half or three years ago when, you know, you and I were first exposed as part of, you know, this great company to some of the, groundbreaking AI moves.

And someone in a meeting said something like, “Well, where does this all go?”

And off the cuff, you turned and said, “You know what?

Everybody's job is a set of tasks.

And we need to look at it like that.

And if your job is just a set of tasks that can be automated, you may need to start looking for a new job.”

And I mean, I remember writing that down really quickly when you said it, Brad, because- I have no recollection.

That's what I assume.

I'm glad you took notes.

But it's a really important framing.

And it does start to give people something practical to think about, which is that, historically, we've talked about what we do as a title.

“I'm a product manager.”

“I'm a marketer.”

“I'm a salesperson.”

And it's a great shorthand to basically bundle up what, at the end of the day, is a set of tasks to be done and how you communicate what you do.

It's important for us to actually think about our jobs not as a title, but as that set of tasks, because the more that you think about it like that, the more you can start to realize that, “Wow, there are certain tasks that AI can do really well, and that's a great thing.

But if my job is only a set of those tasks, I need to start thinking about what that means for me.”

We bucket those tasks into three buckets.

One, tasks that we, you know, feel pretty, pretty good that AI is going to automate those and can do a great job with them.

You know, “Summarize this document.”

“Translate this piece of text.”

You know, AI is going to be great at that.

The second bucket are those tasks that we feel like can really help augment what you do as a human being.

So, you know, AI can't go all the way there, but they can really give you a superpower as you realize how to use them.

The last set of tasks, the third bucket, are those things that are, so innately human or messy sometimes, that we don't believe that AI is going to be able to do those.

When you're in a meeting and people aren't agreeing on something and you have to get them to agree.

Or people who are on different pages about the direction to go when you got to bring people together talk about a strategy.

The ability to really communicate and galvanize a group of people around going a certain direction.

We bucket those into those tasks and then it's a really easy exercise, you can start to think about in your job.

“My goodness, like what do I do on a daily basis?

And you know, if I really boil that down, what percentage of my job fixing fits into each of these buckets?”

Again, it's not a crystal ball.

It's not the answer, but it's a way to start thinking about “Am I in a role right now that I need to be thinking about making a quick change?”

Or, “Am I in a role right now where, wow, I feel really, insulated into the future?”

Or, “Am I in a role where, you know what, like most people are, some of my tasks are in this bucket one, some of them are bucket two, some of them are bucket three, and how can I be great at all of these?”

But I mean, when you think about, you know, say, just that dividing line between what you rely on AI to do versus what you're now using AI to do, but you're doing it with AI.

How do you find that changing your own work?

One of the greatest things that I found so far with AI is, having Copilot built directly into Outlook, and my ability to get this long email where people are debating something, and just say, “Hey, can you explain this to me really quick? Like,

really quick? Like, what's going on or what do I need to do?”

And there's so much nuance in a lot of these discussions, and there's so much decisions that I have to make before I can make a decision or reply to email.

But I can save a good ten to 15 minutes on a topic when I can just come up to speed really quickly.

So, I love that.

And then the second thing that I've started to do quite frequently, I'll be in a situation where I have to send an important email to you or to Satya, and, and I'll ask Copilot, “Hey, how can I make this better?”

Or, “What am I missing here?”

I'm not asking to make a decision.

I'm asking it to challenge me or help me as a thought partner to make a better end product that I'm trying to make a point on.

You know, a lot of these that I'm talking about, these are bucket two tasks.

You feel like you have this superpower all of a sudden to kind of do more, with AI.

But it doesn't just happen and it does- You can't just, you know, assume that you're going to type something into some random AI and it's going to be there for you and help you.

There's a lot of work and effort that goes into this in helping it become that thought partner for you.

And, you know, your reference to curiosity.

I mean, I felt for so long that that actually is the fundamental fuel for growth, for learning.

But it is a bit of a craft and a bit of an art, even to learn how to use AI.

And in your work, how are you seeing the development of that capability, that skill?

I think everyone has their own, you know, approach to working with these tools.

And I actually think that's a great thing, because to be building this thought partner with you, it has to become so personalized to you and who you are and how you work and think.

The LinkedIn feed these days is flooded with people who are so excited to share what they are doing or learning with the various AI products that they're using.

It’s symbolic of a couple of things.

Number one, people are trying a lot of different things in their flow of work.

Right.

And not all of them hit.

But when they do, when you're able to really find like a bucket two task that makes sense, you're so excited about it that you want to share it with the world.

You know, number two, the feedback that you see on these LinkedIn posts, like, “Did you try this”, or, “Try it this way”, or, “Oh my goodness, I'm going to go and try that.”

It kind of goes back to this human idea of like, we're all trying to figure this out together, and this building of a community around these topics and how you're using it.

It's just really inspiring to watch people kind of motivating each other on and kind of talking about it and doing it.

Anyboy who's been around computers for the last ten or 20 or longer years, knows, hey, some people, they were like PowerPoint or Excel wizards.

They could do things, that most of us would go, “Wow, I wish I could do that.

I cannot.” And, it in part can be people get some formal courses, it can be online, it can be in some other format.

It might be watching a video, might be LinkedIn learning, or it might just be practice.

Yeah.

The same thing is happening here.

Even just being inside, you know, a team.

The comparisons, people say, “Wait, how did you get it to do that?”

It often- “How did you prompt it?”

“How did you use it?”

You think of writing as something that you would either do yourself or rely on.

Maybe you take a shortcut and, you know, you let your Copilot or some other, you know, chatbot write for you, and it does a good job.

But wow, I have been so struck when people really just work with it— Yeah.

—and they keep using it.

And, one of my colleagues has a habit when she gets something, she doesn't like, she says, “That's terrible.

You got to do that again.”

And it'll come back and say, “Yeah, you're right. It's terrible.”

Takes feedback better than maybe the some of the humans we work with.

But it it is a skill.

Yeah.

And it is a skill, in part, honed through practice.

We talk a lot in the book about this importance of a mindset shift of really adapting AI in your workflow or pushing yourself to adapt it.

For the future of your career it's really important to be trying these tools, and learning these tools as you would with any other skill.

We live in this technology world, and it seems like, you know, according to you and I, everyone in the world is using AI all day long.

That's not true.

To really kind of push yourself to learn about it, read about it, try it out.

I think that's an important mindset shift that folks need to be making.

You have this notion, bucket three.

You know, the tasks that are uniquely human.

And that hence AI won't do or can't do. For a huge number of jobs, there are significant parts of it that are uniquely human.

If you just, you know, think about what it means to work in sales.

You know, every company that has a product has people who are in sales.

You know, to be a lawyer.

And so often success turns on relationships that build trust.

So much of the work that matters actually involves investments of time, of building relationships, of understanding other people.

And the more people can move tasks from bucket one to bucket two, and then free up some more time for bucket three, which I think is frankly where we're often the most time constrained, people are so busy, they just think, “Wow, I think I could be a better manager of my team if I just had some more time to ask the people I work with, you know, how are they doing?

What's up with their kids and their family?”

And that is actually an important part of what it means, I think, to be successful.

So, I think it's just a different way that you offer of reimagining a world of work that can be more meaningful if people figure out how to use AI the right way.

These skills, they're important, but they've historically been talked about as soft skills and almost like put to the side.

Like, “Those don't matter as much.”

We've always kind of known they really matter, quite frankly.

Like, having strong EQ in your job is is a really important thing for for many people. The fact that, you know, so many of these hard skills feel like they have the ability to be automated, that now all of a sudden it's kind of, shining the light on the true importance of some of these soft skills.

If you think about, I mean, you know, If you think about your your day today or my day today. My goodness.

Like the number of the number of times I've had to use, you know, some uniquely human skill around, you know, compassion or, you know, EQ, or conflict mediation I mean, these are- That's what these jobs are.

And to think that those aren't important, I think makes no sense.

But to think that, wow, what will happen in a in a professional world where people are actually much better at these skills and have really honed in their craft on it?

I think that it makes things a lot better.

Most people in some way have jobs where at some point in time you need people to bet on you, to trust you.

And that usually comes with time well spent in investing in those relationships that make the difference.

I also think this connects- You go from jobs to careers.

And you have this phrase that really “a career is not a ladder,” maybe the way we’ve often thought about it, “but a climbing wall.”

Can you say a little bit more about that?

The most requested feature by far that I've seen in my time at LinkedIn is you know, people say, “Hey, Ryan, LinkedIn has all this data.

Can you can you just use that data to show us exactly what career paths are supposed to be or what they look like?

If I want to become a CFO, what am I supposed to do?

Or I want to, you know, be a marketer, where should I go to school now?”

And the truth is, you look at the data and there is no such thing as a linear career path.

You have to realize that you need to take your career into your own hands.

We're moving from, you know, just this idea of roles into specific tasks, and the importance of those tasks.

All of a sudden, you know, this kind of linear thinking of a, of a career or hierarchy inside of a company starts to look a little bit different.

And you need to be thinking about your career less about, “I need to be climbing this ladder, or getting this new title or promotion”, and more about, you know, “What adjacent skills or tasks can I be picking up?

What did I think I couldn't do that now, if I really embrace AI, I can actually do more of that?”

It's a reframing on what, you know, we've historically thought it meant to be in a career, or what a career was made of.

We’re seeing phenomenal, you know, employees at LinkedIn, or Microsoft, or many companies who historically may have thought that their, you know, path to success was, “I'm a great IC and now I'm supposed to become a manager.

Like, that's what I'm supposed to do.”

Yeah.

But now it's like, “Wow.

As an IC, I can, you know, leverage some of these AI tools, get a lot more done, be more fulfilled in my life, and that's what's rewarded now.

That's what seems exciting, my ability to help my company in greater ways.”

These hierarchies are so embedded in the human psyche.

And I don't think these get changed overnight.

But, I am starting to see that trend.

I think it's important to think about, you know, “I'm not just trying to be the next, you know, seniority or level, but I'm trying to expand my skill set.”

That's going to be the path to success moving forward.

As you get to this part of the book, you're basically encouraging people to think about three questions as they think about their their own careers and where they want to go.

The first one is, Why do you work? The why.

Say a little bit about that question and why you make that the first question?

I don't want to discount that the answer to many people to that question is “I need I need to live, I need money to live.”

And I think that that's fair, but, and really important.

But I think it's a great place to start, which is inside of myself.

Like, “Why am I doing this?

What do I care about?

What is going to make me get out of bed every day?

What is motivating me?”

And I think that then helps you make the next decisions and what, you know, you should be trying to do or learn in your career.

But it also connects with then your second question, which I think is even more, perhaps beneficial for people as they're really trying to to think about themselves, which is what do you uniquely do?

How do you think about that question?

If I want to have a fulfilling career, if I want to be able to, you know, leverage those skills and tasks that I know how to do, in a world where, you know, some of these bucket one tasks may become more commoditized, like, “What is it unique about me that helps me stand out in this field?”

What are those, you know, human skills that you uniquely bring?

What are those other skills and tasks that you uniquely know how to do, you know, with or without AI tools?

To paint a picture that's more at a task-based level than on a role-based level.

And again, I think it's just more of this mentality shift from roles to tasks.

And then you go to the third question, “Where do you want to go?”

How do you and Aneesh think about that question and how people best think about it for themselves?

I think the good thing is that if you're able to answer one and two, you know, it starts to give you a pretty good ability to feel like you have agency over what number three looks like.

Again, to so many people, you know, careers and jobs, it feels like a black box, you know, that “Someone else is taking, you know, care of this for me.

I get on some path and it.

And again, I might.

That's how it's supposed to work.” In reality, no, no, you have to take it into your own hands.

You have to take that agency of what you want to become into your own hands by again, going back to “Why am I doing this?”

You know, “What is unique to me?”

And then with those two questions I think you're really able to answer, you know, a variety of ways that you can go with your career that match those two things that will then end up with something that's fulfilling and unique to you.

So many people end up in jobs that, you know, are not what they meant to be.

They're not what they meant to be doing.

They don't enjoy doing that.

And I think if you can really foundationally, end up principally with those first two questions, it will lead to a much more fulfilling career, especially in a time where it feels like, you know, there's so much uncertainty and you don't have control of it.

You do have control of it, but you have to put in the time and the effort, and the work, to really ground yourself in those principles and those questions to know which way to go.

There's also this really terrific, logical flow in your book.

“Understand the impact of the technology.”

The part we've just talked about sort of that comes after that is actually the “Know yourself.

What's uniquely your strength?”

Then it goes to a third part, which is putting it in the context of the world as a whole, where economies are going.

Which I think is helpful as well. And you

entitle the chapter, “Economies Need Innovation From All for All.”

What do you and Aneesh mean by that?

I think if you start with the mindset that, you know, there is a very positive future of the world of work, and you think about what some of these AI tools can go and do and unleash for the world.

There’s some really positive outcomes to all of this.

I have a 20-year-old daughter who, you know, for much of her life has been really focused on, you know, “Dad, how can I make an impact on climate change?

It feels like there's nothing that can be done here.”

Now, the conversations we have are more like, “Oh, you know, these tools are going to be so powerful that some of these really important questions in the world, like climate change, and health care, and poverty, we may be able to find step change breakthroughs in solving some of these problems.” When you look at it through that lens, all of a sudden it becomes so inspiring what can happen.

And then you take the logical steps back to say, “Okay, well, what needs to happen to get there?”

It requires, you know, these strong partnerships between the public sector, the private sector, the infrastructure that needs to exist in the world to allow some of this prosperity to flourish, the skilling that needs to exist, to help people learn what they can do with these tools.

There's so much at the foundational level of work that needs to be done that can't just be done by, you know, individuals or companies, it needs to be done by, you know, kind of, schools and governments and everyone involved.

But when you when you put yourself in that mindset, wow, how exciting can this be?

That almost brings us back to where we began, talking about an outlook on the future.

And this– Should we be optimistic?

Should we be pessimistic?

Should we be excited? Should we be anxious?

The first thing I would note is, even if AI may automate or make it possible to automate many of the tasks in your work, what you do is more than just the sum of the tasks.

We at Microsoft see so much about how great AI tools are automating coding.

The job of a software engineer is not going away, but it is changing.

The data that we have right now on LinkedIn.

We're seeing an increase in the number of software engineer postings that are happening right now.

And it feels like that should be ironic, but it's not necessarily, at all.

Exactly. Exactly when you think about the power that comes through the creation, you know, through software engineering.

Now, that ability that can be in more people's hands is actually really, really exciting.

But to your point, the job is changing.

Take the job of a product manager, where you know, historically what you used to spend a lot of your time on was, you know, number one, talking to customers to understand the problem.

Most important.

Number two, writing a bunch of, you know, specs to hand over to engineers about how the product should look, how the features should come together, how we’re going to measure success, etc., and then help manage the kind of project to be done.

Directionally, that job is still the same today, except that second step is different.

You're still out talking to a lot of customers, but the next thing you're doing is actually you're writing a bunch of evals for the model. It's not an antiquated product- Explain what an eval is for people who are not familiar.

For most people it's, you know, the idea that a customer has this need.

We have to help our product, which is an AI-enabled model-driven product to fulfill that customer need.

So, I need to help teach the AI through what we call evals.

So, a scenario, the product needs to do this, and the AI needs to respond like this.

I need to teach it how to do that in order to fulfill that customer need.

A product manager's job is still talking to a customer.

It's still writing something that looks like a spec.

The spec now is just a set of like, “If this scenario, here's a good or bad response.”

“If this scenario, here's a good or bad response,” and helping to train the model to help the customer do their job, still working in the process.

So, it's not like the job is going away, but it is changing.

And the product managers who are, you know, really succeeding in their careers right now are the ones that are embracing, you know, that AI eval loop and really understanding it, how it works, and in the flow.

So, I think everone’s job is changing.

In fact, it's not a new thing.

If you look over the past eight years alone on LinkedIn, you take the average role.

This is not even an AI-related comment.

The skills required to do that job over the past eight years have changed by 25%.

And we expect that by 2030, they will change by 70%.

So, even if you're not changing your job, your job is changing on you.

And quite frankly, that's always been the case through history.

It may just be accelerated now in the AI age.

The other point that you make in the book is that there's probably more premium and opportunity in the future for cross-disciplinary work.

The ability to combine that, you know, what might be a specialist, but with also, the ability to think across specialties.

Do you see that actually becoming one of the soft skills that's more necessary, or in-demand, or valuable because of AI?

I think a couple things there. You know, first, and we've we've tried this inside of the LinkedIn company over the past year, and it's been really exciting to see.

Historically, we have siloed roles in the software production process.

You know, I talked about one just a second ago of a product manager.

But in that process that you also have a product marketer, a designer, a front-end engineer, to create, you know, part of the LinkedIn product.

What we've learned is that when you enable people to use some of these great AI tools, oftentimes people are able to do many more of those tasks that are required in those siloed roles.

So we tried something recently.

We created a role at LinkedIn, which is called a builder.

And historically, you'd think of it as those four roles.

And now it's just this one role with a great set of AI tools that enable you to build a product from start to finish, leveraging a lot of the insight typically held siloed in those roles.

When roles are siloed, it requires a communication path, and that takes time to do and build.

When you can enable a single builder with the ability to do this, they can do things much more frequently.

For a company like LinkedIn, like the speed and the quality of the decisions to make and get a product out there, are really all that matters.

We try a lot of things and we test it and we pull a lot of things back.

So, enabling this new class of builders to go and build more things and test more things helps our company to thrive.

Quite frankly, doesn't mean anyone's role is going away.

We're making more builders.

And we've created a new program at LinkedIn for associate builders.

People who are just, you know, maybe coming out of college, maybe not even going to college at all, but are proficient in building things and understanding these tools as a new way of entry-level work to come into our company.

Because it's so valuable for what we need right now at LinkedIn.

I think we'll see a lot of roles start to change like that as well.

Again, not something going away, but adapting the way that work is done to help a company succeed.

Well, one of the things I love about that, and even though you say a job is not a title, and as somebody who didn't major in computer science, if I could choose between being a coder and a builder, I think it's pretty cool to be a builder.

Builder sounds great. Yeah.

So let’s conclude with what I think is maybe the, I'll call it the emerging great debate in the tech sector.

I might even argue the emerging great debate for this century as a whole.

What are we trying to do?

Are we trying to use AI to outperform people?

Or are we trying to use AI to help people develop the capacity to do more in work, with their lives, in short, help people perform at a higher level?

I actually think there's a bit of a schism in the tech sector.

If you just look at what people have as their mission, or just their great quest.

There are some who say, “No, we are in search of AGI.”

What is AGI?

Well, there are differing definitions, but they say, “It is the ability, to have some autonomous system that can outperform humans at, say, most economically valuable work.”

Or you have our mission, which is basically to create technology that empowers people to do more, to achieve more, or to be more that they want to be.

Those are two very different visions of what different companies are trying to accomplish.

I still remember when LinkedIn and Microsoft came together, and part of the conversation was Satya Nadella and Jeff Weiner, realizing that the two companies had very similar mission statements.

So, as we look at the future.

You know, you uniquely, you've you've had this experience at LinkedIn, you've been part of Microsoft, you look to the future.

What do you hope we will do with AI for people in the world?

One of the most important reasons that Aneesh and I felt like we needed to write this book right now is to, more than anything, start the discussion and help people to start understanding what's going on.

The reason that I work at LinkedIn, and the reason that I work at Microsoft is because of the missions of these companies.

Like, LinkedIn is a platform for 1.3 billion professionals around the world to find economic opportunity.

It has been that way for 20 years.

And, you know, through different economic changes through Covid, we've been there as a platform to help people navigate their careers through their community, through how they learn new skills, through how they, you know, adapt as human beings. And

I think now more than ever, people need to be understanding and having these discussions again.

And it's not just unfortunately, up to, you know, some tech companies or you and I, but it's governments, it's economies, it's educational institutions to really paint a positive future for what this can all mean.

AI is an enabler for us to do bigger and better things as a society.

We have to be thoughtful about the approach and how we get there.

Everyone has to have a framework so they, you know, can deal with the uncertainty in the messy middle we're going through, to how to navigate it right now.

But my goodness, if we are able and when we're able, to navigate through it, to give humans these superpowers, to enable and to do more than they ever thought possible, I think we're going to end up in a pretty special place.

I know you share the same thought as well, and that's why you're here.

Every book is an argument.

Every book starts a conversation.

I think the book that you and Aneesh have written really is about two conversations.

One is how can an individual or a parent coaching a kid, or somebody who's 20 years into their career and looks ahead to another 20, get some practical advice and think in some new and helpful ways?

In this changing time, how can individuals use AI to be more successful in so many ways?

But there's a second argument you're making as well, that there is a path.

If we put our minds to it, we will decide the future as people.

Machines won't decide it, people will.

There is a path, where as a society, we can use AI to fashion a broader and better future for lots of people.

And it's not about being replaced by machines, it's by using this to achieve things that we couldn't otherwise contemplate.

I think you and Aneesh together have written a book that creates the basis for these conversations.

I think it's the conversations that people want to have.

But more than that, I think it's the conversations that we need to have.

And I'll say it helps reinforce what all of us who work here at Microsoft and LinkedIn.

This is why we joined these companies in the first place.

It’s why we’re still here today.

because we actually want to see technology do good for people.

And I think you show us how.

So thank you very much.

Thanks, Brad. Appreciate it.