1143: How to Build a Career that AI Can’t Replace with Aneesh Raman

Pete Mockaitis
Aneesh, welcome!

Aneesh Raman
Thanks for having me.

Pete Mockaitis
Well, I’m excited to hear your insights about AI and economic opportunity. Could you maybe kick us off by sharing what’s the most surprising or counterintuitive thing you’ve discovered about us career professional folks and AI?

Aneesh Raman
Ooh, it’s a big one. It’s an existential one that we have internalized this diminished sense of self as humans at work across the industrial age. When AI broke out, what now three, four years ago, immediately, there was this great fear.

Immediately, the conversation was, “We’re done. We’re at the end of the road for humans at work. We’ve got this thing that can beat us at these things. It’s going to beat us at those things next. It’s going to beat us at everything soon.”

And I just sort of, like, intrinsically, didn’t believe that. I was starting from a place where, for a long time, I had thought the labor market did a horrible job matching talent and opportunity, indexed on pedigree signals like your college degree, “Where did you work?”

So I just knew there was so much human potential out there that had been blocked out or locked out of economic opportunity all over the world. And so I just didn’t believe that humans were done. I kind of felt like we hadn’t even begun yet.

And the more I sort of thought about it, the more our CEO and I talked about it, what led to the book was this realization that humans are more than we’ve been at work for a couple hundred years now. For a couple hundred years, we have been about one thing above all else – efficiency.

And we sort of told ourselves a story that the knowledge economy moved us out of the industrial age, of people working on factory floors on assembly lines. But it didn’t. Even if you were with a laptop in an office, you were doing more, better, faster, more, better, faster, more, better, faster. Everything was about efficiency and productivity.

And we had derided almost these skills that make us, us. We called them soft skills. We said they were nice to have, not must have. And all the math worked in terms of the industrial age and what the economy valued in terms of technical and analytic abilities.

But I think what’s been most surprising to me is that AI is forcing us to reassert ourselves because it is going to out-machine us, it’s going to out-efficiency us. And yet, our human brain, which is I think still the most incredible object in the known universe, it’s been around for tens of thousands of years, long before the steam engine arrived, and the industrial age descended upon us.

And so we’re going to pull from these strengths that we’ve had for millennia, that we talked about in the book, and it’s going to be a moment to reassert ourselves and our capability, I think.

Pete Mockaitis
Oh, wow! These are big ideas.

Aneesh Raman
Welcome to my brain.

Pete Mockaitis
“Internalize the diminished sense of self.” My goodness. You know, it’s funny, I was just chatting with Claude last night because I think the First Lady was with a robot doing an education event. And I was like, “Oh, can that robot finally load my dishwasher for me? And when can I buy one?”

And so, I was looking at that, and it said, “Oh, this robot is impressive because it could figure out how to fold a towel with just 80 hours of video.” I was like, “Oh, well, my five-year-old figured out how to fold a towel in about four minutes of instruction with a hug.”

So, yeah, I’m with you, our brains are spectacular. But, yeah, there are some domains in which we are being out-efficienced by the AI.

Aneesh Raman
Yeah, and I think that’s okay. It’s not okay right now because it’s causing a massive disruption to work. It’s changing the rules of the game, which are hard to manage if you’ve been playing the game the old way and you’ve done everything right and, suddenly, you know, old math won’t solve new equations. But I think it’s an opening for people that see it.

We were never meant to be machine-like. We were never meant to spend our days doing the work of efficiency and more better faster, more better faster, more better faster. I mean, at one point, as we were reporting in the book, you know, thinking about those people on assembly lines who are fastening that one widget over and over again, or the knocker uppers that we talk about, the people who their job was to shoot peas at windows to wake people up as this sort of human alarm clock.

I looked up and they were just at this coffee shop, four people sitting next to each other, on their laptops, just slamming through emails. And it just connected for me that this is all still ever been efficiency work. And so, I think the real opportunity we talk about in the book is to see this as a big change to everything, to be understanding of the fear that that’s going to cause, because the human brain is wired to fear change. It is not wired to get exponential change. We are in a moment of exponential change.

But then act despite that fear, push past it, because while it’s understandable, it’s also unhelpful. And if you start using these tools and using them not in ways that then just take all the work out of your day, but start to take away the stuff that’s mundane, routinized, efficiency work, free up time to do more cool things with these tools, to learn new things in new ways, to build new things in new ways.

And then to open up space to do the things we uniquely do, to give yourself time to think critically, to think about ethical implications of what you’re building if you’re an engineer, to spend time brainstorming or partnering with other humans.

The turning test started us down this path of AI versus human, and then it beat us here, it beats us there. But that’s not where the story goes. There’s no innovation. There’s no growth if it’s just all about AI. Humans are illogical. We’re unpredictable. What works for us requires someone to be us, to be human, to in-tune that.

So, really, the test we should be doing is human versus human with AI, versus humans with AI, because we always do the coolest stuff together. And that means think about yourself five years ago, think about yourself today, “What are you doing that’s new and better and energizing that you couldn’t do without these tools five years ago?”

And in the book, we talk about an easy way to start this. Put your job title aside. It doesn’t matter if you’re a CEO. It doesn’t matter if you’re a senior director. It doesn’t matter if you’re the newest hire at a company. Your job title is irrelevant for the purposes of this exercise.

Every week, you do about a dozen tasks, list them down, and then you’re going to put those tasks into three buckets. The first bucket are tasks that AI can now do or can soon do. So coding is in there, quick summary, quick analysis, first draft of content, meeting notes, like all that stuff’s in bucket one.

Bucket two is stuff you’re doing with AI that’s new. It’s not just additional stuff that you’re putting in bucket one. It’s, “Are you learning something new with AI?” “I’m on marketing, I got to talk to the sales team. They speak a different language. How do I close that expertise gap in what I’m trying to pitch them?”

Are you building something new? “I have to present. What’s a cool image I could associate with this idea? A video? How do I make this land in a more visceral way to the people I’m trying to convince to back this project?” So that’s bucket two.

And then bucket three is, with the time you’re saving in bucket one, with the cool new stuff you’re doing in bucket two, what are gyou doing that’s uniquely you? And that starts with what’s uniquely you as a human, your ability. We have the five Cs in the book, but with those, think critically, “What’s an ethical implication of what we’re doing?”

But then are you spending new time with people to try new things, to test something out as a partnership, to get advice on how to pitch something. And as you sort of move the tasks of your job away from bucket one towards bucket two and bucket three, you’re adapting your job. You’re redefining your job.

We have a statistic at LinkedIn, 70% of the skills for the average job will have changed by 2030. Now, the old way that disruptions hit meant that, at some point, in six months or a year, your boss, your boss’s boss would come to you and say, “Here’s how your job has changed by 70%.” Because old disruptions from the steam engine to electricity to the internet, they played out over years and they came top down.

This one is different. Your boss actually doesn’t really know how your job is supposed to change. Their boss doesn’t know how their job is supposed to change. CEOs are trying to figure this out at an organizational level. So we get to change our jobs now. We get to start figuring out where these tools come in and then what that opens up in bucket two and three, not just because we’re human, but because we’re us.

We have a chapter in the book, “No One Beats You at Being You.” That’s where it’s going, is that you’re going to shift your job and then re-center your career around your unique curiosities and capabilities.

Pete Mockaitis
No one beats you at being you. And it’s funny, I’m thinking about, you know, so me here now, here we are having a podcast about professional skills development, and there are a lot of places where you can get such things.

And it’s interesting how, if I talk to an AI about such a matter, I might get the answer, and it might be quick. And yet, it is not as satisfying, complete, thorough, giving rise to new ideas and connections, the way hearing a full blown conversation between two folks on a matter is. And I think that that really resonates.

Aneesh Raman
And I think that it’s really important. Yeah, I’m glad you’re saying, because right now there’s this sort of idea to AI or not AI, as if it’s binary. And if you AI, you’re doing everything AI. If you’re not, you’re rejecting it for righteous reasons, and that’s where you’re at.

And in the book, we have the story of Neil Pretty, whom really, he embodies this idea that you need to use AI, but you cannot misuse it, nor should you overuse it. And Neil starts using this tool to help him prepare for different presentations, and he overuses it and realize it doesn’t sound like him and it’s not going to distinguish him. And he dials it back and he uses it differently.

Instead of asking it to tell him what to say, it says, “What would this CEO say about what I said, or this academic? Give me 12 reactions to what I think.” And then he would use that to even get better at what he was going to say that would have taken much conversation with many people ahead of a meeting.

So you can overuse AI. And MIT has done cognitive scans and come up with this term cognitive debt. Like, if you’re sitting at work and your boss asks you something, you copy and paste it in the tool, then you copy and paste the answer back and send it to your boss, you might be doing efficiency work more efficiently.

But if you run into your boss a week later, and they’re like, “Hey, that was a great idea. How did you think of that?” you might not even remember that exchange because your brain is not tracking it, and you will have brought no critical thinking to it. So that muscle is atrophying. So you got to make sure that you are using this tool to do better things yourself. You cannot outsource to it.

Pete Mockaitis
So in the universe of more, better, faster efficiency work, how would you suggest is the contrast? If I’m thinking efficiency work AI stuff is in the land of more, better, faster, what is the land of our humanity?

Aneesh Raman
This is the first time someone’s asked me that. Because what’s crazy is we had to define what makes us us. We had to define what makes humans unique in the arena of work.

It turns out not much work had been done around that. As you started talking to neuroscientists, behavioral psychologists, behavioral economists even, when I’d ask like, “Who from companies or from the world of work comes and talks to you?”

One neuroscientist said, “Not many. Like, athletes will come because they want to push their brain to the limit. The military will come because they can’t hire from another military. Hedge funds will come because they want a cool like summit speaker. But you were not getting incoming from everyday practitioners of work.”

But now the mind is going to the center of work, not the machine. And so what does it all lead to? You know, in the book, we identify the five Cs that we think are at the core of human capability – curiosity, compassion, creativity, courage and communication. Those are what we offer up at the intersection of our IQ and EQ of our consciousness and conscience.

Then we say there’s some habits we all need – resilience, adaptability, handling hard well, failing fast, learning quick. And we sort of bundle it all into this idea of being entrepreneurial in our habits and in our thinking. And we know that in saying that, we lose a lot of folks who think being entrepreneurial means starting a business, and that is not for them.

Paul Cheek from MIT, who’s a professor on entrepreneurship there, has an amazing definition for it. “Entrepreneurialism,” he says in the book, “is doing more than is reasonable with the resources you have.” So every one of us every day has a task, has a project, has something we’re doing at work, what’s more than is reasonable that we could do with these tools and with others with the resources we have?

And then what that leads to is a flip. Instead of more, better, faster, I think we’re doing new, bigger, bolder. We are creating a whole bunch of new ideas, a whole bunch of new ways for businesses to grow, a whole bunch of new businesses to go after, a whole bunch of new areas from climate to healthcare to all sorts of stuff that we could create technology for businesses to address, at the local level for just a community, or at the country level, or at the global level.

So, to me, “more, better, faster” becomes “new, bolder, better” and not just in terms of work. Like, I think if we do this right, and it isn’t just us as individuals. Institutions need to completely redesign the systems of work from employment to education, entrepreneurship.

But, ultimately, we get to better work for each of us, better work for all of us, better defined by just more human work, more fulfilling, more high value, more impactful. But that all leads to greater prosperity and progress because of this sort of innovation explosion, this entrepreneurialism that can take root.

Pete Mockaitis
And to these notions of efficiency work versus newer, bolder stuff, I’d love your hot take on these AI layoffs. I mean, some say, “Oh, well, that’s just AI washing. They over-hired, interest rates are worse. It makes a better story for Wall Street to say, ‘Oh, it’s because of AI efficiency.’” But others say, “Oh, no, no, no. Sure enough, one person can now do what things that previously require two, three, or four, and thus it makes sense to shed those jobs.” You’ve got an interesting vantage point. What’s your take on this?

Aneesh Raman
I mean, we’re seeing jobs get added, one million plus jobs around AI. That’s not just the sort of like hardcore engineering jobs. That’s also the data centers. We know sectors are hiring, like healthcare. Look, there’s these two truths we have to hold at once that are somewhat inconsistent.

The first truth is we know at the other end of all of these moments of disruption from technology, we generally see an increase in employment, and the Fed is out there sort of repeatedly with that. Jobs change, new jobs emerge. MIT has a stat, 60% of employment in 2018 didn’t exist in 1940. Creator wasn’t a career 10 years ago. Data scientist wasn’t a job 20 years ago. So we, generally, do see employment go up.

That happens after a messy middle where a lot of lives get upended and it’s really hard for people. But we do see employment go up. That sort of thing one, truth one. Thing two, truth two that contradicts that is we’ve never been here before in terms of this technology. It is fundamentally different in terms of what it’s able to do.

And I think predictions are unhelpful right now. Anyone with absolute certainty about what’s happening to a job category or to all jobs or to jobs in this sector, let’s see how it turns out in five or 10 years. Like, I think it’s just impossible for anyone to know with certainty anything absolute.

The one thing we do know, to contradict myself a little, is the only thing that matters right now is what we believe, and what we choose to do, and what decisions we make, and what steps we take. And that is true for us as individuals. It’s true for us as organizations. It’s true for us as societies. It’s true for us as humanity.

If we decide that worse is more likely, and we make decisions that make worse more likely, worse is more likely. If we decide that better is more likely, and we make decisions that make better more likely, better is more likely.

So in terms of where employment goes, there’s so much in the air. I mean, we’re going from an old world to a new world of work. There’s so much macroeconomic muckup that’s going on on interest rates and geopolitics. Every company is going through its own moment of business transformation.

Some over-hired and now they’re managing that. Some are built with an org chart for stability, order, predictability. That isn’t going to help you innovate, be agile, and grow. They’ve got to manage that. There’s no one truth to everything that’s happening.

And so I think for folks who are looking for a single answer, who are looking for someone to tell them what to do, who are looking for an off-the-shelf playbook as an individual or as a company, like, that’s not this moment. It’s not like back when it was like everyone get a CS degree or bootcamp certificate in coding if you can find one, because that’s the ticket.

There is no “it” right now, but that’s it. We’ve all got to start to figure this out on our own, use these tools, and with these tools start to understand our own unique interest, capabilities, where those could go, where we would pitch ourselves across a broader set of job opportunities that we might, otherwise, have looked at. And I think that’s what we’ve got to do is look. It’s a metacognition sort of moment.

Pete Mockaitis
Understood. But you do have some interesting data. 85% of people are in jobs where AI can automate at least a quarter of routine tasks. Can you tell us a little bit about that data and what sorts of things we’re seeing automated now with AI?

Aneesh Raman
A big thing we’ve been trying to push people on is to look at jobs as a set of tasks, not as titles. A good example of how not to do it, I would say, is looking at software engineers. And for a bit coming out of the gate with AI, everyone said that title describes all software engineers in one way, and that one way is that they code. And as AI got better and better at coding, it became, in that line of argument, intuitive that software engineers were done.

We’ve actually seen recent data where the hiring for software engineers is going up because as AI is able to do more coding, more companies want to build tech, so they’re hiring. And the job of software engineer was never limited only ever to coding.

Some of those jobs, entry level jobs, even middle, they were, but the job doesn’t have to be just that. In fact, as AI is able to do coding, it shifts to reviewing the code, or talking to customers, or having those conversations about ethical implications of what’s being built. It’s the same three buckets and things move.

ATMs are a good example, we talk about in the book. When ATMs hit in the late ‘70s, everyone thought bank tellers were done. We have a quote from the New York Times. It basically says bank tellers are done. Bank teller jobs, like, doubled between that moment and 2010, and they doubled because you had more banks opening so you needed more tellers because ATMs allowed it. The job of the bank teller shifted to being more about relationship banking.

Now, there were some debate over whether the quality of the job went up, but in an absolute term, you know, the jobs went up. They came down after that because of the iPhone and the smartphone and all the banking we’re now doing. But you couldn’t have predicted that in the ‘70s.

So that’s all to say our data doesn’t look at job titles. It looks at jobs. It looks at the tasks people are doing. And it says, if you are in a job where a lot of your job is that bucket one, that’s worth knowing. That doesn’t mean that entire job is going away. And it doesn’t mean you are done at work. It means you’ve got AI coming for well over 50% of the jobs in that task. So you want to start on your own moving tasks in your day to day to bucket two and bucket three.

And if you do that, don’t worry about the job category or the job title you have. That’s all secondary now. It used to be job title mattered first because you’d reverse engineer from it. Job title matters last now because we’re going to be reshifting work.

And so depending on your number, and you don’t need us to tell you this data, you can do an evaluation of the tasks in your job and look at where you’re heavy. Anyone who is heavy in bucket one, okay, what do you got going in bucket two and three? How can you build out from that?

If you’re in a job category that feels really volatile, okay, what are the transferable skills you have across two and three that could take you into other job functions or job categories? But it’s not an overnight, everything is done end of day sort of thing. It’s a step-by-step incremental of, “How do I manage this change sort of thing?”

Pete Mockaitis
And we had a really good chat with Jeremy Utley, who suggested shifting perspective from AI is not the oracle with the answers, but rather like a collaborator, a teammate, and that’s been pretty helpful. I’d be curious to hear, for those whose AI use is limited to sort of an enhanced Google or enhanced Bing, where do you think are the most promising opportunities, like, “Hey, go do this right now with AI, and you’re going to see some cool career benefits”?

Aneesh Raman
This is another one where there’s no one answer for everyone. I’m sorry to tell folks. Like, you’re going to have to go to the gym. You’re going to have to try things out, test things out, and figure out what is the high value of AI for you.

It could be learning new things. It could be building new things. It could be coaching you on new things. You got to keep trying the tools. Like, to your point, I think too many folks either are afraid of AI and don’t want to touch it. Or, if they’re using it, they’re using it just for a better search.

We have five Cs I talked about, and curiosity matters most right now as individuals. And the first place to start is be super curious about these tools, because their capabilities are changing every day. It’s almost like a skill of tool dexterity.

I use multiple tools every day. Every once in a while, I shift to the dominant tool. I use them for all sorts of things. Every week, I’m trying to push a new task out to the tools so that I’m constantly testing what new things that I’m working on can it help with.

It helped with writing at first, and then that pushed me to realize, “Okay, I got to focus on how I elevate what I can get help with on the research or first draft side. But also how do I spend more time doing in-person communication?”

So I started studying, like, theater actors who have it down, who know how to command a room, command energy. What can I learn from them now that my bucket three is going to be more of this? Right now, I’m using the tools for a lot of coaching. I want to send this email. I’ve told the tools what I’m working on, which is sending less emails that are less lengthy with less ideas to people like Ryan, who I can bombard with ideas.

And so it’ll say like, “Hey, you just got yesterday, like take a day off,” you know, like stuff like that. So it’s not so much about the tool capability. It’s what is the human capability you’re working on in that moment? Because we’re all going to want to keep growing right now in new ways, which is fun. It’s hard, but it’s fun.

And then you’re going to use the tools differently based on what you’re working on. If you’re just doing search, that’s an issue. So the easiest way to do it is find the hardest part of your tomorrow. You got something at work tomorrow that you’re not looking forward to, that is either monotonous and drudgery or complicated and a hard conversation you got to have, or you’re suddenly going to have to come up with an idea and you’re bit freaked out about that.

Whatever is your hardest thing tomorrow, start going to the tools and asking them how they can help you with that. And they might not be able to help you. Okay, that’s like a good example of a tool that isn’t there yet, or a task that isn’t there yet, but they’ll give you something. And that’s the sort of rhythm you want to get in.

Pete Mockaitis
Okay. Well, could you give us some fun examples of folks who saw some really great tactical good things flowing from tools into what they’re up to tomorrow?

Aneesh Raman
My favorite from the book, probably, I mean, they’re all stories of individuals who are using these tools to get jobs, keep jobs, and change their career, build businesses, like, all of it. But Jonetta Gresham is in her 50s, and because of her age, she came to AI with, in her words, a “Hell, no to AI,” mindset, because she had seen Terminator and Terminator 2 and Terminator 3, and really felt like this was a robot apocalypse come to life.

Again, she had a task at one point, which was to get her resume ready. And she used a tool to just help her do that. And she was blown away at how the tool helped her articulate skills that she had and better organized experience that she had in a way that made her so much more employable for the job she was going after.

And so that sort of opened up her eyes to like, “Okay, maybe this can help me.” And a little bit later, she was taking an IT certification course. And she is someone who, in various moments of education, didn’t feel like she was being taught in the way that she would like to learn, in the way that her brain process information, and in the way that would feed her curiosity.

So she told the tools to help her learn all the stuff she had to learn in the ways that she likes to learn, with stories, with analogies. The tools did that, she passed the test, she got the certification.

It can personalize against your needs in a way that no technology has before. It can close learning gaps. It can close entrepreneurial gaps or building gaps. You just got to get in the rhythm with it.

Pete Mockaitis
Yeah, I like that a lot in terms of, if you’ve got a laser focus on, “This is the thing I need to go learn,” and then how can the tool facilitate that, I found that rather handy. Like, I found myself getting in the Mac OS Terminal bash command line, and I don’t know what I’m doing, but it’s like, “Hey, if you want to, you know, do this automatic downloading of stuff, you’re going to need this tool.”

So I was like, “Go to GitHub,” it’s like, “Okay, no, you’ve already lost me.” And so I say, “Explain it like I’m five.” And it’s really funny, it’s like asking the robot to go to a store. It literally explains it like I’m five. But that was very handy. And I’ve heard that theme from a number of people.

It’s, like, they know a little something about the domain that they’re after or looking to enter for perhaps the first time, but not nearly enough to actually achieve anything. But with this sort of mega-crutch, they’re saying, “Oh, okay, I can kind of fake my way through step by step.” And then afterwards, like, “Oh, hey, I guess I know how to do this now. How about that?”

Aneesh Raman
Yeah, we’ve got a great story of a guy named Diego, who’s in Texas and is trying to push for rural entrepreneurship with AI to really inspire more folks to realize they can build businesses. Often, folks who couldn’t afford to go to college for whom entrepreneurship is, as he calls it, this permissionless path, this ability to go build your career on your terms.

And he has a great line, which is, “We are no longer limited by what we know. We are only limited by what we can think to ask.” And just imagine what that means for all people all over the world who have access to these tools, who hopefully have electricity and AI infrastructure.

But you’re only limited by what you can think to ask. All of us as humans are innately curious about things, wildly different things. That’s what’s amazing. We all have different perspectives, different things that drive us. But imagine now having this tool that can sort of feed that curiosity and help us align it with the work we do and the impact we want to have and the purpose we want to bring to our jobs.

That’s where you start to get excited. I think we are collectively doing a horrible job telling that story and making it clear, that hiding in plain sight is this thing that is going to make all of our jobs more interesting and more fulfilling, and all of our efforts lead to greater impact for good in the world.

And that’s now on us to try and reset that story and that conversation, which is like the big reason we did the book.

Pete Mockaitis
I like that, “What you can think to ask.” Have there been some power questions that you found transformational?

Aneesh Raman
I think a lot of it is, right now, for folks around, “Where do I start?” or, “What do I do about? How do I think about AI? How should I use AI? When should I not use AI?” You can just dump that in as a voice memo into one of these tools, and it gives you a start. It gives you something to react to.

Again, it doesn’t give you the answer. It gives you an option. And it’s your job to push back on it or to pull from it, and then try and learn something here. Ask it to challenge your thinking over there. One of the things we talk about in the book is like the, I think, it’s a hundred to one rule.

I mean, “You pick your number, but give me like 80 versions of something,” and then you react to which of those you like. And then you can start to think about why and build from that. Or, “Give me the five best arguments against the thing that I think is true about what I’m going to do tomorrow.”

That’s where I think people are really starting to get good results from it. Not, “Give me the answer,” but, “Give me a way to get to a better answer.”

Pete Mockaitis
And I like what you’re saying with regard to the challenging is because it seems like that’s the default setting is sycophancy in these AI tools. It shows me a study. I was like, “Wow, that’s very compelling.” I was like, “Do we think this is real?” It was like, “Actually it has all the hallmarks of being a fraudulent paper mill submission.” I was like, “It’d be nice if you proactively shared that.” But, yeah, to ask it to do the challenging is great.

And you said voice memo and I think that’s a brilliant hack right there in terms of not just the one sentence, but the five minutes of verbiage can make all the difference.

Aneesh Raman
And you can just dump it all in and it’ll organize it. I know someone who does a call with AI every day. They do the chat functionality because you can also, without having to type in or do a voice memo, you can literally converse with these tools.

And they go out for a walk, and they just talk about everything on their mind, “I’m like thinking about this, I had a hard conversation with this person.” And over time, what these tools start to have is longitudinal data on us. They aren’t another person. They are just a collection of insights and knowledge that’s out there. And then, increasingly, if you give it context and give it info, insights, and thoughts on us over longer and longer periods of time.

And so in these conversations, the tool will start calling out, “Hey, you’ve talked for a few times now about wanting to learn more about neuroscience, or how that’s going to relate to work. Here are some, like, podcasts you might want to listen to.” Or, “I’ve noticed, like, anytime you have to have a conversation that’s tough, and it is how you end your day, it really upends your day. Like, have you thought about making those conversations happen at the start of a day?”

It starts picking up on stuff for us that we might miss in the day-to-day of just life being busy. So the key thing is, like, this is a tool that is the easiest technology humans have created for humans to use. It is literally like just talking to someone else at the most basic level. You don’t have to go learn AI. You just have to, like, sign up for a free tool or watch a couple of free videos on it, and then just start using it.

Pick a thing. It can be an exercise plan, a meal plan, or something at work, a project, or a set of tasks you’ve got going, and just start using it. Like, it’s sitting there for any of us to use. So you got to just start using it and keep using it but don’t outsource to it. Use it to then start building you into a better person.

Pete Mockaitis
All right. Well, anything else you want to make sure to mention before we hear about some of your favorite things?

Aneesh Raman
I think it goes back to your opening question. Like, it has been surprising how we have internalized a diminished sense of self, and yet it is a reality. And so the biggest thing I would tell people is, like, what matters most right now is your belief in yourself.

You’re going to have to bet on yourself. That’s the future of work and then push your leaders, and we’re pushing them, to build systems that make that bet pay off. But the thing that starts it all is going to be that you believe in yourself and you’re going to bet on yourself. And that’s going to take some work because we are all coming out of an era for work that wasn’t about betting on yourself.

It was turning yourself into whatever the job description needed, whatever the job category needed. So it’s going to be a flip for your brain. The good news is, and there’s a great book, Tiny Experiments, a bunch of them on neuroplasticity and how we can rewire our brain to become a different person.

The good news is you got a human brain and it is able to be rewired and you can become a different person. You can get to belief. You can get to a place where you know exactly how and why you’re going to bet on yourself, but it’s going to take some work. But that’s where it starts. That’s what I would say.

Pete Mockaitis
All right. Well, now could you share a favorite quote, something you find inspiring?

Aneesh Raman
I like the, “Some men see things as they are and ask why. I dream of things that never were, and ask why not.” That drove me for a while. I think, right now, it’s more “Be curious, not judgmental.” I think it gets appropriated to Walt Whitman.

Pete Mockaitis
All right. And a favorite study or experimental or bit of research?

Aneesh Raman
Mine, I mentioned at the MIT one, 60% of jobs in 2018 didn’t exist in 1940. That’s just like a good number for us to keep in mind.

Pete Mockaitis
And a favorite book?

Aneesh Raman
A bunch of them. My favorite hits at a certain moment in life, that sort of like hits me deep as it relates to this conversation, Sapiens. I read that in August 2023, GPT had gone global the prior year, and it is a brief history of humankind.

And so it just helps you have a sense of, like, how incredible the human brain is, but just also how much has happened across millions of years when we all focused on a few hundred years. So that really widened my perspective.

Pete Mockaitis
And a favorite tool?

Aneesh Raman
Copilot, I’m using it a lot because I work at LinkedIn. My co-author is working on Copilot. So it’s kind of a default because I can go tell someone if there’s something we should make better out of it. But it can really give me good advice on, “Should I send this email?” or, “What am I overspending my time on?” because it’s got my calendar, it’s got my email, it’s got the team’s messages. So, for me, right now, because a lot of my growth is growth I want to do at work, it’s been helpful.

Pete Mockaitis
And a favorite habit?

Aneesh Raman
This is probably controversial, because I don’t know if people would say this. My favorite habit is small talk, actually. I love small talk. I think every human is like a documentary unto themselves. There’s this great word, sonder, that I won’t do it justice, so people should look it up. It’s a word someone made up, I think, five, 10 years ago. But it’s that every human around you is living a life as complex and interesting as your own.

And that’s true across human history, or at least since we’ve had the brain we have with the ability for complex thought that we have. So I find small talk just amazing. I love meeting new people and just, I’m sure I’m awkward about it because I ask like deep questions sometimes really quick, but I just, like, love learning about people.

Pete Mockaitis
And is there a key nugget you share that people really connect and resonate with and quote back to you a lot?

Aneesh Raman
Hard things are hard. That’s a good one. You know, at one point, someone asked me, “What’s been the hardest part of your career?” And I was like, “You know what? All of it.” And I did it kind of, like, begrudgingly. And then as stuff has stayed hard in just figuring this story out, I revisited, you know, when I worked for President Obama, he had a “Hard things are hard” plaque on his desk because at certain moments when legislative victories were hard fought, people would remind each other hard things are hard.

And that just has led me to become a real believer in the bigness and value of hard. I have, like, an ode to hard things. It’s got, you know, quote from a stoic Marcus Aurelius, who’s like, “The obstacle is the way,” to “Hard things are hard,” to Carl Lassen, the Duke women’s basketball coach who has a viral video that’s amazing about how the whole thing in life is, “How do you handle hard well?”

Roger Federer had a commencement speech a few years ago about the mastery of hard things. Nvidia CEO Jensen was at Stanford Business School and said, “I wish upon you pain and suffering,” because his point to these Stanford Business students was, “You got to build resilience and you got to go through hard for that.” So, yeah, hard things are hard. I think I’ll take that.

Pete Mockaitis
And if folks want to learn more or get in touch, where would you point them?

Aneesh Raman
LinkedIn. The sleeper functions on Linkedin, I think, that people don’t know enough about is you can follow people without connecting to them.

You can go follow folks and they’ll be in your feed. So I am, I’d say, regularly, every three months, unfollowing some people where my curiosities have moved somewhere else, following new people who are talking about the things that I’m newly curious about.

So follow me until you get bored of me. Follow others. All the people in the book are on LinkedIn. And then the book, Linkedin.com/opentowork, that’s where you can go find out about the book.

Pete Mockaitis
All right. And do have a final challenge or call to action for folks looking to be awesome at their jobs?

Aneesh Raman
Bet on yourself. Find your way to betting on yourself and you’ll be okay.

Pete Mockaitis
All right. Aneesh, thank you.

Aneesh Raman
Thanks for having me.