Podcasts

Pete Mockaitis
Paul, welcome!

Paul Leonardi
Hi, thanks for having me, Pete. I appreciate it.

Pete Mockaitis
Well, I’m excited to be chatting. We’re talking Digital Exhaustion. But first I want to know, I understand you are the youngest blackbelt in U.S. Aikido history. Tell us about that.

Paul Leonardi
Well, I was, at least circa 1992, or somewhere around there.

Pete Mockaitis
I assume 12-year-old or someone just have to usurp you. The nerve.

Paul Leonardi
Yeah, well, they might have in the last couple of decades. Yeah, I started practicing Aikido when I was in second grade, and I didn’t like it when I started because I just wanted to be like Bruce Lee or the Karate Kid and punch and kick stuff. And my parents didn’t like that idea very much, and said, “We’ll put you in a defensive martial art,” and I didn’t really understand what that meant.

But Aikido is about using your opponent’s energy and reorienting it so that you can throw and pin and do things like that. And I think it’s actually turned out to be a pretty good metaphor in my life. Like, how do you take energy that’s moving in one direction and recast it so that you can move in other directions and do productive things?

And so, I’ve really enjoyed, you know, I don’t practice regularly anymore. But it’s certainly an important part of my identity. And what was kind of interesting is I did it with a bunch of kids, and several of those kids ended up going on to graduate school and getting PhDs. We didn’t come from like an affluent or highly educated area.

But I think there’s something about the discipline of doing a martial art, combined with, and Aikido is very much like this, where you have to do improvisations all the time on key techniques to deal with opponents that are doing different things. And that kind of focus of technique plus improvisation is something that lends itself really well to doing research and focusing on topics, you know, sort of ad nauseum for a really long period of time.

Pete Mockaitis
Well, I’m glad you mentioned directing energy because that’s exactly where I thought this might go. This is we’re talking about digital exhaustion. Well, first, can you define what do mean by this?

Paul Leonardi
It’s a hard thing to define in words, but let me try to define it in actions, behaviors. So, here’s the story I get from a lot of people. “I get midway through my day. I’m staring at my screen. I realize I’m just scrolling. I’m clicking on some random stuff. I know that there’s an email that I should respond to, but I just don’t want to do it. My eyes are sore, but I can’t look away from the screen. And I just feel this sense of bleh, even though I still like my job and I like the work I’m doing.”

I think that really characterizes the feeling of digital exhaustion. It’s that we are so enmeshed in this world of communication and tools and data coming at us. And we need it, and it’s useful, but it’s also just wearing us out.

Pete Mockaitis
Well, could you share with us, I think many of us can relate to that, like, “Oh, yeah, sure. Okay, mm-hmm, understood.” I’m wondering if you discover anything really shocking as you dug in your research here.

Paul Leonardi
One of the things that I expected to hear from people was, “I’m going to…like, I want to give up my tools. I want to go on a digital detox. I want to stop using…” name your social media platform. And rarely anybody said that to me. Most people said, “I want to be able to do all the things, but I need to figure out how do I do it better? How do I do it in a way that feels like I’m in control and isn’t sapping all of my energy?”

And I thought that was interesting because most of the discourse that we have today seems to be you have this sort of either/or choice. You’re on social media or you decide not to be on social media. You get a dumb phone or you get a smartphone. You stay away from your tools, right, whatever it might be. And we just don’t live in a world where you can choose to walk away from most of our technology. And most people don’t want to because our tools do great things.

If it weren’t for the internet and video conferencing and USB mics, we wouldn’t be having this conversation right now. So, we like our tools, we want to use them, but we need to reorient to them in ways that are making sure that they’re energizing us, allowing us to be productive, being engaged and not sapping us of all our enthusiasm and excitement.

Pete Mockaitis
Well, I wonder, are they? I mean, I think some of us feel it, like, “Yes, my phone is a problem.” And I wonder if others among us are not even aware of damage being done. Can you orient us to the lay of the land with the research here?

Paul Leonardi
I started questioning people about feelings of digital exhaustion in, roughly, 2001, 2002. And I did that because I had a few experiences when I was doing some research at this large atmospheric weather science organization.

And the scientists and the admin people there kept telling me about how they love doing research about atmospheric conditions, and they loved working with these fancy computer models. And they thought they were really making a difference by giving reports to the FAA to help with plane routings and things like that.

But that they just start were feeling like there was so much data coming at them and so many different tools that they had to learn, that they were kind of feeling overwhelmed. And almost everybody that I talked to said that. And when I asked them, “Okay, well, do you feel like you are exhausted by your tools?” roughly half of them said immediately, “Yes!”

And the other half said, “What do you mean exhausted by my tools? I mean, I kind of feel like worn out by them, you know, but exhausted? I don’t know. I just use them.” So, I’ve been asking that question ever since. And I’ve asked it thousands of times. And I’ve got over 12,000 people that I’ve interviewed and surveyed for the book.

And what’s happened over time is that, each year, it seems, that I asked that question, more and more people from that 50% that said, “No, I don’t feel exhausted,” have been moving into the exhaustion camp. I think we’re becoming more and more aware of the toll that our tools take on us.

And when you read a lot of the popular press and books and things, like Jonathan Hyde’s The Anxious Generation that talks about these big problems associated with social networking sites amongst adolescents, in particular, I think more and more of us are becoming reflective about the role that technology is playing in our everyday lives in ways that we hadn’t really considered before.

So, there’s this dark side that comes with all of the positives of using our technologies and that awareness has been growing.

Pete Mockaitis
So, boy, 2001, those feel like quaint, simple times as compared to today.

Paul Leonardi
Yeah, I know. It’s true.

Pete Mockaitis
So, what’s our percentage at nowadays with your surveys with regard to digital exhaustion?

Paul Leonardi
Yeah, so I survey people on a scale that goes 0 to 6, and it’s probably not super interesting to talk about why that scale is 0 to 6, but what in 2000 to 2001 timeframe, the average response was about a 2.5. So, you know, like, “Okay, I feel a little exhausted,” but sort of low. In 2022, which is the last time that I really conducted a large-scale survey of this, it was up above 5. So, it’s doubled in that 20-year period.

And what’s interesting is there’s been two major inflection points, so two points at which the graph just sort of trended up. The first one was right around 2010, and that’s a particularly important period because we had just seen the introduction of the iPhone two and a half years prior, and Facebook reached a hundred million monthly active users at that point. So, 2010 represents a period of time where social media, in particular, really has, you know, arrived en masse for most people.

And then the second inflection point was 2021, and that’s right after COVID. And, of course, we all know that even for those that worked really intensely on screens and in a very digitally mediated world before COVID, the move to mass working from home, interacting with everybody through digital platforms really seemed to create another spike in that graph.

And what surprised me is that I would have expected at both of those points, as I was watching those numbers increase in real time, some decline afterwards. But I’ve not seen a decline in either of those trends after 2010 and after 2021. The numbers just sort of remain flat. And so, I wonder if we just kind of keep adding a digital tax to our lives and have not been finding a way to reduce that burden.

Pete Mockaitis
And I also wonder, you asked about exhaustion associated with the use of the digital tools, are we pretty sure folks are attributing it accurately or correctly, there’s not some mystery third force bringing in exhaustion upon us and we just blame the tools?

Paul Leonardi
There absolutely might be. You know, there’s a whole confounding set of factors that are important to consider when we talk about exhaustion. One is stress. We get stressed by lots of different things. Not all stress is bad, right? Some stress is good. It creates an adrenaline and cortisol release that allows us to do good things. But we get stressed, and stress is different from exhaustion, I would say. Stress is kind of the more momentary feeling of, “Oh, you know, I just have to respond to these emails. It’s driving me nuts.”

And exhaustion is the cumulative effect of those stressors over time. Now, we get stressed by many things other than our technology, right? We get stressed by the demands people placed on us. We get stressed by, you know, the way people act or behave towards us. We get stressed by the volume of work we might have. So, there’s lots of other stressors that are kind of mingled in with the digital activities that we’re engaged in.

Also, stress and exhaustion are both kind of driving forces that can lead, ultimately, to burnout in our jobs. But burnout is a much bigger concept than exhaustion because burnout is about how we orient to our work more broadly. Are we getting opportunities for promotion? Are we feeling like we’re making a difference? If we don’t have those kinds of things, the research suggests that we tend to feel more burnout.

Exhaustion, though, is a critical component of burnout. Christina Maslach, who developed one of the best burnout inventories, talks about emotional exhaustion as being one of the key predictors of burnout. And it’s perhaps the one that is most prevalent when you are talking about burnout is like how emotionally worn are you. So digital exhaustion is certainly a part of that. Is it the only thing? No. But I do think it’s one important factor that we can control through some changes in our behavior.

Pete Mockaitis
Well, shout out to Christina Maslach, a guest of the show. Yes, understood. Well, then, I’m curious, theoretically, these digital devices “should” be making our lives easier, simpler, better, lower stress, right? Like, whereas, before we had to do all these old-fashioned things, like, you know, find an envelope and a stamp, to send an old-fashioned letter before email.

Or, you can just ramp it up, or we have to mosey on over to a computer to send a note as opposed to getting it on our phones, etc. So, in some ways, or at least that’s part of, I’d say, the promise or the marketing or the hype associated with tech tools, and we’re hearing it now with AI, “It’s going to make your life so much easier.”

Paul Leonardi
Oh, yeah. Oh, yeah.

Pete Mockaitis
How is it that it is a factual statement that I can spend fewer minutes of my life achieving a given outcome by utilizing these digital tools, and yet, I feel more exhausted instead of less exhausted with this empowerment?

Paul Leonardi
Yeah, it’s a great question and it feels like a paradox of sorts, doesn’t it? But let’s take a look at two major drivers of our digital exhaustion – attention and inference. And let me try to give you an example of why what you’re saying, you know, our tools help us to do these things that are supposed to make our life easier, but at the same time end up contributing to our exhaustion, like how both of those things can exist simultaneously.

Okay, so let’s start with attention. We, as humans, appear not to be very well made to move very quickly across lots of different tasks. Our brain takes a beat to disengage from what it’s doing and reengage in a new context. And there’s lots of good science that shows that the kind of disengagement that needs to happen makes it difficult for us to multitask.

But our devices are demanding more and more switches and attention from us all the time across different applications, across different areas of work, across different arenas of our life, from work to home and etc. And we’re just not made for those rapid switches in connection and disconnection that technologies create for us.

So, you’re right on the one hand that it’s wonderful that if an urgent work problem presents itself when I’m at a soccer game for my kid, I don’t now have to, like, you know, maybe 15 years ago, I got the phone call and I’m like, “Oh, no, I need to leave the soccer game and run into the office.” And that would have been really disruptive. Now I can deal with that problem on my smartphone pretty easily from the soccer field.

But what that has created is this fracturing of our attention between my home life and my work life. And I’m now, all of a sudden, situated physically on a soccer field doing work, disembodied, right, and I’m working through my screen in order to sort of be in the office. Not to mention that I’m on an application and, like, I’m working in Google Docs, and all of a sudden, I get an email notification, and I quickly switch to go see what that email notification is.

And then I go back to my Google Docs, and I don’t seamlessly pick up where I left off, because it takes a while for me to re-adjust and port my attention over from the thing I just left. And there’s lots of good research. Gloria Mark is one of my favorite scholars who does a lot of work on attention. And she gives an example that I love, which is that our attention is like a whiteboard.

We think that we’ve written all over the whiteboard and we just erase it and we can write something new. But if you look at most people’s whiteboards, you realize there’s still residue left over from what they wrote before. It’s really hard to erase everything.

Pete Mockaitis
Got to get the spray cleaner going.

Paul Leonardi
Oh, yeah, that little “pst, pst, pst” going. And that’s what our minds are like. And so, it takes time for us to reorient to different activities. And that reorientation, those switches in attention that those reorientations require, are really a great source of our exhaustion, even though the technologies that are allowing us this access in multiple ways are making our lives easier. So that’s one example right around attention.

The next one is what I call inference. And inference turns out to be a huge driver of our exhaustion. And let me kind of take it this way. We are inundated with many, many, many data points all the time. Pieces of emails that come at us, right? We see images that are posted on Instagram or little videos on TikTok. And we get a glimpse about, “Well, what is this person interested in? What is this report really saying? I got this little bit of data from our customers about how many emails they open or whatever it might be.”

And we are constantly forced to grapple with the fact that we see a little and we know we don’t see the whole picture. And so, we’re always trying to fill in the blanks or make assumptions about what’s going on behind the scenes. And that inference-making is like turbocharged now, because we’re constantly inundated with pieces and half-truths and little examples and almost never the full picture. And it takes a lot of cognitive and emotional work to be in a constant state of inference-making.

One example that I love is that I talked to, in interviews for the book, this guy by the name of Dean, and Dean was telling me how, when he was just after graduating college, his buddies wanted to go on a bicycle trip through Europe. And he decided at the last minute he couldn’t go because it just wasn’t a financially prudent move for him.

But he kept watching on Instagram, you know, all the great places they were cycling, the beautiful vistas that they saw, the great pubs that they went to along the way and the friends they were making, and he was making all of these inferences about how they were having the time of their lives, how he felt like a loser because he couldn’t go on the trip with them, so on and so forth, right?

And this might just sound like, “Okay, so what? You’re looking at a bunch of pictures of people’s posts on Instagram.” But having to contend with a world out there that’s giving you pieces of information and making sense about, “Where’s my role in that?” is a really exhausting experience. And we do that all the time. Sometimes it’s through images. A lot of times it’s through just pieces of data that are coming in.

And we’re always looking at ourselves in these platforms also, “How do I appear to other people?” And then making inferences about, “How must they think that I appear given what they see about me? And, oh, did I give the right impression? Did I not?” So, if that all sounds tiring as I’m explaining it, think about what it’s taking in our minds and in our hearts to do that.

Pete Mockaitis
Yeah, boy, you really put a nice point on that and in terms of inference being exhausting. And I’m thinking and talk about half-truths, I find it, I feel that when I watch the news, because I’m doing exactly that, I’m trying to make sense of what’s being communicated to me. And, particularly, I’m going to say politicians, or statements by leaders of technology or business, in terms of, “Is that true? Why do you suppose you said that? Am I being lied to right now? And is that partially true?”

When you said half-truths, I could imagine, in a way, that’s how I feel about most also marketing communications, particularly around AI products, I’d say in terms of, “Okay, what you’re saying seems to be technically not a lie. Like, this application does, in fact, do the thing you say it does. However, it does so unreliably and inconsistently with such need for correction, fixing, editing, redoing, babysitting, it’s like, I’m not quite sure it’s actually useful or value added at this stage of the game in late 2025.”

And, in fact, I saw a study associated with software engineering, for example, which says, “Hey, we actually did a randomized control trial associated with folks who are using AI versus not using AI, their experience, they know their code base and what they’re up to. And when you measure it on the clock, it was slower, fixing the AI errors.”

And yet it feels faster because sometimes it gets it right, and it’s like, “Whoa, that’s impressive.” And it’s just a good feeling and it is sort of, like, wowing. And so, I think you’re right, in a world where we’re getting lots of half-truths, it is exhausting. And I’m coming back to flashback. I had to check out, potentially getting a new roof.

We own a little multifamily home in Chicago, and it was over a hundred years old, the building. And so, it seemed like, “Oh, yeah, that roof may need some care.” And so, I was having a heck of a hard time getting anybody to come on over. So, I was like, “You know what, the heck with it. I’m just going to call 20 roofing companies.”

Paul Leonardi
See who shows up? Right.

Pete Mockaitis
“And we’ll see how many people show up.” And I got about five, which, I mean, is striking there.

Paul Leonardi
That’s about par for the course these days. Yeah.

Pete Mockaitis
You know, 15 out of 20, just don’t even want your money, but, okay. So, I got about five, and it was so tricky because some people say, “Oh, no, you got to tear off the whole thing and just start again.” And others were like, “Oh, no, we can just put another layer on the existing.” And it’s like, “Well, putting another layer is much cheaper, and so I would like to do that if I can, but can I?”

And I found it very mentally exhausting because, here I am, it was about three versus two, the opinions on just another layer versus just tear the whole thing off. And I think that this is just so common of so many situations. It’s like there’s ambiguity and we’re getting different messages from different people.

And you’re wondering, “Am I being straight up lied to by one of them? Is there a nuance I’m not understanding? Like, how can I deduce what is true?” And it’s exhausting. I see the same thing when I’m evaluating potential marketing initiatives. It’s just like, “Well, who knows what’s going to happen?”

Paul Leonardi
I like your roofing example. It rings true. Maybe we’re just unlucky and need to buy roofs, the two of us, but I think this sort of puts it into perspective. In 2000, or like early 2000, I also owned a rental property that needed a new roof. I’m not making this up. And I also got some conflicting bids.

And I remember thinking at the time, that I know nothing about roofing and I still don’t really know much about roofing today. And I had few ways of really knowing what was the best course of action. And, more importantly, I didn’t know, I didn’t think that I could find out. I really needed to figure out who was the best expert or who could I trust and I would lean in on their expertise.

Today in 2025, if I needed a new roof, and I got conflicting estimates that said, “You needed to do things,” the first thing I would think is, “I can figure out what really I need here.” We have this impression that the world’s information is at our fingertips, and if I only look in the right places and if I do the right kind of research, I’ll be able to determine what the right course of action is. The reality is, even though we might think that, it’s really hard to do.

But knowing that the possibility exists, and thinking I should be going and looking for it is exhausting. And for many people, it’s demotivating. And this is one thing I found over and over again as I was doing the studies for this book, that when you reach these kinds of critical decision points where you feel like, “The world’s information is at my fingertips and I should be able to make a great decision out of this, and I’m an idiot if I make the wrong decision,” people just don’t act a lot of times. It stalls them.

A kind of a funny related story, this was maybe 10 years ago. I was doing some work with a really large company, a software company that is, I won’t name, but is very into search. And I was with a group that sort of, that helped advise companies about ad buying.

And what was really funny to me in these meetings was, somebody would come, like a project manager would come, and they would say, “Okay, here’s the strategy that we think we’re going to use to advise this company on how to make their ad purchases,” how to increase click through rate, let’s say.

And someone on the team would say, “Oh, do we have data to test your hypothesis?” And then everybody would kind of giggle, and be like, “Yes, we have all the data.” And so, they would say, “Well, go test that hypothesis and then come back and then we’ll decide if we should advise the company to do this or not.”

So, they would come back, and then someone would say, “Hmm, what if this?” “Oh, do we have the data for that?” And then they’d all laugh and then they’d go back. And it was this whole, like, analysis, paralysis by analysis. It’s like they almost never made decisions about what to do because they realized, “We have all the data. We should just keep going back and looking at it.”

And this is the kind of thing that I see people doing all the time, is we just don’t act because we feel that we should do more. And the act of trying to do more is exhausting, and knowing that I’m never going to get the complete amount of information wears us out just thinking about that. So, it’s this matrix of data and technology and expectation and inference that we’re trapped in these days, I think, that creates these real deep feelings of like, “Aargh, why do I have to do more? Why can’t I just break free?”

Pete Mockaitis
Understood. Okay. Well, I think this is hugely valuable already, just surfacing what’s going on, “Oh, hey, you’re doing a lot of attention switching, you’re doing a lot of inferring, and you have too much to look at with regard to your switching of attention and your potential extra data points to go about your inferring.” So, Paul, lay it on us, if we want to find more energy, less exhaustion, what’s the most leveraged stuff we can do to achieve this?

Paul Leonardi
Yeah, so where I like to begin is to say, if you understand that these attention switches, this inference-making, these are the key contributors to our exhaustion, then what we need to do is figure out, “How do we reduce the amount that we are switching our attention and the inference making that we have to do?” So that’s the big picture. Those are the things we need to work on.

So, then we can start to talk about very specific strategies that help us to do that. One of them that I love that I call, it’s rule number three in my book, it’s called make a match. And the premise is simple. The execution, though, is harder. So, here’s the premise. We often are dealing with situations that are ambiguous. The answer is not straightforward. There’s going to be some amount of negotiation or conflict that I need.

These are regular occurrences in our work days and in our lives outside of work. We also deal with some situations that are pretty straightforward. You know, like, “Are you going to pick up the kid or am I going to pick up the kid?” “Do we send this email to the client tomorrow morning or this afternoon?” We don’t need to reduce a lot of ambiguity, have a lot of discussion around a lot of those issues. They’re pretty easy to resolve.

What I see happen often, though, is that we choose the wrong medium, the wrong tool for the job given the level of ambiguity, disagreement, discussion that needs to take place. So, think about an issue, I’ll just give an example of something that happened to me. We needed to do some re-budgeting in the department that I worked with, and I chair a department and I was working with one of our assistants.

I happened to be traveling. I was in Europe when this issue came up and we needed to sort of quickly talk about the budget and recategorize some things. And I just kept thinking, “This is like a straightforward issue. Let’s just do X, Y, and Z.” And my admin person that I was working with kept, like, responding in these kinds of weird ways. And it wasn’t clear that she was going to make the changes that I was suggesting.

And then, like I would get kind of more upset and my email became a little tenser, and I said, “Look, we just need to act on this.” And then there was a day of response, compounded by the fact that I was overseas, and I was eight hours’ time difference. And this became such an emotionally exhausting interaction for me because I began to think, “Oh, man, she’s trying to subvert me. Like, she’s not responding on purpose to this.”

And I was kind of spiraling, having these negative assumptions. And what I realized kind of in the process was, “You know, this is not a super simple issue. My first impression was this was simple, but if I really thought about it, this is much more complex. And I’m trying to resolve this complex issue through email asynchronously. And we have this time difference.”

“And the best thing that I could do to reduce this ambiguity and to stop me making so many assumptions and her making so many assumptions is just to hop on a Zoom call.” And we did, and we hammered out the whole issue in like 10 minutes. But it was two days, or almost three days, of me like wasting my life away, it felt like, being upset about this. I talked to my wife, I was like, “Oh, I’m so frustrated by this interaction that I’m having.”

But what didn’t I do? I didn’t stop to say, “What am I trying to accomplish here? And what’s the best mode of interaction to deal with this problem? It’s an ambiguous situation. It’s going to require some collaboration, some real time discussion.” And if I just had picked up the phone, just had done the Zoom, I would have resolved this so much faster.

But when we don’t do that, things escalate. We send more emails that are pulling us out of our attention that we’re paying to other things at the moment. We’re forced to make more inferences about, “Why didn’t this person respond faster? What did they mean?”

And the same goes in the opposite direction, that if we have a super simple issue and then we have a big meeting to discuss it, when really it was like, we pretty much could have just decided this via email, we waste a ton of time and attention and emotion talking to death about something that we could have resolved much more easily.

So, we can reduce our attention, we can reduce the amount of inference that we’re making, if we’re matching the complexity of the challenge with the capabilities of the tool. So, the shorthand here is, if you’ve got a more complex challenging issue, you want to use a tool that’s going to put you in real-time collaboration and discussion so you can resolve those issues interactively.

And if you have a pretty basic kind of thing that you’re trying to solve, then switching to a low-fidelity medium that just like allows you to say yes, no, agree and move on, probably is going to be the best bet. So, making a match between those information requirements and the capabilities of the technology is one key way to reduce that inference-making and attention switching.

Pete Mockaitis
That’s handy. And I’m also thinking about making a match associated with the time necessary for something. I think if you’ve got a mismatch on either side, it’s frustrating and annoying in terms of, “Why are we having a three-hour meeting about this? This is ridiculous,” versus, “Okay, we’re just going to figure out this tricky challenge that’s been vexing the business for eight years in our little 30-minute call.”

Paul Leonardi
Exactly.

Pete Mockaitis
Well, either way, you’re going to find frustration if you have a mismatch of the tool, the medium, or the time. And then I think that expectation piece as well is tricky in there because it almost seems like you “should” be able to resolve it in the time that you have scheduled for it when you may just have scheduled the wrong amount of time.

Paul Leonardi
Yeah, and then everybody feels frustrated and demotivated because, “Well, clearly, we didn’t do our job right. We should have figured this out in an hour. We must be a dysfunctional group or we must not have brought the right information to this meeting.” When, to your point, perhaps it was an inappropriate time allotted for this in the first place, “And we never could have done it. And now we just all feel worse for having tried.”

Pete Mockaitis
All right. So, make a match. What’s your other favorite approach?

Paul Leonardi
Yeah, another one that I really like is the first rule that I talk about, which is reduce half your tools. And this is one that a lot of people give me the side eye about when I say it, like, “What do you mean by just like stop using half of my tools? Am I really going to be able to do that?” The answer is, yes, you’re really going to be able to get most of the way there at least, you know, 50% is just a rough number anyway.

But if you think about these ideas of attention switching and inference, the fewer tools that we have in our toolset, the less likely we’re going to be to suffer the problems associated with those two drivers of exhaustion. So, one of the things that I really suggest that people focus on is to look at, and really make a list of, “What are all the different technologies that I’m using on a daily basis?”

I used to ask people to do this 10, 15 years ago, and they come up with about 10. And a lot of those were hardware. So, they would say, “I use my laptop, and I use my BlackBerry, and I use…” you know, whatever. Today, the number is more like 30. People come up with about 30 different tools that they use in a regular day, and most of those are applications. Many of them are at work, “I use SharePoint. I use Zoom. I use, whatever it might be, ChatGPT.”

And many of those are at home, “I use Instagram and I use Zillow and I use Game Changer app to keep track of my kids’ games.” And one of the things that I recommend is, when you make this list, that you first start going through and you say, “Okay, well, which ones of these do I have the actual power to cross off this list?” And, usually, we have more power at home than we do at work.

And then I say, “Well, which ones are functionally duplicates of each other? So, are we using two tools to do roughly the same job? So, do I have a Zoom meeting sometimes and then I have a Microsoft Teams meetings other times? Or do I use Canva and Photoshop, when, really, they’re doing the same thing and I don’t know why I use both of them anyway?” And so those are candidates for reducing from our list.

And then there’s other ones where, “I’m actually just sort of in charge and there aren’t network effects.” So, you know, it may be that I say, “I really would love to give up Slack in my organization, but I can’t just give up Slack because everybody uses Slack, and they depend on me.” However, I’ve talked to a lot of people that have two or three team chat applications. And when I ask them, “Well, why in the world does your team have two or three?” nobody can really recall.

And so, what I find is that many people have told me that they actually will raise this in their organizations, and say, “You know, like we’re chatting on Teams and on Slack and on this third application. Like, is it possible we could just reduce to one?” And usually the team is like, “Yeah, like why don’t we just stick with Slack or whatever?”

And so, we actually do have the power to reduce the number of tools in our toolset. I think, in more ways, we have more degrees of freedom than we typically think we do. And doing that just means that now we’re switching between fewer applications and we’re doing fewer things that are creating those attention-switching and opportunities for inference.

You know, just a super quick example in my own life, it used to be that in a given morning, I might be on Zoom, Microsoft Teams, and Cisco’s Webex, you know, I would be doing video conferences on all three. And that doesn’t sound like a big deal except that I’m very comfortable with Zoom, because that’s the one my organization uses most often.

And when I switch to a different one and I’m trying to share my screen or engage in the chat or create a breakout room, there’s those moments of, “Oh, where’s the button for that? And how do I create the breakout room because I’m not as familiar with the other platform?” And it’s those little moments of friction that add up to be exhausting.

And reducing those, as much as we possibly can, just give us a cleaner starting point and is going to reduce the odds that we’re going to feel exhaustion from our tools if we can reduce the toolset. And my advice to leaders in organizations is that, often it’s difficult to really make a noticeable difference in the volume of tools that we have unless you step in and you make some decision.

I had one senior leader tell me, “You know, I think of this like the Smokey the Bear slogan, ‘Only you can prevent forest fires.’ It’s like, I feel like I’ve really realized only I can prevent technology proliferation.” And that’s because you’ve got the model for many of these SaaS vendors who sell tools in your company, is to price it in just a way that anybody can buy that application with their credit card.

It sorts of sneaks in right below the spending limit of, “I need formal approval from IT.” So, you get all of these applications that kind of spring up everywhere. And unless you have someone looking and saying, “Look, we’re not paying for 20 different subscriptions to the same kind of tool,” or, “We don’t need three different kinds of computer rendering platforms,” it’s really easy to get stuck with too many tools and increase our overload.

Pete Mockaitis
Yeah, it’s interesting how I’ve experienced this and, it’s so funny, it doesn’t seem like it “should” be that big of a deal. But if I have to hop into six different tools to accomplish a task, even if it’s only like a 10-minute task, it really does take a toll, more so than if I were just cruising through email, say, for 10 minutes. And it’s just so funny that that’s just kind of the human condition.

Paul Leonardi
It’s true. And we don’t notice it. I think I liken it to running sprints, okay? So, if you run all out on a sprint, let’s say for 10 seconds, and you cover a hundred meters, you feel pretty good. And the next sprint that you run, if you’re not resting adequately, you might cover a hundred meters in 12 seconds. And then the third one, you cover a hundred meters in 14 seconds.

You feel energetic, right? You feel like, “I can do it,” but it’s the accumulation of that fatigue over time that eventually hits you, and someone says, “Okay, run one more hundred-meter sprint,” and you’re like, “No, I can’t do it. I’m too exhausted.” And it’s those little micro moments that add up to big exhaustion feelings at the end of the day, just like you described.

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

Paul Leonardi
I just want to say, okay, AI, this is where I think AI, if we do it right, because we’re still in the early stages, could be really useful. If we can figure out how to put AI in a role that helps us to stay engaged in a task, keep our focus without having to switch across so many different applications, without having to go look for so many different pieces of information, that’s where these tools could be most useful in helping to reduce our exhaustion.

So, I’m optimistic. I wouldn’t say that I think that that’s where everything is going, but I’m optimistic that these tools might be helpful as they keep us in our workflows, keep our focus and engagement in areas that we want by reducing the number of tools we need to switch across and reducing the amount of attention changes that we constantly have to make.

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

Paul Leonardi
It’s attributed to the philosopher Voltaire. I’m not sure if there’s any real record that he said it, but the older I get, the more I appreciate this quote. And it’s, “Cherish those who seek the truth. Beware of those who find it.”

Pete Mockaitis
Okay. And a favorite study or experiment or bit of research?

Paul Leonardi
Yeah, one of my all-time favorites is The Jam Study that was done by researchers at Stanford, Iyengar and Lepper. And what they looked at was people buying jams. And it was a really neat little experimental condition where they showed people, I forget the exact number, but like three or four jams, and then said, “How many did people buy jam?”

And then they gave them a display that had like lots of jams, like 20 jams on them. And then they said, “How many people bought jams?” And you’re way more likely to buy a jam if you saw three or four jams than if you saw 20 jams. And their conclusion was too much choice is demotivating. And I love that. It’s a simple study, a powerful finding. And every time I go to a restaurant and get one of those menus that seems to span 30 pages and can’t decide what I want to eat, I remember that study.

Pete Mockaitis
Yeah. And a favorite book?

Paul Leonardi
One of my favorites is At Home by Bill Bryson. I just really love the way Bill Bryson writes. He does a couple of things. One, he just takes these, what you would think are mundane topics, like At Home, he has a 17th century English farmhouse that he lives in, and he uses that, he walks through every room in the house, and uses that to talk about, “Well, what was life like four centuries ago?” And that’s cool.

Pete Mockaitis
All right. And a favorite habit?

Paul Leonardi
This is one that I’ve been cultivating much more since writing the book, and it’s about being intentional. So, when I pick up one of my devices, or I’m going to get on my computer, I really take a beat and think, “What am I trying to accomplish? And how will I know that I got there?” And what that does for me is it allows me to bookend my experience.

It tells me, “You did it. Time to close your browser,” or, “Okay, you finished doing this. Time to put your phone down.” And if I don’t start with that intention, it’s easy to spiral into just continuing to scroll and doing all the things that make me exhausted. So that’s my new favorite habit, be intentional every time I sit down in front of a device or pick one up.

Pete Mockaitis
Okay. And is there a key nugget you share that really connects and resonates, and people quote back to you often?

Paul Leonardi
Yeah, they say about this, the idea of, “I don’t want to give up all of the technologies that do great things for me. And I haven’t been able to figure out what I’m supposed to do then to find the right balance.” And the fact that you give some rules and say, “Technology is not the problem. It’s how we use it, how we orient to it, that it really is,” they tell me that’s been empowering.

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

Paul Leonardi
Yeah, I say go to PaulLeonardi.com, or you can find me on LinkedIn. I think P. Leonardi is my handle there. Those are great places to find me, or at UCSB’s Technology Management Department.

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

Paul Leonardi
Yeah, I would say really practice being there, wherever you are. We live in a world that makes it very easy for us to be everywhere else but here, which we can teleport in our minds to places, we can be on our devices and be halfway across the world. But there’s a real power in just being where you are, be in the meeting, be in the conversation, be with your kid. Try that and I think you’ll see there’s a big difference.

Pete Mockaitis
All right. Paul, thank you.

Paul Leonardi
Thanks so much for having me.

Pete Mockaitis
Gianluca, welcome!

Gianluca Mauro
Hey, thank you for having me.

Pete Mockaitis
Well, I’m excited to be chatting with you about AI. You are a genuine expert. You’ve been researching and studying this stuff way before even normal folks had heard of this ChatGPT business. So great to have you. And tell us, any super surprising discoveries you’ve made along the way as you’re researching and teaching this stuff?

Gianluca Mauro
Well, first of all, I think something that is interesting to think about is when ChatGPT came out three years ago, it was the “Oh, my God” moment for most people, right? But AI has been out there for quite some time in different shapes and forms and with different levels of usefulness, let’s say. And I think the first “Oh, my God” moment for me was when I realized that, basically, every industry and every professional could find a use for AI.

And I’ll tell you probably what was the most interesting, or strangest maybe, project I worked on. I worked on an AI project to control the quality of diapers in a factory. So, yes, you can use AI for pretty much everything.

Pete Mockaitis
Well, now I just can’t let that go. How does AI help do quality control for diapers?

Gianluca Mauro
Well, so are you ready to go on a journey on how a diaper factory production unit works?

Pete Mockaitis
I imagine AI might be able to analyze rapid photographic imagery of diapers as they come off of the line to assess quickly potential for defects and fix the issue more quickly upstream prior to them being packaged and having to be thrown away. But I’m totally making that up.

Gianluca Mauro
You got it.

Pete Mockaitis
Oh, I feel like a genius. Yes!

Gianluca Mauro
Oh, my God, you are. This is extremely accurate. Extremely accurate. We had this issue that, you know, they basically have, a diaper is basically two layers of elastic material with something that is absorbing in the middle. And then if you pull this elastic material too much, it breaks, especially when you’re cutting it into shape.

Pete Mockaitis
Been there.

Gianluca Mauro
Yeah, exactly. So, if you had kids, you know that that’s not fun. So, we were looking at all these pictures in the factory as they were cut into shape to try to understand, well, what was the ideal size of those big elastic rolls and try to basically optimize productivity. So, that was quite a crazy moment because, think about this.

I did this project maybe seven or eight years ago, so three or four years before ChatGPT came out. It was not obvious for anybody or for any company that they might have a use case for AI.

So, imagine me when I went and pitched a diaper production company, “Hey, maybe you should look into AI to minimize the mistakes, the defects that come out of your factory.” It was not obvious at all. It was quite interesting to find actually amazing use cases in that context as well.

Pete Mockaitis
Well, that’s very, very intriguing. Well, so we’re talking about everyday professionals utilizing ChatGPT or other AI tools to be more productive. You’ve got a LinkedIn Learning Course on exactly that. So that’s pretty handy. Could you maybe start us off by sharing what’s perhaps a fundamental misconception or mindset shift that helps make all of this stuff make sense?

Because I imagine we could spend all day talking about, “Oh, here’s a really cool prompt,” or, “Oh, here’s a fun little tactic,” “Here’s a nifty little thing you might try.” But could you maybe set the stage for us on a more principled foundational level to help us scaffold the rest?

Gianluca Mauro
Absolutely. And I think the most important thing for everybody listening, you need to understand that, in order to really get value from AI, the number one thing you should focus on is your mindset and changing your habits. This is not anymore about necessarily getting the right tools. Most tools are pretty good today, not perfect, but, you know, they’re pretty solid, especially compared to three years ago. And it’s not even about having the most amazing prompting skills.

The biggest bottleneck is your habits. How much have you embedded AI tools and new different workflows and ways of working in your day-to-day work?

I’ll give you an example, I love making this metaphor. It’s like going to the gym. So, let’s say that you have the best equipment. That’s the equivalent of having the best tools. And let’s say you also have amazing skills. You have a squat with perfect technique and you know exactly how to do a really good bench press. And that’s the equivalent to having really good prompting skills.

But then let’s say you never go to the gym. Guess what? Your muscles ain’t going to grow. You’re not going to lose the weight that you want to lose. That’s not going to happen. I would rather see somebody with okay tool selection and with okay prompting skills, but, really, somebody who’s invested a lot in rethinking the way that you work and is curious and is constantly trying new things out than having somebody who has read all those scientific publications about best prompting techniques and has bought all the AI tools, but then has not adapted the way that you work to work with these tools.

That’s the most important thing today in this context. I wouldn’t have said that three years ago, but that’s where we are today. You need to really change the way that you work and embed them in your workflow. And that requires a little bit of effort.

Pete Mockaitis
I hear you. It does require a little bit of effort. And I would also say some discernment, because I think that my impression is, and you can tell me if this is accurate or not from your research-based perspective, it almost feels like a lot of companies, CEOs, products, just kind of want to shove AI into something because investors want it, the stock market seems to like it, and maybe some people are impressed.

But I’m almost at the point now, when I see a tool say, “Oh, now we have AI,” I’m like, “Oh, geez. Is it any good or is it just going to disappoint me again like all the rest, you know?” And so, that’s my take is that, yes, we should take a look at our habits and get into the groove of using AI tools where they’re genuinely helpful and useful and handy. And that requires a little bit of change management on our own parts.

But my hunch is there are also times where you say, “No, AI has actually no place in this little piece whatsoever, and so we’re going to deliberately choose to not stick it here but instead put it over there.”

Gianluca Mauro
You’re spot on. And there was actually research about this that I found really interesting. It was done by Stanford with a couple of other people, and then the Harvard Business Review wrote an article about this that went quite viral. The title of the article is “AI-Generated ‘Workslop’ Is Destroying Productivity.”

Pete Mockaitis
That’ll get some clicks.

Gianluca Mauro
That’s going to get some clicks. Exactly. And so, the main outcome of this research was that if you ask people, “Hey, what do you think about your colleagues who use AI?” You’re going to find that colleagues who use AI are often perceived as less creative, less capable, less reliable, less trustworthy and less intelligent. And that is not great.

Pete Mockaitis
Yeah, fair.

Gianluca Mauro
You do not want to be perceived as less intelligent, trustworthy, reliable, capable and creative. So, the interesting thing in this case was I honestly don’t think, and that’s also what the researchers found, that that’s a problem of AI per se. The problem is that a lot of people are using AI just in the wrong way. What does that mean in practice? Well, AI workslop is basically when you are trying to use AI as an amplifier of your laziness, basically.

Pete Mockaitis
Ooh, tweet that!

Gianluca Mauro
Yeah, and I want to give a practical example, okay? Let’s say that you ask me, “Hey, Gianluca, I want to know how I might use AI in my podcast,” okay? And let’s say that I am just so lazy, I don’t want to think about what are your challenges. I don’t want to think about what are your objectives. I don’t want to think about your audience. I just go on ChatGPT and I ask, “Hey, how might a podcast producer or host use AI?” I get a research. I copy it. I send it to you. What happened?

I got a generic piece of, like a bunch of text basically, on a PDF. I gave it to you and it took me no time to produce that. It took me, like, 30 seconds to get like a bunch of text that sort of makes sense. But I’m going to waste your time reading something that is so generic that you could have found on one Google Search. So that is something that damages you because you just wasted your time reading the report that is generic and has wasted my time as well, because now you’re going to ask me questions I need to go and fix it and you’re going to think less of me, etc.

Now let’s see what I should have done if I wanted to use AI to make it way, way better, way more interesting. I would have started asking you questions, “Hey, Pete, what are the top challenges that you have? What are your objectives for next year? What do you think could be the thing that helps you the most? Do you want to be more productive? Do you want to repurpose your content more effectively? Do you want to be able to research your guests better? Like, just tell me, tell me what’s going on.”

You provide me some context. Context is a keyword that is super important in today’s AI era. You give me some context. Then with this context, I go on ChatGPT, and I say, “Hey, I interviewed Pete. These are his top challenges. What do you think might be a relevant use of AI?” Now start getting something interesting. I start getting something that is more relevant.

And then I might say, “Okay, cool, ChatGPT. Now go and find top case studies of similar podcasts to How to be Awesome at Your Job that have done something similar. Now find some tools. Now tell me what could be potential risks.” The output, then, that I send you is going to be much higher quality and it’s going to actually give you value.

But notice how the difference is not the tools. It’s not that I used a different tool that is not ChatGPT, or is that I had some special prompting skills. It’s just that I’ve been mindful. I’ve been mindful of what might be interesting, what might be relevant for Pete, and how might I use ChatGPT to basically boost my productivity and make my suggestions for Pete even more and more relevant and useful.

You see the difference. It’s not about the tool. It’s not about how good am I in prompting. I didn’t talk about doing anything particularly fancy here, okay? It’s not fancy prompting technique, there’s no coding involved, it’s just a different mindset. I tried to use AI to amplify what I would have done if I didn’t have AI. And that really works.

Pete Mockaitis
Yes, it really does. And what you’re reminding me, and you’re talking about amplifying your laziness. I’m thinking about there was a fabulous interview on The Copywriter Club Podcast, which I listen to, even though I’m not a professional copywriter, but we’re doing copywriting all the time. And there was a famed copywriter on there. We’ll look him up and put him in the show notes.

And he said, “When I’m using AI to assist me with copywriting, I don’t say, ‘Write me a sales letter.’” It’s like, “What I do is…” well, first of all, he’s using the custom APIs of an AI tool as opposed to any off-the-shelf chatbot. And then he’s saying, “Okay, I’m going to write this part of a sales letter, given all of these instructions that I have previously written for what I’m into, as well as several examples, as well as what the product is and how it’s helpful to a certain user base on these needs and want and preferences and desires and pain points. And then, so voila.”

And so, there are numerous multi hundred-word prompts associated with doing a thing. And then he was like, “Okay, this is a pretty good draft. And from that I can tweak.” And so, we’re not amplifying laziness. In fact, a tremendous amount of thought has gone into what we’re doing here. And then, because he’s done it many, many times, and he also said AI does not account for taste.

Gianluca Mauro
Yeah, exactly.

Pete Mockaitis
And then from there, you can get it. And that was a real lightbulb for me, which I’m connecting now with your amplifying laziness comment. It’s like, yeah, if you just say, “Hey, do this thing,” you’re going to be disappointed. But if you put a ton of thought into it, it can kind of get you to a draft substantially faster.

Gianluca Mauro
Absolutely. And I’ll tell you what, you can amplify laziness, but you can also amplify your expertise. You can also amplify your perfectionism, if you’re a perfectionist like me. And I will give everybody a very simple thing that they can try right now. So, I’ll give you a simple prompt structure that you can use. And it’s very simple, okay? Just four lines.

So, start with some context. Context is basically the who, the why, and the what. So, you might say, “Hey, I am a podcast host. I need to…” whatever, “…prepare for a new interview with this person. My objective is to make sure that I ask the most interesting questions about this person.” Okay, that’s context. What are we talking about? I’m assuming I’m putting myself in your shoes, by the way.

Okay, so that’s the context. Then you say, you ask AI, “I will give you, for instance, a list of questions I prepared.” Something you’ve done, okay? Something that, you know, maybe 50% effort, something that is almost there. And then it will say, “You will tell me…” that’s what you’re telling the AI, “You will tell me three things I’ve done well and three things I could improve.”

“For each improvement opportunity, provide suggestions on how I could implement them. Make your feedback concise and reference specific parts of the text I gave you.” And then you just paste in your work at the end. I use this all the time.

And it’s such a simple way of using it, right? It just takes something you’ve done, and you just say, “Hey, this is my context.” Again, context is super important. It’s super important, because if you don’t put your who, why and what, then you’re get generic advice that might actually lead you in the wrong direction, right?

So, if you put the right context and if you ask this, so much value and, honestly, you can get to some pretty amazing return investment in like two minutes. Every skeptic I have, every skeptic I speak with, and, you know, I still meet quite a lot, I ask them to do this, and they always come out quite interested in the tool after that.

An example I can give you is I worked with lawyers. Gosh, lawyers are an interesting crowd, because obviously, they’re very critical for really valid reasons.

And I always tell them, “Look, take a case that you have that you can share publicly, take a response that you have written or something that you’ve produced, and just ask for three things that you’ve done well and three things that you could potentially improve and how.” And, usually, they get one thought, and they’re like, “Huh, I haven’t thought about it. Interesting.”

Then they might decide not to use it. That’s up to them. But having a really expert second opinion with a one-minute effort and for free, honestly, “Where do I sign?” It’s amazing, isn’t it?

Pete Mockaitis
Yes. And I’m thinking about, when you said expert opinion, it’s funny, when I heard that, I reacted a little bit because I’m thinking about Sam Altman talking about, you know, doing his very Sam Altman storytelling thing that he’s good at. Talking about the release of GPT-5, it’s like, “You know, before it was like you’re talking to a high schooler. And now it’s like you’re talking to a PhD in any area.”

And so, I was like, “Hmm, this is really not my experience at all, good sir.” But I think it’s expert in the sense that it’s been around the block. It’s like, “Yo, I’ve read the whole internet, okay? So, in that sense, I’m expert.” And I’m thinking about, there’s this book called Obvious Adams. It’s all about thinking, “Well, what would be the most obvious thing?” Or, Tim Ferriss says a question, “What would this look like if it were simple?”

That’s often my experience is it says the thing that’s not crazy, innovative, and brilliantly never before seen, but it’s like, “Huh, I probably should have thought of that, but I didn’t, and you did. And because you’ve surfaced that, we’re moving this forward, and that’s helpful. Thank you.”

Gianluca Mauro
Yeah, absolutely. So, I think one thing that is really not intuitive is that AI sometimes feels extremely smart and sometimes feels extremely dumb. And it’s really hard to predict, whether for my specific task is going to be, you know, the former or the latter, like, “Is this a 10 out of 10 question or is it going to be a one out of 10 question?”

There was this famous viral thing, viral experiment that came out, which is if you asked AI to count how many Rs are in the word strawberry, it would just say two, and there are three, right? I think a five-year-old can do that, probably, you know, but AI can’t do that. But, hey, it can write a pretty good legal letter for, you know. It’s just like so weird. It’s like it can do math, it can write code, but then it can’t count Rs in the word strawberry. Like, what is this?

And I think we just need to understand that it’s called artificial intelligence, but it’s not intelligent in the same way that humans are. It’s a different kind of intelligence. It processes data in a different way. It’s really hard to just give people a sort of like cookie cutter, very simple rule of thumb to understand when you’re in a good space to ask questions to AI and when not.

You just need to develop a little bit of sort of a gut feeling for, “Hey, this is something where I might get something good, and this is something where I might not get something good,” but there are guidelines. And the guidelines are, there was this research done by Harvard Business School, and they basically came up with a very simple classification of skills that AI has, so to say, AI capabilities. They call them within the frontier skills.

And these are four, very simple. Copywriting. AI is amazing at taking text and just turn that into other text. Now, a professional copywriter might argue whether that’s good copywriting or not. That’s a different conversation, but it’s amazing at just manipulating text, writing poetry or, think about this. It can write poetry and a legal document. I can’t do either, okay? So, it can do all these things. So that’s the first one, copywriting.

Second one is persuasiveness. So, it can write pretty good arguments if you ask it to, which is interesting. The third one is they call it analytical thinking. And it’s quite interesting if you give it a complex problem, and if you ask it to analyze it, it can give you recommendations or different ways to look at it.

And that’s the example that I gave you before, right? If you give it something that you have produced, legal letter, interview questions, whatever, and you say, “Tell me three things I have done well, three things I could improve based on the context,” it does it really well. So, this sort of like analysis, analytical capabilities.

And the fourth one is creativity. Now, people argue whether that’s real creativity or not. I don’t want to get into that philosophical conversation, but from a pragmatic point of view, it is quite creative, honestly. I had this thing a few days ago where I had a framework that I came up with to support companies in finding use cases for AI. And I was like, “How do I call this thing?

And I just gave it to GPT-5 Thinking, and I said, “Just please come up with an acronym.” And I would have never come up with any of them. It was super interesting and creative and it worked quite well. So, these are four things where you can feel quite confident. So analytical thinking, copywriting, persuasiveness, and creativity.

Now they also found where AI does not perform well at all. And that’s when you’re asking it to give you a recommendation, analyzing a bunch of different conflicting pieces of evidence. Let me give you an example. What they did is they took a few researchers, sorry, a few consultants from Boswell Consulting Group.

They took these consultants and they asked them to analyze a bunch of evidence of different strategies that a business might decide to go for to launch a new product, okay? Three different strategies. There’s a PDF with a bunch of interviews. There’s an Excel sheet with a bunch of numbers. All of these things, you need to look at this evidence and ask AI to help you in identifying the right strategy.

What they found is consultants perform better if they did not use AI to come up with the right strategy. Why did that happen? Well, because when you have conflicting evidence, conflicting pieces of information, in this case, imagine data said, I’m just coming up with stuff now, data said that sales were going up. But in an interview, somebody’s sales are going down. There was this conflicting piece of evidence.

AI was basically just like going with one. It was really hard for the AI to understand what was true and what was not. Whereas, for humans, it just made more sense to, for instance, look at Excel sheet, but ignore the interview because they thought maybe this person doesn’t know, doesn’t have the most updated data, for instance, that’s an example. So, AI was just like misled by the data that you provided.

Unfortunately, that’s how a lot of people use AI. A lot of people use AI today this way. Get a bunch of PDFs, a bunch of data, a bunch of emails, a bunch of stuff, throw it in, and they just ask for a quick answer to the problems. AI doesn’t work that well when you provide an insane amount of information and just ask, “Hey, tell me what I should do.” You should go step by step. You should use it to, again, amplify your thinking.

So, a better way would be, put this data in and say, “Hey, can you summarize the key takeaways from each one of these documents?” You take them and then you say, “Okay, what might be a good strategy? What might be good arguments for strategy one? And what might be good arguments for strategy two and strategy three?”

You see how you’re using it as a co-pilot. And that’s a really good branding from Microsoft, by the way. You’re using it as something that assists you in thinking rather than a, “Hey, I’m going to throw all my data. Just go ahead and do my thing. I’m lazy. I’m just going to copy your output and give it to my boss, you know.”

Pete Mockaitis
Yeah, I like that a lot. And, in a way, it really makes sense that it is that way because it just says, “Hey, I just know what words mean and what words tend to come after and next to other words. I don’t actually know that some dude’s opinion is of less importance and should be given less weight, gravitas, than a summary sales data reflective of millions of transactions.

Gianluca Mauro
Yeah, and it’s sycophantic as well, so it’s trying to please you. Imagine like, you know, you go to a doctor and say, “Hey, I have some headache,” and the doctor tells you, ‘Get this. Get this pill and just go.” Well, that’s not a good doctor. You should ask a little bit more questions and trying to understand.

What AI, and this is improving by the way, but historically, has been trained and, you know, it’s used to just get an answer. And so, if you provide maybe conflicting piece of information, as we said in the case study before, it’s just going to try to give you an answer rather than pushing back. And I go back to what I was saying before. This means that the tool is powerful, but it all comes down to the mindset that you have when you use it.

Do you want to have quick answers and you just want to get as fast as possible to a bunch of texts you can send to your boss or you can publish on LinkedIn? It’s probably going to just boost your laziness and just not get anything high quality. But if instead you use it as an amplifier for your curiosity, for your expertise, for your capabilities, well, now we’re talking. Now you can really get to some amazing outputs.

Pete Mockaitis
Yes, I like that a lot, the amplifier. And it’s interesting, is sometimes, I think when you look at the prompt that you’re sharing, it really does kind of garbage in, garbage out, and it’s the opposite, you know, magnificence in, magnificence out. So, I could say, “Hey, give me some information about sleep apnea.” And so, it can say, “Oh, well, this is a common affliction, blah, blah, blah.”

But then what I’ve said is, “Show me the results of several human randomized control trials that utilize novel interventions for the treatment of sleep apnea, i.e., not a CPAP machine. And give me a summary of the quantified impacts associated with the apnea hypopnea index reduction associated with each.” Now that, and sure enough, that has led me to some interesting places. And I found this thing called inspiratory muscular training. You breathe against resistance. And what do you know, that really helps.

Gianluca Mauro
Interesting.

Pete Mockaitis
And I’m not using a CPAP machine. So, thank you AI for putting me in some good directions. But I think it shows that, “Are we amplifying laziness or are we amplifying a targeted, ferocious curiosity?” Like, “No, find me precisely this, and then we can play ball.”

Gianluca Mauro
Absolutely. You’re spot on. It’s perfect. But, to me, the interesting thing about this whole concept is that there’s quite a lot of responsibility on the user.

It’s basically telling people, “Hey, if you don’t get the right output, it might not be because of the tool. It might be because of the way that you are using the tool,” which from one point of view, I think is empowering because it’s basically telling me, “Hey, amazing, I have some agency over the output that I get.”

But from the other point of view, I think some people might find it a little bit stressful, “Now I need to learn about A, B, C, D, all these different things so that I can actually use this machine well.” Well, yes, but at the same time, honestly, as I was saying before, it’s about changing habits. It’s not that hard. You don’t need to get a PhD in Math to understand how to use one of these tools.

And so, what I recommend to people who might feel a little bit maybe overwhelmed, or maybe afraid that you’re using it wrong, I always tell people, “Hey, find your little safe space to experiment. Take a hobby that you have. Maybe you’re interested in, I don’t know, Formula One.”

That’s one of the latest things that I’ve been nerding about. And just go and try to do your researches and prompts and test things about Formula One that’s maybe not related to your job so you feel safe. There’s no fear of putting sensitive information into these tools, and just try to get a sense of how the tool might be helpful and useful for you in a setting where you’re free to experiment. And then you can take all these learnings and apply them to your job.

Pete Mockaitis
Okay. Well, so you are somewhat famous for your CIDI framework – context, instructions, detail, and input. And it sounded like you were giving us exactly that in the context of, “Hey, give me some feedback on a thing.” And so, can you give us a little bit of detail for how we might think about applying this in all kinds of different ways?

Gianluca Mauro
Absolutely. So, the CIDI framework is a framework that I came up with, I think, a couple of years ago, maybe. And my objective was to find a simple recipe to get people to think about their prompts in the same way that I think about my prompts.

And so, it’s quite simple. It starts with C stands for context. Tell me who you are. Why are you doing this task and what do you need to do? Just try to make AI get into the zone of, “What are we talking about?” Think about this, AI might act like a lawyer, might act like a doctor, might act like anything, right? So, you need to zone in.

The second part is instructions. When I say instructions, it’s important that you’re very clear, and you’re talking to a thing, not to a human so you can be very direct. And I typically give my instructions this way, “I will tell you this, you will do that.” “I will give you an email I wrote, you will give me feedback on it.” That’s the instructions part.

The third part is details. Details are, basically, I look at it this way, it’s very simple, “Explain what good means for you. What does a good output look like for you?” And that’s an interesting question. I feel like it’s almost meditative. It’s almost like therapy. You need to ask yourself, “What do I want? What do I really want? How does a good podcast script look like? How does a good LinkedIn post look like?” And just describe it in plain words.

Pete Mockaitis
Or, I guess this could also be examples, like, “And here are three instances that I consider good.”

Gianluca Mauro
You got it. That’s the part of the prompt where you might want to put, for instance, something you’ve done in the past, and say, “Hey, look, this is something that I consider to be really good,” or, “This is something that represents my tone of voice, and I want you to try to replicate that.” That’s the details part.

And the last part, the input, is when you put actually what you need to produce. So, for instance, if you need to have feedback on a legal document, you put it all the way at the end. The reason why I structure it this way – context, instructions, details, and input – is that it’s very easy to reuse.

So, if I write a really good prompt that explains exactly who I am in the context and what I need to do, exactly what I want out of it in the instructions, in the details, and then the input is, let’s say, this legal case that I need to analyze, the next time I have a new legal case to analyze, I just need to replace the last part of my prompt. The first part of the prompt, the context, instructions, and details are the same.

So, it makes you, number one, think about all the important things in a prompt and leaves really little room for error, because you need to think about all of them – context, instructions, details, and input. But it also makes your work scale a little bit. Because some people, and I get it, get stressed, “I need to write a good prompt. How long is it going to take me to explain who I am, what I need to do, yadda yadda, yadda. What does good look like?” I understand it can be a little bit of a pain if you want to write a really long and cohesive and complex prompt.

But if you write it this way, then it’s very simple to reuse. And that’s your copywriting podcast guy. That’s a perfect example. I think he was prompting, using, maybe without knowing, but he was using that sort of structure, it sounds like, because he had some things that you could probably copy and paste again.

Pete Mockaitis
Certainly. I think it is John Morrow is his name, and we’re going to include that in the show notes. Indeed, the context is, “Hey, we’re a sales letter for this product for, you know, which serves this user with these needs, wants, concerns, who use language like this.” And then the instructions are, “Write the headline of a sales letter.”

The details are, “Here are some other headlines that we think are fantastic, as well as the general guidelines of copywriting that we find to be effective in this industry.” And that might be hundreds or thousands of words, and that’s acceptable, right?

Gianluca Mauro
Yeah, I mean, always try not to go too crazy because then it becomes too much context, right? I think AI could maybe process it, but I always say, you know, if you try to put too much stuff and you’re not fully sure about what you actually put in, then you might have added something that is actually misleading. So, try to keep it in check. Don’t put too much if you don’t know what you’re putting in. But, yes, conceptually makes sense.

Pete Mockaitis
And to that point with the context, I mean, I believe, you know, we’re like a hundred thousand plus tokens. So, is it your professional opinion that, okay, you might have a hundred thousand tokens, but don’t use 50,000 words? Or, what’s your take?

Gianluca Mauro
Yeah, so, I mean, for people who don’t know what tokens are, tokens are basically AI breaks down your messages into parts, parts or tokens. So, if I say, for instance, “Hello!” it might be two tokens, “Hello” and the exclamation mark. And there’s something the AI models have called a context window, which is basically how many tokens they can take a look at, at once. And I think GPT-5, the latest model from OpenAI, is at 400,000 tokens. Some models are up to one million tokens.

So, while you can add a million PDFs and resources into a prompt, then you risk getting into a situation in which you’re adding, if you’re adding not high-quality context, you’re just misleading your model. An example that I always make is the following. You go to a doctor and you say, “Hey, as I said before, I have a headache. What do I do?” That’s way too little context.

But if you say, “Hey, I have a headache. Let me tell you my medical history. When I was two years old, I once fell and hit the knee on the floor, and it was really painful. Then when I was three years old, I once ate spoiled milk. When I was four years…” that’s too much. You’re just confusing your doctor, right? So, you want to try to select some context that might be relevant.

Because, again, you never know if you’re just putting something that is just misleading or it’s just not very relevant to your question. Don’t stress too much about not putting enough but also don’t go crazy.

Pete Mockaitis
Well, I guess what I’m saying is, what I want your professional judgment on is, if I throw in the full transcript of a meeting, or a book, you know, is that likely to help or hurt me or under what context?

Gianluca Mauro
Oh, I do this all the time, by the way. Like, if I take the whole transcript of a meeting, and I need to write a sales proposal, transcript of the meeting, the whole thing, because it’s all relevant. It’s my meeting with a customer, it’s all relevant. And I take that, I take an old proposal that I wrote, and say, “Adapt this proposal to the context of this meeting.” That’s perfect. But think about what I added in. I added only relevant material for my task.

Pete Mockaitis
Well, that’s helpful. You mentioned it’s bad at analyzing conflicting information. And I’m thinking, sometimes it also seems bad at giving me precise pinpoint pieces. For example, if I say, “Give me verbatim quotations of something,” it seems to really struggle.

And maybe it’s just trying to not violate a copyright or something, but I feel like the more I want it to be super precise, specific, narrow, exact, data point or quotation, it seems to struggle.

Gianluca Mauro
Yes, and you will be correct in saying that. And, I mean, there’s a technical reason why this is happening. It’s just in the way that these tokens are processed. It’s basically making a big average of everything that it has read up to that point. But conceptually, you can look at it this way. This is not a truth machine, okay? This is not like a search engine.

A search engine takes a bunch of data, the entire internet, and it just points you to the right point. It tells you, “Hey, this is the link that it’s the most relevant to your query.” This is not that. A good way that I look at AI is it’s a compressor of knowledge. It took all the knowledge of the internet, compressed it into a thing. And then when you ask questions, it can decompress it and give it back to you.

So, what this means is that sometimes you lose some information in that, say, decompression. And I mean, I think this is a metaphor that is, really, maybe it makes sense just to people who are into audio and this sort of stuff because you have this thing. You’re losing quality as you compress it. It’s the entire internet, but you can just like quit it like this in a second. So, you lose a little bit of quality. And so sometimes you have these errors. But I have to say it’s improving really fast.

Pete Mockaitis
Okay. Well, is there anything else that it’s bad at?

Gianluca Mauro
I think a good way to look at this is thinking that it’s an amplifier, okay? So, it’s bad at telling you, “Hey, what you’re doing, it’s not ideal.”

Pete Mockaitis
Yeah, “You’re asking the wrong question,” you know?

Gianluca Mauro
Exactly. It’s not going to do that, which is like, I think, the most important skill today is not being able to find answers. I think it’s being able to ask the right questions and being able to look at answers and be like, “Oh, this isn’t, actually, this doesn’t make any sense.” I’ll give you an example. I think this is quite funny.

I asked AI to give me feedback, as all of you know that I do that quite often, on a PowerPoint presentation that I created. But instead of, like, uploading the slides, I just took all the texts and I put that in. And in the feedback, it told me, “Hey, you’re not using enough visuals.” And I was like, “Of course, you’re telling me this. I didn’t give you the visuals. I just gave you the text.” It makes no sense, right?

But looking, you know, critical thinking, and this is a very simple example, but I had to take that piece of feedback. And even though the best top AI model in the world told me that I need to add more visuals, I discarded that feedback because I was like, “I know that you’re just lying to me. You’re just coming up with random stuff.” So that’s one important thing.

And, by the way, I think something that really scares me is a lot of people are using AI for almost as a therapist to get support in relationships with their loved ones. And, again, remember AI is sycophantic and it’s going to try to please you, so you’re always right. It’s really rarely going to tell you, “Hey, Gianluca, you know, your…”

Pete Mockaitis
“Your behavior is toxic and causing problems. Look in the mirror and fix it.”

Gianluca Mauro
Exactly. It’s always the other person’s fault. Yeah, I had this friend of mine who came to me, and was like, “Hey, I have an issue. Every time now I have an argument with my partner, she goes in a room and then comes back and has a perfect, like, perfectly phrased argument to explain to me why I’m wrong. And I know that’s coming from ChatGPT.”

So, she’s just getting in a room, and saying, “My boyfriend did X, Y, Z, you know. How can I just try to win this argument?” which, again, I think there is some value in that if you use it correctly. Again, I feel like I said it a few times, but I really want to make sure the audience comes back with this. Think about if you instead use it this way.

Go back to your room and say, “Hey, I had this argument. What might be the other person feeling that I’m not thinking about? What might be some blind spots that I might be having? What are things that I’m not considering when I’m accusing, I don’t know, whatever my partner of, X, and Z?” Now you’re actually going to use it as an empathy machine rather than as a, I don’t know, ego booster kind of thing, right?

Pete Mockaitis
Yeah, well said. Are we amplifying the, “I’m right, they’re wrong,” make the case, or are we amplifying, “I’m trying to be understanding and compassionate”? And it will seek to please you. And so, yes, if we amplify the wrong thing, we’re just getting farther down a bad path.

Gianluca Mauro
Correct. And isn’t this cool? Like, the idea that I have so much agency and power over the outcomes of my use of AI, depending on how I use it, depending on the questions I ask and what hat I decide to wear on this day. “I want to wear the hats of the empathetic person who tries to understand what this person might be feeling.” I can have vastly different outcomes. I found this really empowering.

I understand it might be a bit scary, because it’s like, “It’s all of me?” Yes, I get it. But, again, if you have that approach of being curious and just trying different things out, I find that super empowering, honestly.

Pete Mockaitis
Cool. Thank you. Well, now I’d love to get your take in terms of, boy, there’s a lot of different chat bots and AI tools, if you want to do ChatGPT or Gemini or Claude or Grok. Is there a way, and this is going to change every few months but, you know, for now, is there a way you think about for certain use cases, “I prefer this tool over the others”?

Gianluca Mauro
Yes, but in a way that might be unusual for the audience to think about. So, I think about it this way. I think in my AI, I call it my AI tool stack, like all the tools that I use, I think about three main categories. The first one is generic AI tools. These are ChatGPT, Gemini, Copilot, Claude, Grok, basically these five. And, for me, it doesn’t matter too much which one you’re using. All have each respective strengths and weaknesses, but they’re all quite similar at the end of the day.

I personally use ChatGPT. That’s the tool that I started on. That’s just the tool that works the best for my use cases. But, again, I don’t have a strong argument for people to say, “You must use ChatGPT.” Use whatever you want. But the interesting thing is when I look outside of these generic AI tools and I start looking at specialized AI tools, and these are tools that are specifically built for one use case.

An example, I use a note taking tool called Granola, which I really love. I have a lot of meetings in my life, and Granola is specialized in note taking during meetings. Absolutely beautiful. And I’m not affiliated with Granola at all, so I can tell you there are other tools that do that as well. Otter is one. It’s pretty good. There are a few ones.

But, again, for me, who, I take probably too many meetings. Having a specialized tool for note taking during meetings is super valuable. But there are specialized AI tools for lawyers. There’s a tool called Harvey. There’s a tool in Europe called Legora that’s amazing. And these are specialized for lawyers. They give you a bit more features that you might be interested in. They’re a bit more accurate. They have maybe all the laws of a country already loaded in. You know, they’re more helpful.

I have a startup called Epiphany and I built a specialized tool for instructional design. It helps people who create training, create better training faster. And it’s really interesting when you start looking at those specialized AI tools, because, again, you might find something that, for you, specifically for you, can have a lot of value.

I know, for instance, there are tools for podcasters. Like Riverside has some pretty interesting tools to, like, repurpose content. You might find a lot. Curious to know if there’s anything that has really changed the way that you work in that space.

Pete Mockaitis
You know, it’s funny, we do a little bit here and there, but we’re actually still transcribed by humans, which could shock some people. So, we use it in specific, narrow targeted places, but, still, each episode is getting many, many human hours to put out the door.

Gianluca Mauro
And that’s perfect. Again, for me, what I advocate for is thoughtful AI use, not just like take it and put it everywhere. That doesn’t work for me. So, it makes total sense. But that’s the second sort of area that you might want to look at. So, pick one generic tool. That’s like saying Excel. You can use Excel if you do marketing, if you want to track your campaigns. You can use Excel if you’re in finance. You should use Excel if you’re in finance, but you understand where I’m going.

Same thing, ChatGPT or Gemini or Claude can be used by people in every single industry. But then look at those specialized AI tools that might help you even more.

And then the third area is those custom-built automations that you might want to build for yourself. That’s when we’re getting really nerdy, okay? But I love that. And the interesting thing is that the barrier for building your own custom automations has gone down so much. It’s crazy. There are all these AI no-code tools that allow you to plug different tools together so you can build an automation like, look, I’ll tell you one that we have in my company, in AI Academy.

Whenever somebody writes on our website, “Hey, I’m interested in a custom enterprise training.” There’s this custom automation that researches the company and just gives to our salespeople on Slack a message, and says, “Hey, this person has reached out. This is who this person is. This is what the company does. This is what they want.” Research is done already. It’s like a sales assistant, basically.

We built it ourselves. It took us, I don’t know, we know how to do it so it took us a couple of hours maybe, maybe three, I don’t know, something like that, okay? Hours, not days. All right? But we have seen people starting from very limited technical skills, being able to build those custom automations for their business or for their freelance profession in just a few weeks.

Pete Mockaitis
That’s cool. That’s good. Well, talk about dorky, even though I am not at all a coder or a developer, my favorite YouTube channel is Fireship, which has all these jokes and stuff. And so, I’ve heard, I know a couple of the buzzwords associated with AI automation, like the MCP, the model context protocol, as well as the N8n.

Gianluca Mauro
Amazing.

Pete Mockaitis
And so, I know those are key words I might Google and research. But you tell us, if we are just starting to tiptoe down the, “Hey, I got a thing in my life I need automated. I think AI could probably do something about it,” what are the first steps to explore pulling that off?

Gianluca Mauro
Yeah, so I’ll just tell you basically how we help people go from, “I might want to automate something” to “I’ve built an automation.” And that’s just because we know that that’s a process that works. The first thing you have to do is understand what to automate, what not to automate. And it sounds very basic, but I guarantee you that’s where you decide if you’re going to be successful or not.

Most people want to automate too much. And then they start building spaceships that are never going to work, never going to give them the result they want. They’re going to get tired after some time when they try to build it and it doesn’t work, and then give up.

Instead I always tell people one day I’m make a T-shirt with this sentence, “Find the smallest possible thing that could possibly work.” The smallest possible automation that could give you some value. Start with that and then you can expand, all right?

The second part is don’t stress too much about the tools, you know, the N8n or Make.com or Crew AI, all these tools that are coming up, but try to write a pretty good prompt that should power your automation, okay? So, focus on the AI component, and find a way to test it well.

What do I mean by this? I’ll give you an example that I had. There was this one of our students, he was a doctor and he wanted to not just build an automation. He wanted to build a product to give to his colleagues so that they could easily write referral letters, okay? And so, he had to make sure that this thing worked really well because, again, doctors, you know, it’s a lot of responsibility.

So, what did he do? He just found a bunch of referral letters, or he wrote a few with ChatGPT, and he corrected them by hand. And that was his set of examples to test whether his prompts were actually producing something that was good enough.

Pete Mockaitis
Yeah, like, “Can the AI actually achieve the thing I’m hoping it to do? Let’s test that before I build out a whole thing and go oopsies.” Love it.

Gianluca Mauro
Correct. Another one of our students, I saw this last week, so I remember really well, did something to create LinkedIn posts. This guy works in marketing and risk is very low in that case. What’s going to happen if you publish a really bad LinkedIn post? I might get annoyed, but no one is going to die, right? But still what he did is he used his prompt to create a bunch of LinkedIn posts and then he wrote some and then he gave them to some of his friends and said, “Hey, which one do you like the most?”

And he tried that with a few different prompts, with a few different models. He tried with GPT-5, he tried with Claude, he tried with Gemini, and then he just found the best. And then he knew, he had the confidence that this automation was going to work because he had done the work of testing it and collecting the data.

After you’ve done this, step three is now, build your automation. And, you know, there are different tools that are pretty good at this.

Make.com is one that I really like. I use it a lot. Zapier is probably the easiest one to use. If you want to get started and don’t want to waste too much time learning how to use slightly more sophisticated tools, Zapier is a great place to start. N8N is probably the one that gives you the most flexibility on things that are the most capable. And I like that a lot as well.

But again, does it matter? Not really. At the end of the day, if you had a good idea about what to automate and there’s real value, then you can just swap tools and you’re going to be good. So, I suggest that that’s the last thing that you start thinking about.

Pete Mockaitis
That’s good. Well, shoutout to Zapier. We had Wade Foster. Or is it Zapier? I don’t know. Zapier or Zapier, we had Wade Foster on episode 466 back in 2019, and they are still going strong.

Gianluca Mauro
Amazing. Super strong.

Pete Mockaitis
Good, handy stuff there. All right. Well, Gianluca, tell me, anything else you want to make sure to mention before we hear about a couple of your favorite things?

Gianluca Mauro
No, I think we’re good.

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

Gianluca Mauro
I wish I could say who it comes from, but it unfortunately comes from a random guy on the internet. And the quote is, “The hardest part of getting what you want is figuring out what that is.”

Pete Mockaitis
I dig it. And can you share a favorite study or experimental or piece of research?

Gianluca Mauro
I will share the research that I was talking about before, the one from Harvard, where they looked at all the different capabilities of AI. And the name of the research is “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality.” It’s really cool, still very relevant from a couple of years ago, but, honestly, I still quote that, basically, in every workshop that I do because it’s really valuable.

Pete Mockaitis
And a favorite book?

Gianluca Mauro
Ruined by Design.

Pete Mockaitis
All right. And a favorite tool, something you use to be awesome at your job?

Gianluca Mauro
Another tool that I started to use recently is a tool called Wispr Flow. It’s quite interesting. It basically allows you to dictate and it just puts whatever you said into a box. But again, it uses AI to just change that a little bit so that it’s, first, it’s formatted already.

So, when you’re writing emails, you might want to just record and say what you want to say, and say, “Here, I want some bullet points,” and you’re going to see the bullet points. I’ve been using it for a couple of weeks and I might see that becoming a key part of my tool stack.

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

Gianluca Mauro
You can go on GialucaMauro.com. That’s G-I-A-N-L-U-C-A-M-A-U-R-O.com or on AI-Academy.com where you can see all of our trainings so you can get better at AI.

Pete Mockaitis
Okay. Well, this has been so fun. Thank you and good luck.

Gianluca Mauro
Thank you. Thank you for having me.