The Leadership Framework for Executives to Master Timing, Ethics, and Innovation with John Donovan

Jay Combs: Is there a blind spot that you're particularly worried about that maybe you don't think enterprise leaders are thinking enough about when it comes to AI or security that you think everybody should know?

John Donovan: I'll highlight three points that I think are important. The first one is

Jay Combs: John Donovan is a veteran technologist, investor, and author. As CEO of Cudit Investments, he backs breakthroughs in AI, quantum computing, and hypersonics. Formerly CEO of AT&T communications, he led major innovations like 5G. He sits on the boards of Palo Alto Networks and Lockheed Martin and has chaired the President's NSTAC.

He's also the author of three books on tech and leadership.

John Donovan: I have a framework. The house that I live in, which is my decision-making house, has sort of a framework that I use. Things are at the time I make choices, they to me look super easy. And I think the hardest thing in discerning is to narrow it down to two choices.

And then when you really get it narrowed down into two choices, then it always seems very obvious.

Jay Combs: As a decision maker, how are you sorting out like hype from the need to move really, really quickly to move really thoughtfully? What are maybe some of the keys with AI that you're evaluating right now?

John Donovan: Well, I think that the most important one I'll lean on is time. Because if you're making a technology decision, it's much harder to decide the window. If you're too early, then you end up overinvesting. You don't get any yield.

You waste money. And so then on the back end, if you're late, your competition gets you and you can't catch up.

Jay Combs: Is there one specific decision you made that you, hey, I wish I did this differently or it wasn't the right call and that you learned from it the most? Is there a formative bad decision that you had made?

John Donovan: I think the mistakes for me are the decisions that

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Don't miss out. Welcome to the Good Decisions podcast. It's the podcast about pivotal choices shaping careers, technologies, and the future of AI. I'm your host, Jay Combs.

Uh each episode we sit down with leaders who have faced complex challenges. Uh leaders who have pivoted from one career to another, innovators preparing people for the future shaped by AI and entrepreneurs who have uh had to choose between uh what's easy and what's right. We talk so much about AI and the hype and the technology and the data of making decisions uh that we can sometimes forget about the people behind those technologies who are ultimately making decisions and what drives them. What are their values?

So that's what I'm interested in and this is a podcast that talks about those people, how they make decisions and the moments that got them to be the leaders they are today. Uh today we're very lucky to have John Donovan who is a legendary technologist, investor and author with more than 30 years of experience uh at the intersection of technology and business as the founder and CEO of Cudit Investments. John leads long-term investments in AI, quantum computing, and high performance computing and hypersonic technology. He's previously been the CEO of AT&T communications where he spearheaded global innovation efforts including the roll out of 5G and software-defined networking.

John sits on the boards of Palo Alto Networks and Lockheed Martin. Uh and he's chaired the president's national security telecommunications advisory committee. Uh he's also authored uh at least three books that I know of including The Value Enterprise uh strategies for building a valuebased organization and he is recognized uh for his thoughtful approach to both technology and leadership. So John thank you so much for joining us and welcome

John Donovan: Jay thanks I'm glad to be here.

Jay Combs: Fantastic. So, you're the really kind of the perfect guest for this podcast because you're known for your long-term planning in frameworks and I think you wrote your first long-term career plan at the age of 26. Uh that's very unique for somebody. So, I want to start in Pittsburgh which has been the heart of uh the American industrial revolution or to creating American infrastructure.

Are there formative moments um that I guess made you prioritize long-term thinking and planning?

John Donovan: I don't know that at an early age in Pittsburgh I focused on the long term so much as I was focused on just trying to figure things out. I came from a very large family, one of 11 in a neighborhood that was sort of lower middle in income. Um, and you kind of have to have hustle just as part of your everyday life. And I think that I started to, you know, do things like work hard, save money, and start to do planning early.

I started to think about, you know, I got to go to college, got to save money for that. I want to play hockey. It's an expensive sport. You know, we didn't really have a lot of means for us to do things that were outside, you know, the norm.

And I knew that I wanted to live a little bit outside the norm. and I'd have to as a result forge my own path. And then uh my father passed away when I was in college. And um so there was a there were a lot of points in time where I was forced to kind of think about my own future um by myself.

And I started to realize that I could make things happen best if I knew where I was headed and what I was trying to get done. And so I've always sort of been around a planner, if you will. But I think as I started to age, I started to push the horizons out a little bit. And I think that Pittsburgh is one of the greatest places in the world to be from.

And I don't want to give the impression it's not a great place to be, but you know, for me, I wanted to see the world. And so for me, it was a stepping stone. Yeah.

Jay Combs: Now, Pennsylvania is a great I'm from just outside of Philadelphia, so the other side of the state. So, and I know Pittsburgh has transformed itself over the years and it's amazing place uh to be. Um, but when you left Pittsburgh, I believe you went to Notre Dame and you studied electrical engineering. How did you choose engineering, especially at a time when the worldwide web hadn't yet been invented, cellular networks were still in their infancy and foundational internet protocols were just being developed.

Were you thinking about any of those things or were you just, you know, excited to be at Notre Dame and really focused on um I guess yeah, kind of like forging your own path?

John Donovan: Well, it's not a glamorous story. I went to my orientation day and I drove by the student parking lot in my parents' car and I saw these amazing cars that the kids were driving. And I had applied to get into the accounting school because my uh father was an accountant at the bus company. And um and then I got there and I went over to the placement office and I said, you know, before I get started in courses, can you tell me who made the most money on their job offers last year?

And they said engineers. So I said, I'd like to switch to the engineering school. And I hadn't taken calculus in high school. I didn't have the right curriculum ramp to get there.

I would say that the counselors we had at school were just delighted for me to get into a school like Notre Dame, but I had a my high school hockey coach was a Notre Dame grad and he really pushed me to apply there. And then um at the end of my freshman year back then you didn't have email. So they sent a letter and said you have to pick a discipline within engineering. So, I went right over to the placement office and I said, "Uh, who made the most money in their job offers last year?"

They said, "Elect electrical engineering." So, I said, "Okay, please sign me up for electrical engineering." And so, I at that point, I knew that education was a means to an end. And I was really focused on the end.

I really started to put my mind to the job market really early in my college career. And so much so that I would say I really couldn't wait to finish college to get out and start this whole journey of working. And so that's when I think my horizon started to move out a little bit because I started to think about imagine a world where I had more freedom, more control, more management. The ability to perform in a workplace was something that I really looked forward to.

And then in my first job then from that point forward I kept continuing to stretch out my horizons. And so you know I'm I'm a big advocate of doing life planning um so that you can survive short term uh impediments hurdles bad bosses you know wrong position mistakes you know you can you can correct them if your horizon is I think appropriate and your focus is on the big picture.

Jay Combs: So, it seems like there's an economic and kind of financial and I guess longer term career growth focus to your selection of engineering and where you would go for a job afterwards. But given that so many um I guess technologies were just coming into uh coming into phase at that standpoint, were you thinking about the internet? Were you thinking about telecoms? Hey, this is the next big industry that I need to go to or is it still more about uh just kind of career opportunities as opposed to the technology?

John Donovan: No, back then you know they had two disciplines within electrical engineering power and then the electronic path back then you know you had the Intels of the world which were very popular and hiring lots of people. Um, and I just thought one was a little more modern than the other, and I don't think it was anything more dramatic than that. And I just felt like one was going to open more opportunities. And, you know, it turned out to be right.

I interviewed my tail off. I think I interviewed with 13 companies. We were coming out of a recession in the uh early 80s and uh well, we weren't out of the recession. I think my senior year is probably the first year where college hiring had somewhat of recovery.

So I left no stone unturned. Even when I was getting job offers that were perfectly good, I continued to interview so that I could sort of optimize and get the what I would was thinking would be the best thing for me.

Jay Combs: And what was that first I guess best thing job at a at a school?

John Donovan: Yeah, I went to work for the Trane company. And you probably won't be shocked from the tone of the earlier questions that I went because they had the you know they were it wasn't like the best starting salary but it was basically an engineering-led company so all of its leadership were you know trained engineer so it was an engineering centric environment and I thought that would be a great place to you know get started and get moving and then you know I sort of they were it was a great opportunity because I rotated through various disciplines of marketing and engineering and then I went into the sales function and so you know I don't you know as much as I think long term um you know maybe a little more philosophically than others I have a framework like the house that I live in which is my decision-making house has sort of a framework that I use um things are at the time I make choices um they to me look super easy. And I think the hardest thing in discerning is to narrow it down to two choices. And then when you really get it narrowed down into two choices, then it always seems very obvious.

So I don't feel like I'm a particularly great decision maker. I think I try very hard to make lots of decisions fast, to correct mistakes really quickly. Um, and then keep this philosophical horizon, if you will, that allows you to make those mistakes and not feel like they've somehow thrown you off track and in life and against the ambitions and goals you've set for yourself.

Jay Combs: It seems like a simplicity in that of pushing away the things that don't matter and focusing deep on the things that do to whatever your kind of core beliefs are.

John Donovan: Right. Right.

Jay Combs: How did that get you to telecom? I guess from the Trane company I mean infrastructure obviously but yeah is there what brought you to the telecom industry?

John Donovan: Well I went into sales. I did well in sales. I saved the money. I bought small businesses.

I left the big company. Went to the small. felt a little, you know, uh, a little too small for me. went back to get a degree, an MBA to do a career pivot and then I went to work in consulting and the first industry that I did a consulting engagement in was telecom and I fell in love with it and that kind of became my path and telecom's one of the best training grounds because it's hardware, it's software, it's like a layer cake of the OSI stack, you know, the seven layers of how do you move electron you know through an information network and those sorts of disciplines served me well and you know it's from that point um you know as I say the rest is history but you know I think the thing that's underappreciated in my career and even to this day how hard I work to understand what's in the world how much time I spend reflecting on therefore what's next and how committed I can be at various times no matter where I am to never take the shortcut.

So I try to teach my kids, you know, it's really hard to have a good opinion and to hold it. And you don't necessarily subscribe to hold it. But in order to hold an opinion, you have to have put the work into understanding it at a nuance level. I think too many people today have opinions on everything and actually in many cases have a foundation that is entirely intuitive.

It's entirely based on a narrative and very little fact um or conviction around what makes it so.

Jay Combs: And I noticed that and I've been at software for 20 years and with software decision-making I mean there's always the ethos of move fast and break things which you've heard over and over again. Um especially with you know a lot of young managers it can be easy to make decisions change them very quickly. But when you're dealing with hardware and software like it seems like you have to make very concrete well-thought-out long-term decisions. And I don't know if you notice like a different type of decision-making or leadership from a hardware industry to a software industry, but curious if you've noticed any differences between managers who are coming from that infrastructure world versus folks that are, you know, developing tools that are evolving very quickly.

Do you notice a difference in their decision-making frameworks?

John Donovan: Sure. And time is only one of those dimensions. So if you look the joke the semiconductor people say is that software is just the problems that we didn't get around to solving. And so I think you know software has very different processes much easier to correct things much cheaper to make corrections the errors are less costly.

I mean obviously there can be big errors all over the place but there's a reason they call them bugs and not elephants. And you're definitely going to have a different uh tempo and speed and cost of being wrong, different amount of capital that's required to sort of ramp them up. But you know, I think that a decision framework is roughly the same. Whether it's industrial decisions or technology decisions, whether it's, you know, software, hardware, applications, you have to, I think, be deliberate.

And deliberate sometime is fast and sometimes deliberate is a little bit slower. But it's not like, you know, this one's easy and this one's hard, this one requires thought, this one doesn't. You know, it really is just a set of parameters that you have to apply to each and every one. What's the risk-reward of various approaches?

And I think people talk about speed all the time, but they don't use time more broadly. Like I earlier in my life, I had a good friend in Japan and we used to talk all the time and he used to say that one of the things that the Japanese were very good at making decision-making was that don't decide things that time decides on its own. So you don't have to intervene to make something happen if the answer is inevitable anyhow. So I think that taught me a little bit about having a perspective of time.

And so I think I catch a lot of people off guard today when I tell them the big your biggest competitor right now is time or don't do anything right now because time's working in your favor. And so time is a really important element to decision making that I think is underappreciated. And I think when you develop that sort of framework that has the variables of people and financial and engineering and technology and how do you organize you also need to come back and say what is the value of time? Is time valuable in this situation or is it not value?

How much competition is there? How close are they? And I think the analogy I can point to right now is in the AI uh large language model game, the most important element is time. The tradeoffs in these clusters of GPUs in am I going to take inefficiency and buy more GPUs or am I going to take my time and figure this out?

And the answer is if I can go faster and get a bigger cluster even though I have overhead inefficiencies and fallout, I'm going after it. So that's the biggest example of one where time is not only of the essence, it's the number one issue in the decision-making framework, but there's others where time is, you know, far less important. When you get into, you know, decision making that involves very little competition, high engineering complexity, you know, you're going to make a different decision. Yeah.

Jay Combs: on the, you know, the AI front and time being of the essence. I mean, being at a company like, you know, AT&T that, you know, has a, you hundreds of thousands of employees, you're making, you know, you're trying to keep up with technology, stay ahead of competition, but at the same time, there can be a lot of hype on the use cases around LLMs or Agentic AI or whatever is coming next, the risks are associated with it. when you're trying to move very quickly but also avoid the hype as a decision maker, how do you especially as an investor? How are you sorting out like hype from the need to move really quickly to move really thoughtfully?

What are maybe some of the keys with AI that you're you're you're evaluating right now?

John Donovan: Well, I think that the most important one I'll lean on is time because if you're making a technology decision, it's easier than you think to make a technology bet. It's much harder to decide the window because if you're too early, then you end up overinvesting. You don't get any yield. You waste money because Moore's law translates to about 1.5% savings a month.

So, so you save 1.5% by doing nothing. And so if you're late, your competition gets you and you can't catch up. So you're seldom surprised by a technology when you put it all the way into an end market, but the window is a really hard uh decision to make and it applies to everything. It applies to telecommunication networks.

It applies to batteries. it applies to, you know, uh, energy. It just, you know, everywhere you've got to make these tradeoffs to say not just what's the risk-reward, but what is the right timing where I can really nail this thing? When is good enough, you know, uh, performance-wise, where is competition?

All those things kind of are important elements to come back and say, now is the time to move. And I think that's the hardest decision is when do you move?

Jay Combs: Do you look at like individual use cases say around AI like coming from AT&T customer service, customer support is have to be huge as a an AT&T customer, right? Like that's always a top- of- mind issue. Are you looking more strictly at the technology? Are you evaluating the use cases and how we can improve this for customers?

Like what comes front of mind to you with most important use cases for AI?

John Donovan: I think that when you uh AI use cases are going to be pervasive and it's just like a simple framework if you say what is the level of effort to go get it and what's the magnitude of the impact if you find any that the magnitude of the impact is high and the level of effort is low go get those and exhaust all of those before you try to make the tradeoff of what's what are really high impact but they're going to be really hard to get because If you don't have any wins along the way, taking a moonshot is challenging. Like sometimes you have to put a ladder and climb up to the roof and that's as far as you're going to get. But you have to make a tradeoff of organizational learning. Which interim wins do you need?

Which learnings do you need along the way? And then you really have to construct this as a cornerstone is a cornerstone. Building blocks are building blocks. You can't confuse one for the other.

And so I think that when you look at AI and its applications, you really have, as simple as it sounds, just take a two-by-two matrix, say here's the organizational impact, and then here's the degree of difficulty to go get it. And I think you look at it, you'd say customer service is certainly one that's high impact. People don't like calling. They like solving their own problems.

If they're going to call you at a contact center or chat with you, they're probably already frustrated because they already probably already tried looking at an online video to see if they could find the answer there and then they went to that group and then they went to Reddit forum. Wherever they went, so by the time they reach you, they're not like super pleased to be there. But it's really hard because those are very nuanced things. Language, how things are worded, problems sounding like one another.

And so organization one maybe customer contact center is the one they need to go get and it's like it's how they sell. So it's going to be transformative like you know there's a bunch of organizations the hospitality industry much of what they do is through contact centers. That's their salesforce if you will. And um then there's the collections agencies.

That's how they make their money right is um is contact centers. So you view that very differently than someone who has an automated online engine that has very little fallout where the customer contacts are very few in number as a percentage and they're very rote answers. So you know I know it's convenient to say okay here's where it is. If you look at a chart today, it would tell you number one is coding, number two is business analytics, number three is customer contact and so on.

And that's probably those are generally true, but we all know that the fallacy of generalizations. They may not be specifically true at all. So you really have to look at it and say, "Okay, those might be things where the average organization can gain the most benefit from, but it may not apply to me."

Jay Combs: Building on that, one of the things that comes clear to me in some of the interviews that you've done and videos that you have on your your website is not just kind of the analytical decision-making that you're talking about here with um risk versus reward, but the ethical uh considerations that you've taken. you always seem to have a very thoughtful um approach with AI specifically and looking at an organization at the size of AT&T 200 I don't know the size of it now but I think when you were leading AT&T communications it was 250,000 does do the ethical and societal consequences of applying new technology come into your decision framework how do you handle those because I think that's probably gets what's splashed up in the news especially as an executive of how you handle that.

John Donovan: Yeah, I think that's probably like the most central thing to leadership is that you build some sort of consistency to your decision making so that people don't have to wonder what you stand for. They can just watch your decisions and from that they can you can put values and you know code of business conduct and all that stuff into written form and violate it or you can you know have simple versions and then point to that only as necessary and then just create normative behaviors. It's like the difference between normative behaviors in an industry, legislation and regulation, right? You can always legislate it as against the law to do this and you know you need to be compliant or you can regulate it and say you know mother may I do this.

They say well no you can't do that or you can just kind of go live your life and live it the right way. And I just think in leadership I mentioned earlier if you build a framework that you use that has the big picture thoughtfully correct, you can decide things super fast. Everything will feel intuitive. And the ethical framework is a really important room in that house as is like the economics.

What time horizon on the economics is relevant? And then all these other little subrooms and closets. How capable are my people? You know, how much transformation do I think I can drive?

How many, you know, you put all that stuff into a framework that you have, you know, in your head. So, you don't need a consultant to come in and tell you that organizational change can be overwhelming because, you know, you read people, how you doing? How are you making the change? They're saying, "Well, you know, we I got a new boss.

I got a new process. I got a new computer system. Like I can't do, you know, having trouble absorbing it. The people in the field will tell you everything you need to know about the framework for making decisions on an ethical framework.

Like if things aren't right or if you question they're right, even if they're economic or productive, you have to make the right choice. I think that's a benefit for me of my upbringing, my parents, my faith, my neighborhood because right was always the first consideration. It was never like what's convenient or what's profitable. It's like what is the right thing to do?

And that just sort of becomes the framework. And I think it's actually a little bit disappointing to me that people need to sit down and as adults and as an organization or as leaders to assign a team to write that stuff down like it like doing the right thing. If it's ambiguous, it should result in a discussion, but we shouldn't have to decide what's, you know, what is ethical. Yeah.

It's it's just, you know, it's just you got to do the right thing. And not everybody's going to agree on it. That's where I think the leader framework becomes the culture. And so sometimes culture um can survive, you know, many leaders and there's times where a leader goes and instantly changes the culture.

And um and I think the latter is the one that I respect more. We should be picking leaders that can cling to what is right about the past and then navigate the future so that you're constantly evolving as an organization but never changing the view of what's right and what's wrong.

Jay Combs: Apologies if this sounds like a kind of a dumb question, but and I don't want to put words in your mouth. It seems like you equate, you know, ethics and the right ethical things to do with the right decisions. But when you say the right thing, what do you explicitly mean the right thing?

John Donovan: You know, I think the right thing is I can give you many examples of it and but defining right and wrong is always challenging. It's like really simple. It's, you know, the opposite of that phrase, you know, I don't I can't define it, but I know it when I see it. It's the opposite that says like, you know, here's all of these examples of right and wrong.

You say, okay, well, should I take short-term profits if I know a product is defective? Should I take my medicine and call the customer and tell them that I made this massive mistake? Should I be forthright in defining what caused an outage? All those things, because there's always these simple alternatives.

Oh, blame it on a vendor. Oh, let's say that it was force majeure like something happened. Oh, look at how this timing works out. I can say this belongs to that.

So, there's all these little white lies and hedge truths that if you do them over and over again, people start to say that's what we look for. We look for the intersection of convenient truth and the story that sounds good. And then there's decisions about, you know, like the human stuff. How do you manage a layoff?

Are you honest with people? You're forthright. Are you And so, yeah, there's trade secrets. Yeah, there's things that you can't pre-announce and all that sort of stuff.

But the integrity of honesty, transparency, being willing to communicate things, communicate them early. It just, you know, right and wrong look look really simple in hindsight. And they are a little trickier uh in the windshield than they are in the rearview mirror. So, I just think you have to have a framework where you're willing to make a suboptimal decision to do the right thing.

And when I say the right thing, I ultimately think no one can take shortcuts or tell convenient truths for a very long period of time and have that work out. I just don't see that can be a way of life. Yeah.

Jay Combs: I mean it seems like accountability number one is extremely important to you and almost the intrinsic value of doing you know adding value to the customer. It's not about necessarily like profit's obviously an important thing but the intrinsic value of the offering that you're providing to folks is very important and making it transparent and accountable um is I think uh I'm really impressed with that kind of line of thinking. So,

John Donovan: but every business you're making sausage like when you're inside the business it's sausage, you know, and then externally you're trying to package it up and put it on the shelf and make it look really great. And uh yeah, it's tricky. It's a very tricky thing to get right. But I think you if a leader can have a good ethical framework, a good economic framework and a big picture view where they've abstracted the world they live in to a level at which it makes sense, you can get back to ground level and make decisions really fast.

Jay Combs: Is what are some of the main challenges I guess with applying this framework now with AI being available and looking at students in college, right? You can write an essay very quickly that can escape some of the AI detectors and you can, you know, turn in a better paper than maybe you wrote on your own, but you're not going to learn how to do it, right? Apply that up to the corporate level. I mean, maybe people are, you know, creating documents or products or code um with AI.

Do you worry about folks, I guess, maybe missing some of the learnings or skills that previous generations built over time because they can kind of do it with a click of a button.

John Donovan: Well, that's like saying, you know, at some point keyboarding skills are more important than penmanship skills. I actually used to have to write long, you know, multi- dozen lines of code to print. Now you can press a print button. We use oxygen to climb Mount Everest.

You know, there's there's evolution, there's revolution, and then there's sort of history and tradition. I'm a little bit more of a traditionalist. My daughter just graduated uh last month from Caltech, which I'm really proud of her for finishing up. What I had told her to do is if you use chat ChatGPT for anything, start turn your assignment in with the opening paragraph where you used it and why you used it.

And it was amazing the interaction that her or the positive interaction with her professors, you know, when she says, "I was really struggling to put a framework together for this and I knew I would never get it done in time unless I had some sort of framework to work with. So I used it for the framework, you know, or whatever." And I just think that transparency, you mentioned it earlier, is an important element. And I think if someone, the very first time she did it, someone said, "Hey, that's inappropriate."

She would have stopped. Um, and she never wrote her papers with it because she felt that would be, you know, but maybe two years from now, the people that were at the same school on the same courses are using it 100%. and they're able to, you know, read more books and get better insights by getting computer aids to their paper writing. I don't know like I don't know.

I when I when I look at that, I think we have to wrestle with some of the biggest ethical questions of our lifetime. Why I'm positive on AI is unlike social media or the internet overall, I think we're better prepared this time. I think more uh philosophers, social scientists, theologians, all of those folks, trade unions, um content creators, they've weighed in very early on this one. And so at least their voices are at the table.

And so I think the cycle of normative behavior to regulation to legislation is going to be compressed for this one. And I think we're going to be more thoughtful than we were social media. And I think in social media we are more thoughtful than we were when the broad internet came into being. Yeah.

Jay Combs: I mean you were I think just starting at&T as the iPhone came out and that was kind of the last big inflection that changed mobile apps and that obviously is a huge change. So is there a lesson there that you would share or advise uh companies, executives to follow or maybe something that you did that you uh regret that you would do differently this time around with AI?

John Donovan: I'll highlight three points that I think are important. First one is you have to convince your employees that opting out of this technology revolution is not a good idea. Like because I think there's every time a brand new big technology comes along, the engineers and scientists who are involved in creating it try to create a new language that makes it sound too complicated. They try to make it sound like you're not smart enough to come do this.

And so there's a group of people who say, "Okay, well, I'm out on this one." And they so they don't go in and learn the nouns and verbs of the new technology and they don't adapt their job to the new technology. So they run the risk that they become obsolete. So the first thing is you have to convince the your employees that this like every other technology can be understandable.

It can be managed. It can be part of your job and that you should lean in on it. That's a really important element. The second thing is that every big technology is going to carry an element of existential risk and an element of unprecedented opportunity.

And I think to try to conclude quickly that it's either deprives you of the chance to say it's always both. So it may existentially, you know, affect one element of your business but provide a brand new opportunity and something new. And I think that the old idea of genius is carrying two competing thoughts in your head at the same time applies here. It's existential threat and it's unparalleled opportunity.

put those two in your head at the same time and go look at it in that dimension and do so without you know fear or dread like you really have to view it you know I think as an optimist and so I think that's an important element and the third one is linking it to the earlier conversation around timing and how do you look at what's going to be urgent critical and timely where do I start And then build a road map where you're balancing the easy to do, the hard to do, the minimal impact, the gigantic impact so that your program carries with it some tempo, some learning, some impacts, you know, and then circle back to the beginning again. So you start to build, you know, a flywheel of change. And so that would be my advice. And you know, I think a lot of that is based on experience.

Sometimes I've done it right, sometimes I've done it wrong. You know, I think that a great executive can make a lot of decisions with a first principle thinking really close to the ground, really fast if you have your framework. And your framework is really like how do I think about the competition, the economics, the ethics, all those things. And then just keep bringing decisions and let's just get moving.

And then you can move really quickly and you don't need to do things by committee. You can operate really fast.

Jay Combs: And you have a unique perspective serving on a variety of uh committees and boards from NSTAC to you know Palo Alto Networks and others. Is there a topic or blind spot that you're particularly worried about that maybe you don't think enterprise leaders are thinking enough about when it comes to AI or security that you think everybody should know?

John Donovan: You know, I think the hardest part, you know, cyber security, building the products is really interesting because you build products against things. So, automatically you've defined how you stand in the world. And so there's a harder edge around that. The same with the anything that serves the defense department.

You sort of have the adversaries in mind uh when you build. And so there is a dimension of that. You know, I think as it relates to general the geopolitics, I think most really senior executives spend a lot of their time trying to understand geopolitics, tax policy, the economy. So, how does a person who's operating at a director level or an executive director, a VP or a senior VP, how are they getting the perspective that's necessary for them to be successful?

And I think that's just muscle you've got to develop. You know, I think a lot of people very early on used to say, you know, talk to me about those kinds of subjects. But I was always looking for conversations to have. Like if you look at now and you say tax policies, tariffs, the geopolitics of conflict that are going on in the world right now, you have to put all that into a single bucket and make business decisions.

And so I think that every person who wants to personally develop needs to find a way or a group that they can have those conversations with so they can go back and say, "What does that mean to me?" Like does it mean anything if I'm running a contact center out of these countries? Like what's that look like? Because you can't wake up one day and be a great leader at a CEO level and say, "Oh, I wasn't thinking about that."

Uh you really you're being paid to see around corners. And so that strategic thinking, you know, I'll put them in the category of it. It's called philosophical when it relates to sort of ethics and ethos. It's called geopolitics when it relates to like, you know, global markets.

It's economics when you start to think about it in the back, but it's the same framework. It's take your horizon out a little bit, abstract yourself from your job, your function until you get to a level where all this stuff comes together and makes sense. And it's never going to be a perfect forecast, but you have to know the bets you're making. And sometimes doing nothing is the biggest bet.

And sometimes it's the worst bet that you can make. Uh when you look at something and you're not paying attention to a tariff rate for a subcontractor who then suddenly calls you and says, "I can't fulfill unless you give me a 40% increase." You say, "Well, wait a minute. I have a contractual, you know, I have a really good contract with you and they said, "Yeah, I know.

I did that contract when I didn't realize that I was going to be getting this item from one of these countries. It's now under tariff. So, they raised a price to me. I have to pass along or I'm going to be out of business."

And you could have thought about that because you could have been thinking about, so news matters, the economy matters, the geopolitics matters, war in the world matters. That stuff has to matter. And it has to matter at a more junior level than you think because you have to build the cycles uh to be able to be a great leader later when all this stuff is now your job. Wouldn't it be great for you to have the practice of saying I'm thinking one step ahead on this or two steps ahead probably going to get you promoted faster too?

Jay Combs: Two last questions. Looking back like your career has spanned such a transformative period in tech and infrastructure. Is there one specific decision you made that you, hey, I wish I did this differently or it wasn't the right call and you learned from it the most? Is there a formative bad decision that you had made?

John Donovan: Well, I'm going to put it in a category that you may not love. Uh because, you know, I don't spend a lot of time in the rearview mirror. I'm a windshield person. And so, when I look at it, all of my good decisions I should have made sooner.

So when you go back and you look at them and you say, "Oh, these were good decisions." Not all of them were like fast decisions. A lot of them I thought about a while. So I you have to revisit like where was my head and my instinct?

Where was I in the case? How much was I relying on the team? Was I cautious? Because I think fortune favors the bold.

And I think that relates to the good decisions. And if you look, I think the greatest regret is not the bad decision, it's the good decisions I could have made sooner and didn't. When it relates to the bad decisions, I just have this belief that teams produce results. And you should never be an orphan in failure.

And so I hesitate to spend a lot of time saying that was a big mistake because it really reflects on the team. And I feel like as a leader, you should take the bullet for the team on the bad ones. So there were decisions that I should have made, but I'm going to put them in a category of saying I think the mistakes for me are the decisions that I didn't make or I made them too late to be affected. And so I think the ones that you're making at pace, you learn how to adapt.

the faster you move, the more you learn to adapt. And I think that the hit rate doesn't need to be as high if the tempo is up, right? Because you're catching things before you put 100 million in, you've put 10 million in. Before you put 10 million in, you put 1 million in.

So, so like how fast is everybody saying, "Oops, this is not the way it's supposed to be." And so when you let things linger for too long, they don't look like bad decisions because they just cost too much, you know, or you kill something, but you didn't kill it soon enough, you know, and so the things that are alive and flourishing in the world are flowers. And so those are easy. The hard thing is not so much picking where you made the mistake, but picking why you made the mistake and trying to eradicate the behaviors that make you slow, indecisive, not clear enough, and most importantly cowardly.

You know, have to be courageous as a leader. You have to not feel infallible, but you have to once you make a decision, you have to be confident in order for it to be carried out effectively.

Jay Combs: Yeah, it's such kind of a good different take on move fast and break things of uh and I can think of numerous examples where I would say I wish I did that sooner. Why did I wait so long? it can be you're busy day-to-day or you're distracted with other things and that framework of how do you eliminate those things so you can focus on those good decisions faster is really uh really helpful. Uh so final question off the record if you're unwinding after a big or difficult decision what's your go-to cocktail or snack or ritual uh that you partake in?

John Donovan: Yeah, I'm actually very ritualistic um in that I, you know, eat the same thing for breakfast virtually every day. You know, I have a yogurt and pretzels, same pretzels, same yogurt every day. I'm a beer drinker and so my mind knows that I've transition from day to night mode only through drinking a beer. I'm not a big beer drinker anymore, but I do use that as sort of like, okay, that's now time.

It's evening time, which then moves you into a different mindset. So, yeah.

Jay Combs: Do you have a favorite Pittsburgh brew or maybe a Yuengling from the other side of the state?

John Donovan: No. Well, I grew up drinking Rolling Rock. It was the beginning of the trend away from Iron City and uh Latrobe, PA. Yeah, it's um I still get together.

We're going to next month have the 42nd year of fantasy football with the same my high school buddies. So yeah, I almost would ask challenge anybody to pull up that kind of number. Back then it was phone calls and looking in the paper on Monday and rotisserie leagues I guess they called them and you use like thin things and all that stuff. And so we've had the same group for 40 this our 42nd year next month.

So, uh, yeah, I keep pretty good Pittsburgh connection from one particular friend who tries to keep us all united.

Jay Combs: That's amazing. That's, yeah, the that's the right Pittsburgh answer for to those questions. Well, thank you uh, so much. This has been such an illuminating, insightful conversation.

I thank you so much for the time and hope you enjoy the rest of the summer, John.

John Donovan: Thank you, Jay. I appreciate it. Really enjoyed being here. So long.

So on.