Future of Hiring [Oct 15 Cloud2030]

Rob Hirschfeld: Hello, this is Rob Hirschfeld with rockin and the October 15, cloud 23rd discussion was all about the future of hiring, a lot of time talking about today’s hiring. And then in the end, we pulled it into what the future is gonna look like. And that got us into a conversation about AI and evaluating employees and figuring out how to manage them and make them productive. So very interesting discussion. stay to the end, because we really went along on a long time on this one. So enjoy. Rick Parker: I hope you’d start thinking along those lines when they’re in high school, it’s like.

01:01 - Unknown: So the question that you and I talked about, about doing as a as a starting point was, what career advice would you give a ninth grader? for either yours or somebody else? Or a friend? Right? What What would you say for that ninth grader, they should they should go they should think about in today, for their career in 2030. If we want to make it specific, go into think of most kids think, oh, when I go into it ought to be a programmer. That might be the end of all, I don’t think a lot of younger people who are just getting into it. Understand that there’s network engineers and storage engineers, and virtualization engineers, and there’s all these kind of specialties. And it is not just software. I think the hardware might the hardware, I think the only hardware experience we might get is building like their gaming PCs, that kind of get exposed to a little bit of networking, you know, if their home modem router thing.

But you know, the whole idea of firewalls or load balancers, 02:11 - there’s a whole lot of other security, kind of Integrated Security, right? I thought about this kind of later yesterday. Now, you know, where does security start getting added in? I’ve seen securities are getting added in after the network was built. Oh, by the way, we should probably put a firewall in here. And it’s really disruptive to build security and kind of after the fact. It was really kind of hard to build design. And after the fact, there’s so many networks I’ve seen, we’ll build it and then we’ll document it. How does that work? You know, you don’t build a car and then like, write the user’s manual after you build a car? Well, maybe they do. I don’t know. But that’s where some of the design documentation that was going to show was like, you know, first we got to decide what we’re going to build. And then how do we staff to get to where we want to go? Hey, Rick, this is john. I don’t know if this is this an open question, or is it? So please, jump in. So i’m john Quarles.

Some of you don’t know me, but I spent the last four years running a coding boot camp. But we also as part of the nonprofit side of it, it was a nonprofit, we actually 30,000 K through 12 kids. And so this question came up about, you know, we always tell kids, what do you want to do when you grow up? And the things that we did is said, Let’s talk to asking them, what do they want to do when they grow up? and ask them what problems they want to be part of solving. Because 80% of all of our paychecks has to do with problem solving. And basically, it’s, you know, we say chase your passions, but we usually end up really, our passions end up are things that we’re really good at solving, and problems that we’re really good at taking on. And that really changed the dynamics.

And so when it came to technology, because I’m, I’m actually a cloud guy that somehow 04:11 - found himself running in a software bootcamp. I couldn’t I haven’t written any software in at least a couple of decades. But you know, I said, Oh, you want to be in technology? Well, then why don’t you find out as much about technologies as possible, and what problems that they solve, and see if it’s a problem that you might be interested in being involved with? And that made a huge change to the kids? Because, you know, they’re constantly their parents or teachers, like, what are you going to do? What are you going to do? What are you going to do and, and they would just end up saying what they think their mom or dad or teacher wanted them to say. But as soon as you said, hey, what problems do you want to solve in the world and what problems you want to be part of the solution? I had all kinds of things to share. Some of them were pretty comical. I wish I could pull a couple of those out right now but but it was just great. very enlightening and inspiring.

And 05:04 - it’s also very inclusive, right? And how much Oh, we would go into some really tough communities. And it was just open their minds that could actually be paid really well, for being really good at solving problems. It was just an endeavor in their mind, they think that they could be part of solving problems and technology and have the lifestyle and the financial wherewithal that we all enjoy being in this industry. So there’s my answer to that question. I’ve had the pleasure and the pain of having to deal with exactly that question with six nephews and nieces that are all just kidding, with college age, just past college age. And in almost every one of the cases, he best answered came out very much like the one you just heard, which is, what is the thing that really grabs? What’s the problem that you want to solve? What do you want? What do you want? What’s interesting to you, and then let’s talk about what this next generation of technologies is going to do to actually change your job.

If you’re a biologist, 06:30 - the way in which good moments and data analysis has impacted. genomics is is incredible, if you’re, if you’re interested in medicine, summit, same kinds of things, and everything from robotics, to various kinds of micro surgeries, and so forth. And modeling, as opposed to experimenting on, you know, humans or animals. A very big, big deal with one of my nieces, one of the big things was I, you know, I have no problem with the fact that we have to figure out how to have cure these diseases. But the idea of subjecting a living organism to, you know, this kind of pain and suffering in order for events to make it better for me, I just can’t deal.

I said to her, you know, let’s talk about 07:34 - what people are doing with simulations with models with artificially creation, artificial creation of an environment. And it frankly, it blew her away. And she’s now right, this minute, visiting some pretty top flight universities and looking for programs in STEM that will take her in those kinds of directions. So yeah. You know, some of our greatest success was going into a liberal arts colleges and teaching them how to correct software. And they had this tremendous capacity for innovation. And they, but they didn’t have the mechanism to take that vision and make it happen.

08:23 - And not that they all became software developers. But what they said is, they feel like I now have the structure and the language to take this innovation that I have, and speak to a software developer and meet them halfway. Because I understand the difficulty of what I’m asking for. I don’t know if I ask for something that takes two seconds, or two years. But now I have I understand the scope of the the impact of what I’m asking for. And I feel like I’m in a better situation. I’m fine. I don’t know if this is directly related. I apologize.

I came into the conversation a couple of minutes late. But I learned I’ve never actually been a real coder. I mean, the best I ever did was a little bit of basic when I was taking some college classes, so I can’t call myself anything approaching a coder, GW basic. And my wife had to help me with it. So don’t don’t don’t give me any credit. But in line with this in line with solving problems and getting into it is that one of the problems that it suffers from as as a industry is the whole notion of empathy, empathy and support of fellow employees empathy and support of the customers of our work, etc, etc. And I took a chance early on when I was first promoted to a manager for a help desk at HP back in like 91 or something like that. Yes, I’m that old.

09:56 - I think a Janssen hired a nurse Before the help desk, ended up hiring a couple of other people with similar backgrounds, as we built out the help desk, because training them on, on solving the technology problems they were facing was the easy part. But getting them to be empathetic to the situation the customer was in. And carrying that through the lifecycle of the process was the most important part. And they were fantastic at it. They just were fantastic at it. I mean, it just it it mean, in three months, months, we had an entirely different perspective from the business on on where and how it helped us could solve problems for the company. And in fact, we got to the point where we at first dramatically increased the number of calls that came to the help desk, because people thought they could actually get help.

And then through the processes that we implemented, we actually drove down the number of 10:57 - requests that came to the helpdesk because people were getting trained, and people are getting a better understanding of where to find help and how to use the tools and services that were available to them. And we were able to grow to solve a bigger problem and never have to grow as the company grew, the size of the team stayed the same. And it started with people that weren’t it people at all. Amir that experienced let’s see, a lot of it was like network engineers, storage engineers, hardware engineers is probably a better term from Help Desk, a lot of help desk people weren’t necessarily technical people to start from. So it’s really, it’s really a different career pipeline, going into the hardware side than it is into the program into the software side.

I think most software developers probably come out of 11:52 - college. And a lot of hardware engineers aren’t necessarily college educated, the ratio of college educated hardware engineers is much less than software engineers. So that’s my general impression. I can’t resist making a comment. But I was going to turn the floor back to you rich, because you had prepared some material to get us started thinking about the hiring specifically and what the workforce would look like. My experience has been ops ops people are typically not classically trained in computer science. That creates a very, very sad and disturbing difference to this respect, position authority difference in organizations where ops teams are often seen as second class in organizations compared to the development teams and just such a frustrating, unhealthy dynamic there much to that.

12:57 - And despite the renaming of customer success, this is another group that has a whole is has got to be cross trained and trained in so many different things are supported in so many different ways. And I have absolutely seen companies live and die on the quality and the attention that’s been given to their customer success. And it’s not just a tech support. It’s across the board. Thank you. interesting thoughts. I don’t have to think about some of these comments a lot. And if you want Rob, I will go ahead and share my screen. Please do. Sorry, I’m probably have to give you permission, you might your presenter, so you should be able actually, you should be able to share, let me know if you can. You can.

13:58 - Okay, so can everybody see my document or anybody? quick introduction, I’ve been in it for about 25 years, I’ve been involved in cloud computing for 14 years, being in like 2006 as the very beginning of cloud computing. A few of the people on this call have been involved with it that long as well. It’s been an interesting 14 years or so in cloud computing. I mean, the initial discussions were, you know, cloud computing isn’t real. Starting off from that perspective, but about eight years of IT director level with multiple public software’s and service organizations, so a lot of operations and operations time.

14:43 - I’ve had about three years of IP architecture, job titles, building multiple data centers from scratch. I believe multiple data centers, I’m referring to designing the storage, the servers, the routers, the firewalls, the Wham circuit. Everything basically from scratch or smaller companies, what kind of driving this discussion that I had a really exciting opportunity to build data centers all by myself. And most people don’t really have that opportunity, I really refer to that as an opportunity. Because kind of learning how to build a cloud of private cloud and kind of referring to hybrid cloud as well.

And a lot of times, the 15:31 - different teams have kind of kind of like conflicting ideas on how to build things. And once you start making design decisions, and it becomes a little difficult, if you can’t do design it to be a crowd from the beginning. And then the 25 years, it’s been 14 years and just systems engineering, of just individual silos. And part of this is an idea of how to get rid of technical silos. In my technical silos, I’m referring to the network engineers and the storage engineers, and the server engineering team.

So I think a lot of I’ve 16:14 - heard a lot of discussion about how we should get, we should get rid of silos. But I haven’t heard much discussion on how to get rid of silos. So I’m hiring. So I’m gonna scroll through this real quick, and I’m starting off with here is, this is my version of the 2030 hybrid cloud. So it’s big green box over here. This is a private cloud data center module, and private cloud portion of the hybrid the comprise about, you know, one to six of these. And then over here, we have the public cloud components.

So 16:47 - hybrid clouds, I try to include basically, every components of cloud computing. So it’s software as a service platform as a service, infrastructure, service, etc. and kind of they do with 2030. And cloud computing is, this top section is fluid computing management, that would take all the monitoring metrics coming out of all the services and all the systems and feed it up into competing management application. And through machine learning and artificial intelligence, it would control all the parameters of all the subsystems down below to control the amount of CPU and memory and storage and location and everything to optimize cost efficiency and functional efficiency and resource efficiency. So this computing management software doesn’t exist yet. I’m expecting it will exist by 2030.

I know 17:41 - there’s some companies kind of working toward this direction. Just Yeah. Any questions on that or trade show check along. So this is what we’re, this is what I’m proposing to try to build. And the staffing is how to get to how to get to this. I have questions, I’m typing them in the notes so that we don’t interrupt your flow. Sure. I’d like to see if it’s useful for me to see your thinking, talk it through. And then we’re collecting notes in the chat.

And 18:13 - part of this black box in here is the enterprise monitoring architecture that kind of takes all the data from all this stuff in the enterprise, our marketing architecture is what drives the data backup into the management app. This is what a data center module looks like. So this is proximately, three rack design of sports about 750 virtual servers. The main point of this is this is 100%, designed from the very beginning, before you start putting anything, any hardware into any rack. It’s kind of important thing about this, this diagram here, as you can see, there’s rack units where there’s space reserved for certain things.

This is what I mean by 100%, designed from 18:53 - the beginning, but we don’t see Now typically is there’s Rackspace that just isn’t used. And it’s not really assigned to anything. And data centers just kind of grow organically without any design at all. It’s like we’ll build it and then we’ll document it after it’s built. So design up front, you can really optimize the design, it’s really basically impossible to optimize design after it’s built. This is kind of based on a very generic compute resource requirements. Pretty much in the Amazon model.

19:23 - If you go to Amazon, you’re not figuring out you know, basically, Amazon network is designed for everybody. It’s very generic design, so everybody can use Amazon. There’s no reason why you can’t design a private cloud part of the hybrid cloud, to be very generic. They’ll support everything between Amazon kind of chug through. This is why hybrid clouds Why think hybrid cloud so important going in 2030 shaft, it’s basically it’s cost efficiency of number one.

A lot of people have 20:00 - reasons why we should go to cloud computing or hybrid cloud, that every company I’ve ever been at management only cares about cost efficiency, your cost, number one, they don’t care if it’s more efficient. As far as management, they don’t really care about disaster recovery costs. All they care about is, you know, the bottom line, how much dollars is going out? The US is engineers cared very deeply about functional density and resource density integrated raid, and integrated Dr. Right into the design. So many, every company I’ve been at is like we’ll build a disaster recovery later. Of course, that never gets done because no management is ever going to approve 100% tenancy costs.

So going to a raid five disaster recovery 20:43 - cuts, redundancy costs are the cost of 16%, as opposed to 100%. So now we’ll get into like where the staffing comes in. So what got me thinking about this was Marty Lee and Ben Haines discussion on the edge, edge cast, Nirvana. I’m blanking on the podcast and martinis, podcast advanta. And Ben Haines was saying, as a CIO, the most important thing was developing a team.

And 21:13 - that got me thinking, it’s like, well, if we want to develop a team for 2030, what would that team look like? And kind of my opinion, in the last six months has become incredibly interesting to me is emotional intelligence. Now, emotional intelligence, empathy, as Mark stated, is so important. And one of the books I first read on this was on emotional intelligence, it leadership by Harvard Business Review. And within the first couple of pages of this book, it says, intellect and IQ and intelligence, compared to emotional intelligence, emotional intelligence is provide twice as good as the other two without emotional intelligence, intelligence, IQ. And that empathy, it’s not going to go as far it’s twice is important to have emotional intelligence.

22:12 - JOHN, if you’d like to talk to john called if you’d like to talk about this a little bit. It was very coincidence, once I heard the Ben Haynes talk and Marty sock. just coincidentally, start talking to john Qualls and asked him if he was working on and he was working on kind of the hiring and talent management based on some emotional intelligence as well. So very interesting service. But if you want to take over from here, if you wouldn’t mind, a little bit about his heartbeat. Yeah, absolutely. So yeah, john calls, build a few data centers started a company called Blue lock.

Sir, I’m a 22:49 - little off maybe the night because I was actually with my founders, we just cashed our earnout check. So it was a nice night last night with Blanton’s and, but started that in 2006 had kind of eight employees, we went from eight employees, one data center to five data centers and 300 employees and six months. And I tell it almost killed me. And it was the it really was the people side of it that I can’t believe was just under under prepared for taking it on. And so did that spent the last four years running a nonprofit coding boot camp. And I really thought I was closing the skills gap. I really learned it was about this purpose gap.

And I started really going back and saying who were the best engineers ever 23:39 - had? That’s I think I said this to you, Rick is sometimes my best engineers were not the smartest ones. Right? I had some people who had some people who are just incredibly, incredibly smart and really smart and talented, talented. And they they brought a tremendous amount of skills and experience to the role. But they’re almost unemployable and, and really difficult to work with others. So this concept of really hiring and and, Man, I wish I had this 10 years ago, but it’s concepts, we end up hiring for skills and experience.

And then we end up firing for personality, conflict, emotional intelligence. We also they get slammed, I have to say, I’ve seen so many engineers with their visualizes their face, you know, pushed up against this glass ceiling. Because it’s no longer about what skills they can bring to the table, but their ability to actually lead others to solve big problems that are bigger than just one person. And a lot of times it comes around emotional health. And so the head heart and briefcase head us is one of the behavioral expectations for the role.

24:49 - And then what are the, you know, the aptitude or I could call the cognitive potential. I want to be very clear, I’m not I’m not trying to measure how You guys got these big huge sponges, right? That’s how that’s how smart you are? Well, I’m more interested in measuring the absorption rate of smart they are how smart you are is how big your sponge. Because you know, all of us, we’re in this space, it just moves so quickly. And your ability to pick up new stuff quickly and be able to absorb it and take it in and execute it is paramount. Right, so the head, and then I was talking to Rick about the behavioral expectations and someone says, go hire an engineer.

Well, what kind of engineer is this? A, an engineer that’s customer facing is bad, you know, like to think of 25:30 - your dog, backyard dog. You know, there’s so much more than just the word engineer. So that’s the head part. On the heart side, it really is. You know, to me, the head part is where their DNA is right? how their, you know, their behavior profile goes to the role, but the heart is where that on the emotional intelligence journey, and how can we tell where they are? And how can we lead them to the next place and make them aware what it is? I think when I first joined, Rob, I think I heard you talking about I think it was Strength Finders, but I don’t think you said Strength Finders, I think you said something else. Is Strength Finders. Yeah, I call it strength builders. All good. You know, I like assessments, I always define them as this, the assessment is a scientific shortcut and framework, to the insight to the problem we’re trying to uncover. And the most important part is the problem we’re trying to uncover or try to understand. Not the assessment, too often, people.

And Rob, I think you said this, it gets weaponized. Right, people feel judged. And you know, and they, they oversell these things, as you know, they’ll solve diarrhea and depression and acne and all your problems. And just, you know, they’re just a tool, it’s like arguing about the difference between the wall and some other kind of hammer, I’m sorry about this, this has got to be a wind turn it off. So, head heart briefcase is really, now let’s hire harder, so that we can manage easier. And if we have an individual kind of finished with this, to me, I think we all have been looking for our purpose in life and what those things are.

And I’ve always felt like, there’s just five questions 27:13 - that I have to answer. The first one is who I am more comfortable I am in my skin, the more confident I am. The second thing is Who am I not? This is where, you know, to me some of my greatest successes have been things I’ve said no to not what I say yes. Yes, it’s easy. I say it, you know, you say yes, and you fill your life full of obligations and no commitments. So that’s the second question. Third question is how do you work with others? This is the, to me, the biggest challenge with engineers is getting them to work together and empathy.

And you know, who you care 27:45 - about, you care about people who understand who you are. And the more you understand who you are, then you can use that framework to understand who they are. Fourth question is, what do you do? What is that unique ability you bring? And the fifth question is, why do you do it? So who are you? When do you say no? How do you work with others? What do you do? And why do you do it? To me, that is the when I really started to approach that in building engineers, and it’s just been humbling to watch, watch them run with that. So that’s where I think things are going in the future. It’s, it’s gonna be more than a skills that you bring to the table.

But it’s the whole package, the head, the heart 28:25 - and the briefcase, and what you’re doing to invest in it in a lifelong journey. How’s that Rick? Great. junkie gave me a quick demo of the purpose HQ service that he’s developed. And one of the most interesting things I thought about it was it monitors kind of emotional intelligence over time, and gives feedback on how to improve that. So you know, we go and give sales training all day long. I’ve ever seen the kind of monitoring and improving emotional intelligence over time.

Hey, Rick, I really appreciate the opportunity to join 29:02 - today. I’m sorry, for I didn’t have a hard stop 1130 interview, I gotta jump on. But I, man, I just love what you guys are doing. Where was this stuff at 10 years ago, when I felt so alone and wasn’t surrounded. I met Rick and I just love what you guys are doing. I’d love to hear more about what you’re doing everything else and be a part of the vision of what you think about your doing so rock, Nick. Yeah, thank you, everyone. Rick has the ability to reach out to me be well, have a great day. The reason I’m so interested in emotional intelligence and improvement on over time and is that engineers generally trained to management and if you don’t have good emotional intelligence as an engineer, we’re not going to have good emotional intelligence as a management. If you don’t Have that intelligence, emotional intelligence manager, we’re never going to get to cloud 2030, we continue, continue to keep doing the things we always have them. So that’s why it’s still so critical. I concur on that. So making sure they swing back to other conversations, we’ve talked about diversity in the past.

30:21 - In basically, in terms of gaining diversity in terms of race, gender, whatever you will look at most programs, corporate, whatever, are very, have been successful in terms of getting engineers to go into semiconductors. At the basic level, they have not been able to get them past the entry level to management. And that empathy is part of it. And there’s also in mentoring and other things. So basically, it’s the next set. It’s not just people, the basic skills, teaching them how to code, for example, giving them a certification, it’s the next steps, the soft skills, and intangibles, that’s really the the barrier to promotions, which is sometimes not what we definitely think about. But it’s basically the terms of the differentiation between getting ahead in life. That’s I’m thinking through a couple of weeks ago, we did a DevOps lunch with one of the people who doesn’t care for that is that was one of the selling points for him isn’t and that’s the veterans show up because they’ve been military trained, like, with a great can do attitude.

And same time, they’re, they’re very focused on give me give me a task to do it. And so we asked between these skills. I guess I have I have a question, I guess about how does this means that in as we go forward in the future hiring process, are we going to be metric and people on on these non technical skills? I’m gonna like suggest people based on AI and metrics and personality tests, like we were talking about performance. Yes, yes. Be controls to prevent certain bad biases from happening, but you have to it’s, it’s necessary. I’ve heard this mentioned and read this a number of times, it’s like the no jerks allowed, like we hired for no jerks up to give some thought off to look this up. It was a book on software development. Basically, there’s always one software developer who locks himself in a room and won’t talk to anybody else.

33:19 - And they become kind of like a sticking point. And you can’t get rid of him because he like owns this critical part of the code. There’s a name for it. It’s like the thick of it, but there’s a name for it. But Microsoft built advantage came up with a term for it. So I’ll be reading a few bells because we’ve kind of talked circa the late 90s. A lot of time to call that person a prima donna. Yes, prima donnas a good word, to diversity. I’d like to speak to that a little bit. I think the hiring process is broken. I think the annual review process is completely broken. Maybe an it more than anywhere else. I think the hiring process is really driven more towards knowledge and kind of knowledge. Like almost like trivia questions, type of interviews on technical questions. That comes from maybe classical trading.

I’ve had very good success in interviewing and hiring based on aptitude. Much more. So then what’s their current knowledge was? Because I might, My belief is if they have the aptitude to learn, I can teach them anything. But if they don’t have the aptitude, I don’t care. They’re not gonna learn anything new or not as much as we want to teach them. So how’s that broken? It seems to work for you. Basically, because I base my hiring on aptitude and It’s very a discussion based interview process. So what why? Why do you think that other people don’t do that? Based on the dozens and dozens of interviews that I’ve been on, and anecdotes that I’ve heard from hundreds of other people, I’ve never heard almost anything different. As I have, what I get generally gathered is that the, the testing is a way to screen people. That’s the way that if you have 100 applications, you start using tests as screens, right? This kind of like, feature diversity, just a second, I don’t know if this maps, but there’s a lot of, there’s a lot of like, discussion there has been about, like, the si t tests are very gender, you know, or racially bias. So if you have questions, if yes, it can be biased, and why can it screen be biased as well? Right? If it’s okay, though, can we back up to the prima donna just for a moment, because one of the things that that that keeps being said it’s diversity and and excluding the personality type, that is the prima donna is reducing your diversity, there is a place there’s a reason that anecdotally, that personality type has the important part of the code, it’s because they are hyper focused on us Pacific part of the of the problem.

And so I want to just have a discussion around maybe it’s not that hiring them or, or firing them or keeping them or getting rid 36:44 - of them is is the problem, the problem is that they’re not being managed correctly, and they’re not being there, we have to manage everyone from where they are, and help move them to where we need them to be. Very much. So if you’re a prima donna, you have to recognize that and you have to be able to let people help you out. And you feel self aware enough to be able to let that happen. That you you’d be aware unless somebody has taught you how to do that, which means there has to be a manager or someone that is an authority figure, or an educational figure that they respect, that actually has a toolset to bring them to awareness. And so that’s a much more emotional level types manager.

37:49 - Testing in AI testing for emotional intelligence is just a giant lose, you’ve got to actually have management team members who know how to identify the emotional intelligence of these players, and know whether the manager on the team is going to be able to grow them to where they need to be to make the team effective. In terms of larger things, Mark Zuckerberg, let’s call him a prima donna. And I’ve got the guy named the guy at our guy was from Google, who’s Chairman basically had something Madonna, that has grown up. Right, every Don Quixote needs to sanchow right? I mean, and there are times when it’s better to hire pairs or not hire because you never really hire pairs. But if I’m building a team, there, there’s there’s certainly in the past and pairs of people that I wanted to have together on the teams, because their their synergy is such that they they help complete the other person as a team member.

39:14 - If you think about Rob and his partner, Greg, you guys complete each other, like Greg doesn’t know, but he doesn’t speak Intel. Like he really has something to say. And we really have to like pull it out. Make dua complete each other. This is Greg and I’ve been working together for multiple jobs and multiple decades. And one of the things that I’ve learned that this doesn’t just apply to Greg and I think this is the extrovert introvert and part of the value of having some of these sociology testing infrastructures that you can say, somebody who doesn’t, doesn’t jump into a conversation and make them Push everybody out, still has valid points. And this to me, like you had this comment about the go get a beer test with somebody, you might have somebody incredibly introverted, who doesn’t want to have, you know, personal personal details, who shows up at work and very heads down doesn’t share a lot of details, is an amazingly great contributor. But you have to create a space for them to make the comment, right, Andrew is talking about Greg, you know, I’ve been in situations where I’m like, everybody just shut the hell up.

We’ve got to have some other people who aren’t seeking talk, and give 40:34 - their opinions. And, and just because you’re not saying something in the meeting, doesn’t mean you don’t have important funds for the meeting. And that’s all that’s all of our responsibilities. But I do, I do feel like we have these these challenges, where it’s really easy to filter out somebody who doesn’t think like you, or act like you or talk like you or is able to, like you and make make really bad assumptions. And it seriously, I’m not saying racket ism is a great example of this, I think we have to think about what it takes to have that type of broader those are just some, some get people in to organizations.

And 41:22 - I think that’s what a really good manager does is kind of understand the personalities of the team members. I think that’s why the purpose agent service does a pretty exceptional job of that. It kind of generates report of like he can compare to people and it generates record of how well they can work together. And it kind of identify as one as an introvert one as an extrovert, and what each one needs to work better together. Just as a last point on that, and we’ll continue a little bit is, I would really like to see emotional intelligence, referred to during like annual reviews.

You know, it’s like, it’s one thing to I think emotional intelligence can be improved. But you have to be aware of that you need improvement, I took the personality tests was pretty interesting how it came out as like, kind of scary, accurate, but it did kind of point out to be that I have a significant area of improvement that I need to work on. So as I was pretty happy, I took the test. And I agreed with the with the assessment. It’s interesting. So having tools that help people review and analyze definitely be helpful. Rick, I’m gonna pull down your screen if that’s if that’s okay. And settled.

42:45 - Can you do it actually sure, is written on a good track, and especially for areas where engineers which tend to make up a large portion of cloud really money and companies and whatnot, we need tools to help us in our areas of weakness, and we need tools to help us identify those areas of weakness. And management certainly leads to no need to have those tools and have ways of providing like educational material so that those people interested in growing themselves can possibly do it on their own. I would also want to add that we need to foster an environment where showing a weakness for admitting weakness is not a ground for fear. Yes, very much. So. This is This to me is the dilemma with playing 30s we’re so focused on STEM education, boot camp skills, things like that. And yet, what we’re saying is true. The number one thing that you’re going to have to be able to do is be empathetic. I feel like this is this is known.

Yeah, like we 44:20 - know, we have to help people actually connect through these digital mediums and not hide behind the coattails. Are we gonna have tools that actually help people with it right now, but the tools that we’ve got, making it worse. That’s a statement. To make things worse. That’s interesting. Well, that’s because when you’re looking for in tool, a jackhammer looks like a tool if that’s the only one that’s in that type of area. Like you’re looking for a hammer, and all they have is jack hammers you go, a lot of people go to the jack hammers, Google is is, is an example case out the wazoo, where they don’t seem to train their managers, they don’t have tools to talk to people who work at Google, an awful lot of them are unhappy for reasons. They can’t, especially, can’t really identify other than the team’s not working well.

45:32 - thinking for a moment on emotional intelligence book, it’s got about 12 different areas, from different businesses on how teams are working very well together, not working very well together. Either not working well together, the more interesting ones, how they were, how they were improved, or not improved. So I can’t really recommend that book enough. And our current theory, every every every team, every team, every team that works well, it works well, in one way, I have a team. I think their personalities just like their individual personalities.

So it’s really interesting to me to kind of map a teen 46:31 - personality is a unique identity. The thing that I’m getting back to what I think about 2030 in the future, and font align with a eyes and integrations with mean, you could be in a team in 10 years, where one or more AI eyes is actually a component of that team. Perfect. The manager of that might actually be an AI. From that perspective, predominantly an AI will issue with some type of human augmentation. Right is what one frog crazy. To with that better, assuming like we can fix some of the bias problems? And I think those are two different questions. Yeah, and I wouldn’t say better, I would say different.

47:22 - And the people that are functioning well, in today’s marketplace might not function as well, in the marketplace that you’re envisioning. Because you have to you can work a personal, you can work a manager, that’s a person in different ways, or you have to work a manager this person in different ways than you would at AI. And there are people that succeed a lot, because they know how to work there manager. I spent enough time in big organizations to see how different teams culture more than anything molecular where our CEO is very peppy, even the most basic news and exclamation, like everything is like it’s like with my husband. Everything’s fine. It was amazing. Just different culture. definitely different. So I could see, I guess I’m I keep trying to put on the 2030 hat. And everything we’re describing.

If there’s if there’s real material value in in EQ 48:50 - and team harmony and team dynamics, then those convinced me that there is no doubt we are going to throw AI and analytics into this problem in such a way that somebody’s like, oh, their social media posts or seemed a little depressed or angry, or maybe I should, you know, send them some information that helps them feel better or we’re already great. This is where my head’s exploding. We are already doing social media, companies that are manipulating your emotional states to sell more advertising. Right. That’s not a that is a known opinion. That’s a fact of this. Are we hiring systems going to look like that? That would be sad if they do because there are a lot of people who aren’t manipulated by those companies and the People who weren’t susceptible to that route of ulation, at least some of them are going to be really important. Going forward, some of the listener, the neurodiverse, people are oftentimes the ones who make the difference between success and failure in small companies. There’s all sorts of opportunity to become rather dystopian.

And, 50:24 - like, from our perspective, we’re missing these tools as, as being geared towards pushing for equality or equity. But I can also see just a company, what tweaking the algorithms just to aim for, for say to do to hire people who they know what they’re for the date, they’re going to guess, will have lower maintenance, which is going to start excluding a whole Platinum will always see exceptional, given the chance. So, but the thing about and I don’t know how this responds to your initial question, rich, sorry, rich. Rob, about the AI. I’m first of all, you know, teams in general, if you go into an interview, and you say, I’m a good teams person, then you’re immediately discounted as Oh, everybody’s a good team first. And yet, when you get hired, well, why isn’t he a good teams person? Oh, I didn’t say I was a good teams person during my interview, did I. And so there’s this, there’s this.

51:47 - Part of my frankness, there’s this bullshit that happens between how we hire and how we cliche, someone who’s being hired, that’s incredibly important to what we actually say to that person, verbally and non verbally when we hire them. And so I think that’s got to be a critical component of the thought process of bringing people on board, the process of having them on board has to be an incredibly well thought out function. And, in fact, it’s odd that I was literally just speaking about this with a couple of other very important people in my life. process of bringing people on board, how they’re trained, how they’re brought up to the culture, etc, is hugely critical in their success. Secondarily, teams never fail. teams don’t fail, I’ll pick that argument all day long. teams don’t fail, leadership fails.

mathematic, I’m not even I’m not a math whiz, I’m 52:45 - not nearly as smart as most of the people on this call right now. But I can tell you mathematically, a team of more than three people failing as a team is is so mathematically a longshot, as compared to the leader being the problem. And once you go above three, it the math just gets worse and worse in favor of it being the leader that’s. So when we talk about, you know, what kind of culture we want. When we talk about how we deal with individuals in a team, I’ve had teams where every single one of my direct reports, all senior managers, and directors, every single one of them, the vast majority of them, I should say, would never go out to have a beer.

53:25 - They would, they’re just not the same people. But creating a common vision and helping people fit to where they add the most value. And helping people feel valued when they’re contributing to the team, makes them believe that they are a team makes them believe that they can contribute more as a team. And so my biggest concern is that long story cut short, my biggest concern about using AI, or using what we all see in the news and in the press and in books all the time of anything that says it’s always this, it’s always this, you need to be this. That’s wrong every single time. That’s just wrong. And so the human equation of dealing with teams and developing people, making them feel excited about what they’re doing and contributing more than they thought they could contribute is potentially a science and maybe AI will solve for that someday.

But realistically, 54:27 - it’s it’s a it’s a really delicate path and the best leaders know how to do that. They know how to do that without fear. And they know how to do that. Regardless of whether they have you know, a prima donna and, and 10 really empathetic people or some other mix, but you do have to make a call at some point about the value of that prima donna versus The value of the team as a whole, and how much are they contributing? And how much will how much time are you willing to spend in for walling their behavior from the rest of the team, because of the greater value versus just saying, fuck it, I’ve got to cut my losses and find someone who’s more able to contribute while still not burning the team to the ground. Mark. So I agree with your point about the role of the leader and making changes in the team. The part that I question is, I wonder if AI is, if AI really kind of plays a role here? Because? Or if it does, we have to think very differently about how we use technology into this mix. Because, as you mentioned, in your examples, there’s a conscious rationalization that takes place in the human psyche to say, you know what, this is not the outcome that I ultimately wanted, what can I do to change it.

55:57 - But yet, if you think about some of the ways that we build models, and kind of the inherent way that AI functions, it’s based on past history squarely based on past history. So we have to either figure out a way to infuse or identify behaviors or outcomes that we don’t want is a way to guide AI, or we have to come up with a completely different way to do it. I, in some ways, I think a lot of folks, not the folks on this call, and that’s this conversation. But a lot of folks are kind of using AI in a way that I don’t think it should it should ever be used. And so bias comes into the into play, and not surprisingly, right? Because it’s based on history. And we’re all biased in some way. So I don’t know what the answer is.

But it’s 56:46 - I think it’s something that has to be kind of figured out. The other thing that occurs to me in this conversation, right? So again, complex systems, is I can’t think of a place in nature where a system actually truly optimizes like an engineer would optimize that pushes the system, right? What nature does is it gets a pretty damn good given the environment has, but it also creates new destroys, doesn’t work on a regular basis. So the idea that you can create a stable environment and optimize environment without having to play with the dynamics constantly the way a good leader would do, right, the way that leadership is intended to do that in hiring, can you do a better job? I mean, there’s a lot of experimentation around that right now with maybe ai ai helping out with hiring and identify that little thing you don’t know, the thing I’m excited about is the experiment. You know, I can’t talk a lot about this experiment. But we were running at AWS and sort of a number of running companies.

58:11 - And Tom trying to say what if we’d made the person the center of skills assessment instead of the institutions. And so that if we collected all your information about everything you did, that builds skill, and builds experience and builds, reputation, potential, right, and brought that together into an identity for the individual, and then that you evaluate a common set of data that has been collected? Could you get a much better assessment of who actually has the temperament and the skills certainly the maybe even the temperament and the skills to take on a specific task, which is typical. Um, That, to me is somewhat exciting, because at least what you’re doing is you’re creating a common playing field. But if some you know, if somebody’s working in a mechanic shop someplace, or working on a farm or working, you know, in a, as an aide to a Supreme Court justice, does certain things, you’re looking for tasks, if they show the right set of capability that’s going to come through. I don’t see much AI in there to maybe in valuating that data once you have massive amounts, but I’m much more interested in having a really, you know, in observability in the space than I am, right. Ai, folks are getting ahead on AI.

59:45 - The model for learning is self limiting one where someone else spoke That earlier in that it only has a history. And we’re actually putting all of our biases into it. So the closer we get to AI, that is focused on the soft skills, the worst, the worse the bias is going to get. Right now they’re actually talking. A lot of the Arab world is talking about literally phonology at this point. And we have to tamp that down. Because phonology is a way to assess a person’s goodness or badness or capability. That is just yeah.

And so it’s, it’s not 00:37 - AI in the sense of the original intent of the field. And what we were talking about, is something much closer to a self learning. And a, it’s even that the folks who’ve been in the field since the beginning, are saying that’s 30 years off, if, if that close, I put a link into David Hooper Wallace, he is an amazing person to follow. In this since the very beginning, as a student of Minsky, at 14, we come to seek us, maybe we might do again, I’m I cannot actually ping him on that. I’m not directly his friends that I’ve talked to him and we’re alone.

01:32 - And actually, that might be a that would be really useful for this group to really understand where AI is. This is the second at least a second wave where everybody’s talking AI. And the first one was like expert systems and knowledge acquisition, things like that. And this is the next hype wave, it will go down because everything AI is it generates all these wonderful tools, but so far, and we’re getting close to it. But so far, it’s still is up in the horizon 30 years, it has been for the past 15 years. So the horizon.

02:18 - The quick point, and the cloud roles and responsibilities of cloud admin, cloud engineer, and cloud architecture is a document that will be available as a resource. We didn’t really have time to get into that. On the second part about AI, I think at this point, the input for AI for hiring a resumes. I don’t see how resumes are how AI is going to interpret emotional intelligence based on the input of resumes. Oh, man, think of all the gaming we’re going to be doing for AI. Resume reading. Yes, yes. Everybody is amazing. I love these conversations where nobody wants to stop.

But But 03:05 - thank you for feeding this balance and give a second because I pin you directly. Back Wow. Yes, yes. I’d love to entertain you. I want to ask about change. Okay. Talk to you later, everyone. In 2013 discussion is all about future hiring. Days hiring and then in the end, we pulled it into what features to look like. And that got us into a conversation about AI and evaluating employees, how to manage them and make them productive. Very interesting discussion. We really went along. I hope you start thinking along those lines when they’re high school it’s like so the question that you and I talked about, about doing as a as a starting point was, what career advice would you give a ninth grader? For you .