Hello and welcome to My Career and Data, a podcast where we discuss with industry leaders and experts how they have built their careers. I'm your host Shannon Kemp, and today we're talking to Bill Bruno, the CEO at Celebrus. More and more companies are considering investing in data literacy education, but still have questions about its value, purpose, and how to get the ball rolling. We're doing the newest monthly webinar series from DataVercity, Elevating Enterprise Data Literacy, where we discuss the landscape of data literacy and answer your burning questions. Learn more about this new series and register for free at DataVercity.net. Hello and welcome. My name is Shannon Kemp, and I'm the Chief Digital Officer at DataVercity, and this is My Career in Data, a DataVercity Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who help make those careers a little bit easier. To keep up to date in the latest in data management education, go to DataVercity.net forward slash subscribe. And today we are joined by Bill Bruno at the CEO at Celebrus. And normally this is where a podcast host would read a short bio of the guest, but in this podcast, your bio is what we're here to talk about. Bill, hello and welcome. Hey there. How are you? Thank you so much for having me. I'm excited to be here. I'm excited for you to be here as well. So tell me, OK, so you're the CEO at Celebrus. So what is Celebrus and what is it that you do? Yeah, no, absolutely. So Celebrus is a data capture and contextualization platform, which is a mouthful.  It means that when you read any surveys from like a forester or a gardener, they always talk about how difficult it is to use digital data for business initiatives and to bring it together with other sources. And they talk about things like how digital identity verification is a real problem and difficult for solutions to manage. And those are the gaps that Celebrus solves for. So you deploy Celebrus across all your digital touchpoints, websites, mobile apps, kiosks in an airport, ATMs. And we capture all the data for you. We give you a logical table data model that data scientists love and it makes it easy to use it everywhere. We solve for digital identity and we basically at the end of the day solve for two types of use cases. The root and the heart of everything we do is to build better relationships between brands and consumers. On the marketing side, that's in building better experiences by ideally showing you things that you're interested in. But on the fraud side, it's preventing fraud and protecting all of that hard-earned money that you've got that you're looking to spend that day or unfortunately where someone else might be looking to spend it for you and we're trying to stop that from happening. Awesome, I love that. So and you're the CEO. So, you know, we get to have a general sense of what a CEO is, but what's kind of your day-to-day? What are you doing? You know, I think from a CEO perspective, I'm not going to make it sound all fancy, right? What it really means is you're the guy that flies in and wears many hats ideally and helps your team on a daily basis and tries to build a high performing team, tries to help people better perform at their jobs. And in some days, some days I'm a bulldozer, right? Like there's a roadblock in the way of our team from doing something valuable and I'm the guy that comes in and tries to help clear the path for them, right? So, you know, this is my third stint as CEO in different companies. And, you know, I think it all kind of looks and smells the same, right? You've got to be involved. You've got to be working with the team. You're creating opportunities for people to grow professionally and you're trying to make sure that you're building the right culture that's focused around customers and delivering value. OK, OK, so let's back it up again a little bit way back. So when you were in elementary school, you know, was this the dream? This is what you wanted to be when you grew up. What was the dream? You know, I don't think I ever wrote in my terrible handwriting data analyst or computer engineer and anything that I had ever done in grade school, right?  You can probably assume that I at one point wanted to join sports entertainment and be a professional wrestler, the likes of a Hulk Hogan or Ultimate Warrior or things, things along those lines. But, you know, data didn't really peak in for me until probably towards the end of high school when I was actually trying to figure out what the heck I wanted to do at college, right? I mean, that that's just kind of it kind of just fell together. Oh, so what was that path? What were those thoughts that you were in high school? Like, what am I going to what am I going to major in? Yeah, so, yeah, I mean, I was always kind of a nerd, right? You know, I'm proud to be one, but the areas I excelled in were math and science. And so for me, it was kind of exploring where where you could go with that type of background. And, you know, when I was entering school, I graduated in 2004, right? So when I was entering school, it was kind of, you know, the the the rise and fall of the dot com, right, throughout my time there. And I just decided that the computer engineering sounded really cool. I didn't have many reasons for it. I kind of just stumbled into it, right? And went down that path, did an internship where I was in a cubicle coding and nothing against against that part. But it wasn't really for me. I didn't mind the coding part, but I kind of liked interacting with people. So then I started looking into consulting. And so when I came out of college, I joined and found co-founded a consulting firm with with a couple of other folks. And that was the start of my career. And it was focused on at the time, what was called web analytics. So helping people actually prove whether or not those websites were going to make money for them, because, you know, we had just gone through the crash. Wow, that's that's amazing. So you really got into some some data right away. Yeah. Yeah. So tell me a little bit about that. So in that and that journey and yeah, it all started for me in college. I had a couple of classes I took, actually, ironically, given what the art what's talked about so much every day these days. I took some artificial intelligence courses in college. I did a lot of math, did a lot of coding, did some gaming coding, which was quite interesting, although very, very difficult to make so you appreciate the people that make video games today. So I dabbled in a little bit of everything, but I just always loved understanding how things worked. And that and that just kind of tailed itself into a couple of projects for me towards the end of my time at the University of Illinois down in Champaign, which was focused around actually using at the time log file data from servers to identify insights. And that's largely what became web analytics. And now it's obviously grown into something much crazier. It's been a wild ride for the 20 plus years I've been doing it, but it all started with some simple web log files from some servers and trying to make sense of them and write code to do so. Yeah. Yeah. Love it. So you still have that consulting. So tell me about that, that consulting and to grow into that. Yeah. So I did we the company that we found it was called Stratigent. You know, everybody's got to have a fancy name with strategy in it.  I ended up selling it to a to a different business in the UK in 2013. And then started sort of running analytics globally for that business for quite some time before I decided to move on from there, figure out what I wanted to do next. And now I'm on the vendor side for the first time in my life, which has been a been an interesting shift because historically I've always been the consultant that's, you know, vendor agnostic. I'm going to tell you what the right fit is. And now I'm telling you why my solution is the right fit. So that's been kind of a fun transition in my journey, I suppose. I love it. Well, so now with all this experience with data. So what is what is your definition of data? Something that's usable. And I think that that's how I always like to think of it, because there is a lot of information out there. I mean, even even in the data that Celebrus collects for clients, like you're not always going to need all of that data on a daily basis. Right. It's to me, it's what's usable. How are you going to use it? And that doesn't mean that you should limit what you're what you're collecting because I think it's very easy. And I've seen a lot of people talk about that, like only collect what you need. And I think the problem with that is none of us are Miss Cleo. You're not going to know what you're going to need three months from now, six months from now, a year from now. So I think the most important thing now is collect something compliant that you're actually allowed to collect that consumers are allowing you to do so. But the definition for data to me is it's it's not something that's just sitting there, right? It's some it's information that is beneficial that you can use to add value in your job, in at home, you know, with your customers, you know, it's kind of all over the place. Right. I mean, I just read I just reconfigured all of our thermostats for the summer, right, to change all the schedules. And it's all automated and everything's based on data and how we historically use it and when you're home, when you're not. Right. So there's there's no shortage of information, but it's it's to me, it has to be usable. Otherwise, you're probably just wasting your time. Absolutely makes sense. And I have full appreciation of an automated house. Most of mine is too. So tell me, so as a CEO, how do you work with data? What's important to you and how do you use it? And, you know, I mean, you're building it into a product and really at the core center of your product. But but how are you using it in your daily work? Yeah, so it's a it's a great question, right? And I think, you know, from in all three instances where I've run businesses in my career, it's it's always wherever possible, every decision needs to be data driven. But you've got to bring in the right people across the business that buy into that approach, that buy into that culture and find ways to easily automate these things to get the right information to the right people, because it's not just me. That's going to need data on a on a daily basis or on a weekly basis. It's going to be my head of professional services and delivery. It's going to be my CFO and his team. It's going to be my head of HR and her team. It, you know, every single team needs to to to have that culture embedded or that value embedded, that data is how we're going to make decisions, right, even every marketing campaign or every sales idea that gets thrown my way. I'm happy to test them, but we have to have a plan in place that clearly defines what success looks like so that we can work back from that and decide what data we need to be able to measure that success and then make sure that the systems we put in place do that. And I'll be very honest with you. I've only been CEO of Celebrus for almost two years now. And when I joined and the new CFO joined with me at the basically the same time, the first assessment we made was that there weren't enough systems and in some cases any systems in place to really help bring that data driven philosophy across the business and to help empower our leadership and their management teams and sort of as you go throughout the whole organization, you know, to not empower there was nothing there really to empower them to use data in the right ways. And so that has always been a passion of mine. I mean, I think I will always be a data analyst at heart. And there are things that I see daily. There are things I see weekly, you know, so on and so forth that are used to help guide the direction of the business. Amazing. So so is there been any key wins that has enabled you to transform that that culture? Absolutely. I mean, I think, you know, it's always easy, I think, to point to the stuff that goes well, right? Because it's like, oh, it's going great. Like, look, the data is showing us that something's performing. In my opinion, culturally, when something doesn't work, that's when that's when it really comes out. Because how you respond to that, I think, can make or break a culture, right? If you want people to be honest in your business about what's working and what isn't, then you also have to create a space for them to be able to admit that something didn't work, but that we learned from it and how we're going to apply that going forward, right? And, you know, that could be something simple, like a, you know, trying a different style event for marketing purposes and sending the team that maybe may or may not work, or it could be something internal. Like we brought in some new technology to try to help automate some of our efficiencies and it just didn't quite meet expectations, right? It's it happens. You need to be able to test and learn. But the problem, I think, is that a lot of businesses, you know, sometimes skip the data part that goes into that and don't don't think through what success looks like and don't don't make sure that the right metrics or, you know, measurement protocols are in place to help guide that. It's complete in total sense. So, you know, especially being in an executive role, you know, do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next 10 years and why? So another great question and one that is in almost every article these days with with artificial intelligence, isn't it? And what that's going to do, right? But I think whenever there's been technology innovation, holistically, yes, you're going to see certain jobs perhaps become less important or perhaps become automated by that technology. You've seen that in every industry. But then there's always something next. There's a there's a next step from that that creates different jobs or brings different skill sets or offers opportunities for people to to really, you know, dive into a new career or a new set of skills. I mean, data science was like that, I would say, over the last, you know, let's say 10, 10 to 15 years, right, is sort of something that when I was in, you know, in university or college, depending on what side of the pond you're on, wasn't really discussed much outside of like some hypothetical artificial intelligence models, right? But, you know, so for me, I think that jobs and data are going to continue to grow. I think that they're going to become increasingly more necessary. And I think a lot of that's going to be driven by privacy and compliance around the globe as well. You know, it it just may look different, right? You might not have as many people wrangling the data, but you're probably going to have a lot more people spot checking, right, so that the robots don't take over and so that Arnold Schwarzenegger doesn't have to save us again. You know what I mean? I do, I do indeed. Yes. So, so then not to put words in your mouth, but just kind of so it sounds like data governance roles are going to be really, really important and data governance isn't necessarily a dirty word, but a necessary word to to to manage the the policies and processes behind what's. Yeah, yeah, I think data governance should have been for a while, right? And I think we're going to see a pretty heavy investment in that going forward because nobody wants to be the next brand in the news. But I also think data cleansing and validation, too, is is going to be a big one. And I I'm coming at that from an angle of ethical AI, right? You know, I think we're we've seen for years, you know, where things aren't perhaps tested against, you know, what society actually looks like in the real world when products are brought out and it's because the data is bad, right? Or it's not complete or it doesn't represent, you know, the the target market or what the real world actually looks like. And I think, you know, as as organizations run and in many cases are right now sprinting towards AI or generative AI or whatever you want to call it, you know, we can move fast, I suppose. But the part we're going to need something underpinning to make sure that the inputs are good enough to to satisfy the output, right? And so I think you're going to see a lot created around this and to help sort of drive us into the next, I guess, data frontier, I suppose. Absolutely. Now, you mentioned ethical AI. So what does that mean to you? There's so much debate around this and there's so much discussion on this now. I think it varies by category or what type of model or what type of product you're talking about, right? But, you know, I've I've I've spoken on many podcasts over the years and, you know, it's it's a bit tongue in cheek, but true. I used to call them racist robots, right? But it was like, you know, you you've got products or things, you know, like self driving cars and things like that that are not designed for the society that we live in because the the the test samples, you know, are then what they've used as the data in is not complete. And so it's not a full test. So for me, there there's ethical AI on sort of the product side. Then I think when you when you get into things like the banking industry or even retail or travel, where you're perhaps changing the prices on things or you're perhaps changing the offers that I might be seeing versus what you you might be seeing, there's obviously an ethical element to that as well to make sure that the reason we're seeing different offers is actually valid and based on interests and not based on some sort of discrimination. And then I think there's just holistically this this thought that needs to be to spot check, right?  They're they're not they're not going to be any smarter than the data that you've provided access to. And so that's that's when I think of ethical AI and it's something I'm extremely passionate about. But it's you know, there's a lot of angles to it. There's not a right or wrong answer. But I think the most important answer is remembering that there's a lot of bad data in digital and there's a lot of bad data online. And when you've got things pulling from those sources, they're not necessarily using the facts because a robot's not going to just be able to discern that. I mean, if it's if it's published online, it may not be true.  Right.  With a robust catalog of courses offered on demand and industry leading live online sessions throughout the year, the Dataversity Training Center is your launchpad for career success. Browse the complete catalog at training.dataversity.net and use code DVTALKS for 20 percent off your purchase. I love it. Well, so what advice then would you give to people looking to get into career in data management in any form in any level, whether it be, you know, a data scientist or into data governance? Maybe specifically, since we're kind of talking about that, our data cleansing, what skills do you need? You know, and how do they get into that?  There's not necessarily a massive pool of experts that organizations can pull from. And so there's really a good opportunity to land and grow and build a career around it.  And they've chosen to just teach themselves some things. You know, it's there's an ample amount of material out there to learn. There's an ample amount of online courses to teach you about data structures and principles and some of the basics. It's a lot of books out there. You know, so it's not it's not hard. I think my only advice would be if you if you're passionate and you think this is something for you, then then get ready to put in the legwork and work hard.  It might not pay off right away. And you might have to, you know, have some stop starts at some organizations or take an intern internship or you're bringing people coffee in exchange for getting access to stuff. But it's, you know, that the hard work will pay off. And their data is currency in our in our world these days. You know, it's it's the gold of digital. It's the gold of brands and organizations. And so I think it's it's a great career to explore, you know, digital analytics, data science, data governance, however you want to look at it. If you have a passion there, there are an ample amount of roles available for it. And every time my organization publishes a role for someone in our org, you know, things flood in and we're not even that well known of a brand, right? So it shows just the amount of demand and the amount of interest out there. So it's I think it's a great great career for someone that that is looking to start one or someone who's looking to reboot. Oh, yeah, indeed. Any advice on, you know, additional resources and, you know, and how they go and keep on learning? You know, of course, we have our program. So I'm just going to give my plug for a database.net.  Where else can you go learn and and what are some great resources and how do you find mentors and. Yeah, it's a it's a it's a good question. I mean, I think I was going to plug your stuff anyways, but you you be to it, right? But I because I think everybody learns differently, right? And so, you know, depending on how you learn, probably is going to dictate where you go, right? You know, for me, I love podcasts. I love listening to things like this to to learn things of interest and then go off on my Google journey and learn more, right? But the for those there's an ample amount of of phenomenal books that I'm failing to remember the names of that have been written about data structures and principles. There are a ton of analytics universities and and actual, you know, not just online versions, but there are actual universities throughout the states that have and in Canada that I'm aware of that have some phenomenal data and analytics courses. I have a friend of mine who's taking some online courses right now to to reteach themselves some new principles around data. So it it's it's crazy.  Most of it's free to get you up and running. You could go to a Amazon and they have an entire suite of educational materials around AWS and sort of cloud principles. And the list could go on and on. But it's as you might suspect just like data is increasing on a daily basis. So are the amount of opportunities to learn about it. And and just to kind of expand it a little bit.  You really wanted to go out and be more engaged with people. You know, how important are those communication skills and those soft skills needed in these data careers? You know, I think it's a good question. I think it's interesting because it depends on the kind of networking is great for everyone, right? But but some people and and, you know, I've had tech people that I've worked with in my career that just like to go work and they're in there with their, you know, six screens and and they just want to go get their work done. And that's their preference. Then you've got people like me who are going to be more on the other side where I kind of want to I want to talk tech, but I also want to want to be out in the front and interacting with clients and partners and and learning from them. But, you know, there's a lot of phenomenal networking opportunities in almost every city these days. I mean, on LinkedIn, there's several that I participate in the Chicagoland area where I'm based, but there's a ton of LinkedIn groups around data that share different conferences, networking opportunities, etc. And, you know, I think those are great ways for you to meet people, you know, and find people who perhaps are in roles that you're interested in or working for companies that you're interested in working for. I love it. Well, I would be remiss if I didn't ask you. If people wanted to learn more about Celebrus, where would they go? Sure. So you can go to Celebrus.com. That's C-E-L-E-B-R-U-S.com. You can find Celebrus Tech on Twitter as well as on LinkedIn. You can just find me on LinkedIn, Bill Bruno, and I'm happy to connect you as well. And we're always we're always open to conversations. If you need recommendations on jobs, if you want to look at my LinkedIn network and you want me to try to lead an introduction for you because you're looking for a role in data, I'm happy to do it. I've been fortunate in my career to have people help me along the way. I wouldn't be here without the help of many, many people, and I'm happy to pay that forward. Thanks so much. That's a really gracious offer. Thank you. And that's part of my one of my favorite things about the data communities. Everyone seems to be really, you know, willing to help each other out. I haven't seen anybody make it on their own. It's always been a collaborative effort. Yeah, anybody that thinks that you can just make it running on your own, that's a bit of a fool's errand and they've been lied to, right?  There's always a little bit of luck and there's always somebody that's put their hand out to help you get there, whether that's coaching, whether that's advice, whether it's actually just giving you an opportunity to to start a career, right? And you know, like me, if I, you know, I came across the Josh and Julie, they were a husband and wife that wanted wanted wanted to build this consulting firm. And I started in their basement, right? I mean, that that's that's where I started and many people along the way, you know, offered me opportunity, you know, you can work as hard as you want, but you still got you still need that network to help you out. I love it. Well, Bill, thank you so much for taking the time to chat with us today. I really appreciate it. Oh, you're absolutely welcome. I really, really enjoyed this. I listened to a lot of your talks, so I was really excited to be part of this. So so thanks. Thanks for having me. And it's yeah, it's been a been a pleasure. Thank you so much. And and and to all of our listeners out there, if you'd like to keep up to date in the latest in podcasts and the latest in data management education, go to dataversity.net forward slash subscribe until next time. Thank you for listening to Dataversity Talks, a podcast brought to you by Dataversity subscribe to our newsletter for podcast updates and information about our free educational webinars at dataversity.net forward slash subscribe.


My name's Doug French. In case you've lost your programs. And I'm with the Mises Institute in Auburn, Alabama. Of course, that's not why Hans asked me to speak on this topic. I'm actually an ex-banker. I used to make real estate loans, construction loans, in one of those sand states that Steve Saylor talked about yesterday. I was a lender in Las Vegas for over 20 years. And very much a contributor to the boom. And the bust, as it turns out. So thankfully I've found a place to land, but this speech will have a lot to do with my past experiences. But I first wanted to talk about legitimate banking. Not that I have a lot of experience with legitimate banking, but legitimate banking is based on honoring property rights, which seems appropriate for this conference. And if you put money into, make a deposit into a bank, into what we would call a checking account, that person is not trading a present good for a future good. If you put money in the bank, you still believe it's your bank or your money. The bank is just warehousing it for you. The deposit's not alone. You're not giving it to the bank for a certain amount of time to be returned later to you. It's available all the time. You could put it in one day and get it the very next afternoon. That's the understanding. The bank goes to guard, protect, and return the money at a moment's notice. But unfortunately bankers, being men and women, they're subject to temptation.  Sort of just stealing depositor's stuff, or in the case of money, the warehouseman borrows the money temporarily to profit by speculation or whatever and return the money later, prior to when the depositor needs to withdraw it. And of course this is called embezzlement, which the dictionary defines as appropriating fraudulently to one's own use of money or property entrusted in one's care. And essentially that's what modern fractalized banking is. And of course nothing is more tempting than gold coin back in the days of the Goldsmiths or money now, cash money for embezzlement, because these items are fully fungible. And they found that this is very profitable to create money out of nowhere. So bankers and governments have found that it would be very important to find an adequate theoretical justification beyond the easy solution of just simply declaring legal a corrupt criminal practice that's ultimately happened. Now there's a number of court cases down through history that has made this all legal. But really what reminds me of this is a movie, a John Wayne movie called The Common Charrows, and I don't know if any of you have seen it. But there's a great character played by Edgar Buchanan, circuit court judge Thaddeus Jackson Breen. And he tells Paul Regret, played by Stuart Whitman, major here has told me what your problems are. I've been thinking it over and in light of my 40 years experience in legal jurisprudence, I have come to the positive conclusion that there's ain't no way to do this legal and honest. Being sensible Texans will do it illegal and dishonest. And I think that sums up how banks and governments have come together to make law very ambiguous, deliberately ambiguous to legally justify fractional reserve banking. Because ultimately fractional reserves cannot survive economically. They must be supported by government force. They must be supported by a central bank, which institutes the regulations and supplies the litiquidity at all times to prevent the entire apparatus from collapsing. Now banking crises are as old as history. And in fact for those of you who are going to Ephesus on Tuesday, there was actually a crisis that occurred over 2,000 years ago. I don't know what the name of the bank is, it's probably Ephesus State Bank or something like that. But this crisis motivated authorities to grant the banking industry its first express historically document and privilege, which established a 10 year deferment on the return of deposits. So as you're walking around Ephesus look for evidence of some collapsed bank. But there was an attempt in 1609 to return to 100% reserves. It's called the Bank of Amsterdam. Very famous bank and they maintained reserves for a number of years. In fact many historians, many economists believe that they scrupulously fulfilled the commitment to have 100% reserves for 150 years. Now there's some dispute about this and some historians believe that they actually, the Bank of Amsterdam actually, surreptitiously made some loans to the East Indian Company from their vast pool of deposits. In other words the Bank of Amsterdam as much as they tried to maintain 100% deposits again succumbed to the notion that they should loan out this money. And the man who learned about that was a guy that was on the lam from the law, John Law actually. He had killed a man in a duel in his native Scotland and had been tried and been found guilty and they were going to hang him for murder. So he's able to escape and he was a theoretical thinker on monetary issues. He traveled around Europe and he actually went to the Bank of Amsterdam and he discovered that the Bank of Amsterdam had made this loan to the East Indian Company. And as John T. Flynn writes, law perceived with clarity that this bank in its secret violation of its charter had actually invented a method of creating money. So John Law really was the Keynes 200 years before Keynes was even born. And John Law went throughout Europe as he gambled, he partied every night. He was a tremendous gambler, made his money that way. But he was constantly seeking a government to try his system of creating paper money. And he finally found that country in France in the early 1700s. He started a bank called the General Bank. And of course he was smart enough to own it 25% by him, 75% with the King. So he cut the King in on the deal and away they went. He created money, vast forms of money. He started other companies which became the Mississippi system. Of course ultimately within two years of the system he knew he needed to make the General Bank the Royal Bank. He needed government force to keep the system in place. But ultimately the system collapsed. And he did every thing he could by decree to keep people from moving their money from the Royal Bank into gold and silver. He confiscated gold and silver. He did all he could to keep the system in place. But eventually an outraged French public forced the regent to place law under house arrest. And he in fact died in near poverty. In fact the Mississippi bubble, the bursting of the Mississippi bubble was so immense. And the loss is so heavy that it was considered a faux pas in France to even utter the word bank.  Now I want to fast forward very quickly to the United States and how banking in the United States is deteriorated over the last 50 some years. And the reason I'm wearing this fancy suit that I had made in Hong Kong by my Taylor Sammy as opposed to my American Taylor Joseph A. Bank. But bankers used to wear suits. They used to be very prim and proper in the 50s. And that was about the time actually at the end of 1954 National Citibank which was a predecessor to today's Citicorp. It had $6.3 billion in assets of which $5 million was lent out on real estate loans. Only $5 million of $6.3 billion.  And while all loans were only $2.3 billion, in other words their loan to deposit ratio was only 41%. So in the 50s despite practicing fractionalized banking in America bankers were pretty conservative. They wore a suit to work and they were very tight with credit. And they would certainly not make loans from deposits on long term assets such as real estate or not very often anyway. Now when I started in banking in 1957, 51% of all loans with US banks were real estate loans. It's a huge change from less than 1% of loans being made on real estate. In the 50s by 40 years later over half were made on real estate loans. Of course in 1997 at least when I started bankers were still wearing suits. But in the early 1990s and early 2000s that's when dressing casual during the week became very prevalent. And I know at the bank that I worked at we started wearing suits four days a week when I started. And of course in Las Vegas it's hot so you can create all kinds of reasons not to wear a suit. But as we made more money and we thought we were very smart because all our loans were paying off and the real estate bubble was going great. We didn't figure we needed to dress up to do this anymore. So first we had casual Fridays. Then we had casual every day in the summer. Summer being defined from May to October. Well then we redefined summer. Summer began in March and went all the way to December. Which means we dressed up for two months out of the year. Then we decided we can dress casual every day except board meetings. When the board showed up we should probably dress up. But then by that time things were going so good that we didn't care what the board thought. So we dressed up. We had casual day every day even during board days. And then casual wasn't enough. It was casual except for Fridays and then you could wear jeans. Of course the next thing that happened unfortunately is the bank was seized by the FDIC and everybody was unemployed. So presumably they could dress casually every single day. By the end of 2008 the loan deposit ratio for all banks. And remember back in 1954 National Citibank had lent out 41% of its deposits. Still very liquid something that Guido mentioned. By 2008 the loan to deposit ratio for all banks was 87%. So virtually you take all your deposits and you lend it out because it's very very profitable. And by the end of 2008 60% of all loans were secured by real estate. So what we have is very casually dressed bankers lending out all their deposits on real estate loans. And it was good while the boom was happening. In 1991 total bank assets were 4.5 trillion. By the end of 2008 those bank assets were 13.8 trillion. Essentially tripling, more than a tripling. So you might assume that gee there was a lot of savings. Americans must have been saving like crazy if bank assets were going up that far. But actually the savings rate fell from 7% to negative half a percent. The peak of the housing move in 2006. So it's rebounded somewhat since then. And now we have this annoying parade of Keynesian now complaining about the paradox of thrift right now. But we can see that this wasn't savings that were driving these bank loans and bank deposits. It was actually money being created out of nowhere through the banking system. So nobody was saving, casually dressed bankers were making all kinds of loans and being paid like used car salesmen. And as with the help of the Fed expanding bank assets out of nowhere. And this was all based on real estate values that were essentially as we found out later to be an illusion. I saw Donald Trump recently on television. And he's telling the story about old time mortgage bankers earning a small salary. And the only bonus they'd receive is a turkey at Christmas. Around holiday time. But in the last few years he said bankers have been on commission. Some of them make $50, $60 million a year. They don't even get paid when the loan pays off but when the loan is funded. Well that's exactly right. That's the way we were paid was on commission when things got hot. When I started in the banking business you would get paid a small salary and hope for a turkey at the end of the year. But lenders went on commission. And Tom talked earlier about Robert Morris, the evil Robert Morris. It's funny when I started in banking there's actually a trade association for bank lenders. It used to be called RMA, the Robert Morris Associates. And because Robert Morris had financed the revolution according to the pamphlets. And I did a little digging and of course I heard Murray Rothbard give a speech about the evil Robert Morris and the fact that the revolution actually financed Robert Morris, not the other way around. So I wrote this dandy little article about Robert Morris, the evil Robert Morris. And I don't know if they said anything to do with it but within a couple of years RMA changed their name. They were still RMA but they called themselves Risk Management Associates. But again that's kind of silly because bank lenders weren't addressing risk at all. They were just shoveling depositor money out the door as fast as they could. So instead of making a salary and being careful with loan dollars bank lenders began to be paid on commission. Banks wanted real estate assets, they wanted loans on their books, they wanted to grow. And so when I started in the business it quickly reverted to being paid 10% of your loan fees. And you didn't get paid when the loan was paid off. You were paid your bonus when you initiated the loan, the loan was funded. So you had every incentive to seek out loans and make sure they got boarded. Eventually all the banks in town paid bonuses. Everyone was on salary plus commission and eventually portfolio maintenance was added to this where at the end of the year you got a certain percentage of the loans outstanding that you had in your particular portfolio. And some banks even paid as high as 12% commissions on loan fees. Department heads would earn an override on their employees under them so they might earn 2% of the loan fees generated. So everybody was after loan fees and everybody was after loan generation. And nobody was concerned about loans being paid back because in a bubble high tides lift all boats. Whatever silly loan you made on the book there were plenty of greater fools to come in either refinance the loan or the property would get purchased. So there was no great fear that too many loans would be made. There was tremendous fear from bank management that they would actually lose loans, that loans would pay off and they couldn't replace them. There was that constant fear that actually your bank would shrink. That would be awful. And so that's why those incentives were there. Now of course that's all changed with the bust. I think that the price of bankers is going down. And I think they're going to go back to making fairly modest salaries and potentially a turkey at Christmas. But the days of big commissions I think are over. But that's what's led to where we are today. And I know that we've been enjoying the lap of luxury here in Hoppeville. So you probably haven't kept up on the number of bank failures in the United States. But there were three more over the weekend. So we're up to 36 banks have been shut down this year. One of them is of note. Two are in Illinois and they're relatively small banks. But one is called Bank United in Florida. It's a $12.8 billion bank. And it was closed actually on a Thursday, which is unusual. Banks are generally closed at five o'clock on Friday. But Bank United in Florida was closed on a Thursday. They were turned around and sold immediately to Washington insiders, Wilbur Ross, the Carlisle Group, and Blackstone along with a few others. And they're going to inject $900 million into this $12.8 billion bank. So you can rest assured that the beat goes on. The insiders will pick up more of these banks. And it is estimated the FDIC fund will lose $4.9 million on this transaction. They do have a loss sharing agreement with the new group that is buying it. But the Wall Street Journal estimates that the FDIC or the taxpayer, if you will, will absorb all the losses. Now through all this bank lending, we've seen, as Austrian theory would tell us, we've had numerous malinvestments financed. And the most famous one that's hit the internet lately is Guarantee Bank of Austin. Recently it made YouTube that they demolished 16 new and partially built homes in Victor Valley, California. I don't know if you've seen that video. But these were perfectly good. There were four completed homes and another 12 homes that hadn't been completed. And the cost of completing the development was higher than what they could ultimately receive by finishing the homes and finishing the development. So they just went ahead and knocked them down. The bank did. And these were homes that sold from $280,000 to $350,000 in 2008, probably much higher at the height of the boom. And so this Victorville is a bedroom community outside of Los Angeles, about 50 miles away, which sounds like a long ways away, but in LA that's a fairly close bedroom community. So here we have banks that shoveled out money to real estate developers to build homes and a few years later it is more cost effective for the bank to turn around and just knock the homes down. This is not going to be an isolated case. Nearly 250 residential developments in the state of California have been mothballed, if you will, totally 9,400 homes according to one research firm. So that's one example of the malinvestments. But the next shoe to drop, in my view, is commercial real estate. This would be income property, shopping malls, office buildings, potentially casino projects, in fact. And this is where many of the community banks, smaller banks, regional banks have really made their money in the last few years. There's 3,000 banks and thrifts that have commercial real estate loan portfolios that exceed 300% of their capital ratios. So a heavy reliance on real estate. You know, in Bank of America, which is considered too big to fail by the Obama administration, just a couple of the projects that they have lent on. They're the lead lender on the Fountain Blue project in Las Vegas. This is a large hotel and casino, and of course they had intended to sell condominiums. That project is essentially stopped. Bank of America actually has funded two office projects in Buckhead, which is a suburb of Atlanta. Each of those loans is $100 million. And those projects are going to be completed with no tenants in sight. Speaking of Atlanta, there are 35 new condo projects in that city that will provide a 40-year supply of condo units at the current sales rate. So there's plenty of real estate pain to go around. And we'll see how the bigger banks weather that.  But big mismanaged banks get federal money. And with these subsidies and bailouts, the big banks get larger and live to fall up another day. And that's essentially what will happen. But Guido mentioned the equity of some of the big banks. And B of A actually has a capital ratio of 3%. So their leverage is essentially 33 to 1. Wells Fargo's equity capital is 3.7%. Regions Bank has a capital ratio of 5.4%. So even though some of the bigger banks don't have as great a real estate concentration, they certainly have very small equity capital ratios to protect them as this onslaught of defaults in the commercial real estate arena come home to roost. But I would tell you community banks, most of them have real estate concentrations, especially in the sand states and the sunbelt of 80 to 90%. We all drank from the same trough, so to speak. So it's a very important part of the financial system is the community banks. You know, 28 to 30% of total bank assets, and that's where a lot of the commercial real estate has been done. Now you may have read that some of the bigger banks had good first quarters, that they're making money, everything's okay. And in fact, B of A announced earnings in the first quarter of 4.2 billion. However, upon closer inspection, equity investment income includes 1.9 pre-tax sale of the China Construction Bank, and then they had a non-interest income of 2.2 billion in gains related to market to market adjustments on certain Maryland structured notes as a result of capital spreads widening. So actually, when you take out all of that nonsense, they actually showed a loss. So, and the other big banks are no different. Andrew Ross Sorkin wrote in the New York Times, with Goldman Sachs the disappearing month of December didn't quite disappear. J.P. Morgan reported a dazzling profit partly because the price of its bonds dropped. Theoretically, they could retire them and buy them back at a cheaper price. That's sort of like saying you're richer because the value of your home has dropped. Citigroup pulled the same trick. So we have all kinds of accounting tricks that really have created any sort of profits that have happened with the big banks in the first quarter. Of course, we can all be thankful that they were stress test. And Obama says that none of the big banks will be allowed to fail, and so everything will be okay. But a number of people questioned those stress test results. The Wall Street Journal reported that the stress testing was actually negotiated by the banks. They negotiated the results with the stress testers. And so it really calls into question just how much stress these banks could take. What's interesting is with all these failures, we've got so many banks failing that government watchdogs who by law have to review these failures. Any time there's more than a $25 million failure within a bank, they must be examined by the Inspector General. And that threshold is just too low according to the Inspector General. He testified the other day that his office had to do only five failed bank reviews from 1991 to 2007. They've already closed down 36 banks this year, and all of them will be over that $25 million threshold. And so his staff says that they just can't keep up with that. He would like to increase that threshold to $300 million or $500 million. And that also goes for closing down banks. There would be many more bank failures than the 36 if the FDIC had the staff to close down banks. In fact, I've heard that if they had the staff they would be closing down five to six banks a week. But they just don't have the staff to do it. So this is going to take many years to unfold. But the government has come to the bankers rescue, last fall's panic. The Fed wheeled out the money market investor funding facility, the asset bank commercial paper money market mutual fund liquidity facility. It raised the ceiling on insured deposits from $100,000 to $250,000, guaranteed new debt issuance of the banks, thrifts and holding companies that provided full insurance for any and all non-interest-bearing deposits. And the Treasury issued a blanket guarantee of money market liabilities. So as is always the case, when banks get in trouble, the government rides to the rescue with the idea of taking care of the poor depositor. But in fact, it props up the very banks that got in trouble. Now, Murray Rothbard pointed out that in the absence of central bank intervention, these bank panics would be very healthy. They'd be very healthy on a check on inflation in the banking system. And that would certainly be the case in this meltdown. As these assets are written down and as these banks fail, we would see the pressure of inflation would be greatly curtailed. But the Fed is valiantly fighting to reinflate. In fact, it's increased its balance sheet 140%, just to generate a 14% increase in M1 money supply. So the central bank has pulled out all the stops. Chairman Bernanke has done everything but to send out the helicopters, dropping bales of money, although he has said in previous speech years ago that he would be willing to do that. But Jim Grant from Grant's Interest Rate Observer estimates that the federal response to the current downturn is 12 times greater than that of the Great Depression. So we've seen central bank intervention like we've never seen it before. But some people believe that it's not enough. In fact, the Financial Times reports that the existence of a federal reserve, there's a staff memorandum within the federal reserve that makes the case for a negative 5% Fed funds rate. Now it's hard to cut rates below zero. It's very difficult. And I quote here, however, the staff research suggests the Fed should maintain unconventional policies to provide stimulus roughly equivalent to an interest rate of minus 5%. So imagine if they're able to unleash that kind of power. So although ostensibly it's been dodgy real estate loans that are bringing all the banks down, whether it be subprime mortgages or construction loans or land loans, whatever it may be, what it really is is the fraudulent nature of fractionalized banking. Now what Murray called the pernicious and inflationary domination of the state. That's the real culprit. Now when things go bad, the regulators always go into a bank and they say the bank is operating in an unsound and unsafe manner. But what is really unsound and unsafe is fractionalized banking, the lending out of embezzled deposits. Thank you.


Hello, KubeCon. Welcome. My name is Lee Calcote. I'm at layer five. I'm joined by Mr. Ken Owens. Who's at FISERV. We are, I keep interrupting Ken, but he's used to that. Apologies. So we are here to take you all through some of the initiatives within the Special Interest Group. SIG Network. SIG Network has a couple of working groups, one of which will be our focus today. And that one is the Service Mesh Working Group hot topic. So we'll do a bit of an intro and a deep dive. And we'll see if, if Ken will take us through what is SIG Network. Yeah, thanks. Thanks, Lee. So, um, you know, our mission statement in SIG Network is with an ever steady eye to the needs of workloads and developers who create them and operators who run them. SIG Network's mission is to enable widespread and successful development, deployment and operation of resilient and intelligent network systems and cloud native environments. It's really important and I have minds and I have a view of this SIG is that we want to represent, you know, the network develop the network guys but also the developers both in the application teams, in the business teams and also in the network and you know software design networking areas. And so we're really looking at a broad scope within the SIG. With this endeavor, we really do want to try to, you know, inform and clarify as our first goal. And that's important because, as you know, there's a lot of network can be a very broad statement and can mean a lot of different things in a lot of different context. So we're very collaborative and we want to be able to kind of work with different areas and different SIGs and different groups within our community to kind of help bring some of the cloud native networking aspects into the interview and into clear focus. We assist and attract projects. As we'll go through in a few minutes we brought in really interesting projects and we're really excited about how much we've grown in the last couple of years. And we also want to, you know, basically have as part of the CNCF charter we want to be impartial of the different projects. We're not kingdom makers here and so we want to, you know, it's definitely fine to have different service mesh technologies together and different network technologies being represented here in the SIG. So just a little bit about what we've done over the last several years.  C&I was the first thing that we worked on as a group before we were a SIG. We were just kind of a networking work group at the time and Lee probably had some fond memories of the work group times together, the six of us, right? And, you know, since C&I we've worked with Core DNS, Envoy, GPRC, Linkerd, Nats, a friend of Cisco brought in, you know, some network service mesh discussions of the open source project they have going on. It really helped kind of kick eyes off in the beginning of 2020 at KubeCon Europe with, you know, some additional projects like G&I, G&E and Contra and, you know, the service mesh interface you hear more about today. And then we ended the year, you know, working with Chaos Smesh and Open Service Smesh and, you know, today we're excited that we're, you know, looking at an ambassador project in Mastery Ingress. We're looking at, you know, K8GB, we're working with Mastery and with service mesh performance, which we'll get into more a little bit later in the presentation. And on the horizon, we have a couple of things with Submarina is sort of the main thing we want to look at on the horizon. So we have a couple of working groups that you kind of, you know, as Lee mentioned earlier, the biggest one that we're working on right now is the service mesh working group. But we also have a very interesting working group, the Universal Data Plane API. Both of these working groups are active and, you know, we invite your participation and you'll hear more about that as we go through the presentation today. So we do have a couple of white papers out there. And we have several presentations, but the main one wanted to point you to is moving beyond ECTP, the surveying the state of layer seven protocols and the cloud native ecosystem. And so there's, you know, a lot to get involved in a lot to do and hopefully what you see today as we go into the deep dive and I turn this over to Lee, you'll see that there's a lot of interesting topics, a lot of interesting conversations we want to have. And in the community and you know that you'll want to get engaged and we'll make sure you know how to do that. So with that I'll turn it over to Lee. You know, Ken actually that the last presentation that you were just highlighting that while we have, you know, while the group is large and networking is vast that that presentation might be familiar to some as it was subsequently presented as a keynote at last last cube cone as well so I was just recalling that I'm, you know, speaking of recalling things like late breaking news earlier just a few hours earlier today was that ambassador the emissary ingress can we that project has been under review in the SIG for maybe longer than maybe let's not let's not talk about how long it's been there a while it's been under diligence and underwent a name change. It's in it's so you know congrats to that that team. Like, like, Ken was saying, the service mesh working group has a few different initiatives going on. The initiatives are interrelated. They are. Well, the focus is on service matches is a lot that that a service mesh provides a lot of ways that that you can use them. And that's part of the focus of the group is to identify patterns in the way in which users are using services, trying to curate a collection of those. At the same time we're also taking advantage of the CNCS labs. There is not an infrequent question that people will ask is, you know, inquire about the overhead of a mesh or the some of its performance characteristics and, and they, you know, I don't know that, you know, one of the initiatives that's within the group here is, well, it's to leverage the labs to help answer some of those questions. Some of those, those answers are point and time answers about a particular mesh or a particular type of workload. We've been fortunate to what Ken had said about some of those that have come to participate. One of the collection of participants recently have been from from Intel, and if you know, historically that that organization has a long standing focus on performance. And so they're bringing some of their their skills to practice here, which is nice so hopefully we'll see as a matter of fact I think they have a talk as well at cube con, and we'll see some of the you can find some of those results. So actually, if you're what if you're in chat right now, I'm asked for the link, we'll send you the link. So, of those service mesh patterns, though, there has been a collection of about 60 that have been identified, they fall into different categories. There's a fair bit of work that goes into really refining these in detail, and that work is far from complete. There's a there's a first segment of the first half of the segment of 30 is being iterated on and being discussed. There's also there's also tooling that's being worked on in context of the service mesh working group, we're going to talk about some of the tooling, but some of that tooling helps people run those patterns so if you're, if you're reading through the pattern and saying hey hey that's of interest, and you're wanting to use a tool to test it out. We'll talk, we'll talk about that tool here in just a bit. Part of what makes the working group fairly interesting is that there's a number of projects the ones that can had listed off that are. Well, some of them are service meshes themselves. Some of them are emergent standards or specifications that help. There's this interface with service meshes in a, in a standard way and so the first specification here is service mesh interfaces SMI. It's kind of interesting that I look at the statement here the very brief blurb about what SMI is and reflect on some recent conversations that we've been having there and the recent conversations have been about that last on these bit is that when SMI was first announced as a project in a very Kubernetes centric and and focused, and there's been an expansion of that. I don't think we haven't formally concluded but there's clearly much interest toward, toward helping SMI's services that are not running in Kubernetes but are running on the service machine so SMI is focused as a standard for how to interface with service mesh functionality in a uniform fashion. Similar to this as an adjoining specification, there's an SMP service mesh performance. There's a specification that provides a standard way of describing the performance of a service mesh. Some of that is just to be able to articulate that performance in a concise way to do it in a uniform way in which each of the service mesh projects are are beginning to engage with the specification. And it's our hope that through, well, through the assistance of the service mesh working group that each of the service meshes will be able to report on their performance with each release under a set of different scenarios and use the same standard to do that. So, there's there's a little bit in there. The, this third specification is, well, also just looking at this like and reflecting over the last like two weeks now there's been, I guess let me first explain Hamlet and then explain some recent news and so Hamlet is generated and put forth largely by VMware but in collaboration with Hashicorp and Google and begins to define really like to put it in my own to concisely I guess is to is really to define a set of interoperable service catalogs. So like to the extent that you're running multiple meshes, whether they are homeo genius or or heterogeneous types of service meshes that inevitably you're going to want those workloads to be able to interact between the different service measures so you're going to want it to be able to federate them and so that's the crux of the focus of this specification. Here recently there's been, well there's about three areas that that multi cluster kind of Federation discussions are happening there's some of that going on within the Kubernetes. Well, I forget the name of the SIG but the there's multi cluster being discussed there as a new API, a little bit of that being discussed in service mesh interface, and a little bit here in Hamlet and and Ken will you know quickly tell you that that's a great example of what this SIG network is about and it's from this vantage point that we would be able to identify some of those. You know that duplicities is the right. The correct word exactly but to be able to make sure that individual efforts are at least aware of one another and can, and can collaborate and so we're so if you're so if you're listening right now. This is a good place to come in and work those through a one of the so based on the fact that there are many meshes out there. There are a number of them in the CNCF that and whether they're in the CNCF or not, there is those that have chosen to implement service mesh interface. And just like any specification. You need some tooling to be able to verify the compliance of that spec. And so, in this case you'll need tooling to. And that works with each of those eight different service measures that implement SMI. And for the it to flex each of the four specifications that SMI currently has. There's a fifth that's being discussed now. And so, if you're familiar with son a boy of the. I wouldn't say of the Kubernetes project but son a boy to what son a boy is to Kubernetes this SMI conformance initiative is that to to SMI. And so there's some early reports actually this would be the first time I think that these reports are being shown reports of it's about is it about five, yeah about five different service meshes and their, their compliance falls with respect to these different right now it's just three different of the SMI specs. We're seeing a lot of red, and there's good reason for that. And that's because the SMI spec, a new version was just released about a week ago. And so, there was a breaking change it's in terms of that that spec and so hence part of the red here just for the moment. So, so we it's our hope to get a few more of the implementations up here, get get them participating in the tests, I'm even more directly. The tool that's being used is is measuring. And it is one of the tools that can and mentioned a moment ago it's up for up for adoption into the CNCF. Can if you oblige me if you were to click on that that measuring logo, there is measuring implements the these SMI conformance tests, it also implements the service mesh, service mesh performance specification. And it kind of does so across any number of service measures and so on that service mesh performance specification though on the next slide. We'll describe that a little bit more this specifications also up for review and donation to the CNCF. We articulated earlier as a way of a standard way of capturing and describing your infrastructure can you know it's characterizing your service mesh performance. It does that the spec directly does that it also facilitates some other interesting things it facilitates, maybe benchmarking of a given mesh over time and how well it's doing from release to release. It also facilitates comparisons between service measures to the extent that that's apple apples to oranges to the extent that that's those are comparable. It also facilitates, well potentially a new performance index maybe a new concise way of articulating the, you know how well how fast or efficient your service mesh is running. I think it's this next slide that talks about mesh mark, which is an emergent. Well, it's an emergent ruler or yardstick for it's an emergent index by which you would. And like I was just saying like advice, concisely convey how well your system is running. It's really quite complex, maybe harder than I think some of the folks that had gotten into it had initially considered what's been fortunate here over the last month or so is some new and others have joined the initiatives, a couple from Red Hat some from Intel, and, and are hopefully helping define a new a new way of describing service mesh performance so maybe I'll leave it at that and leave you with the cliffhanger what that ends up looking like. You're seeing some of the, you're seeing each of these initiatives overlap a little bit, and it's been long been the intention of the working group to get some of these projects. Well, that that were generated inside the working group into the CNCF. I don't know that that's the intention for the maintainers that are working on get Nighthawk, but it becomes kind of necessary. This particular initiative becomes necessary to the extent that Nighthawk is quite a capable piece of software. And if you're saying night what then I'll quickly tell you that that Nighthawk is more or less a sub project of Envoy, and maybe at some maybe at some point it won't be a sub project will be, but anyway it's a performance characteristic tool so it's a load generator. It's quite quite capable it's written in C++ it builds alongside the same build tool chain is as Envoy. To be able to facilitate some of the tests and the benchmarks that are being performed within SMP. This project get Nighthawk is bringing together is making it easier for people to get to get Nighthawk into the hands of the masses, so to speak. The collaboration with Meshory and Nighthawk will, well, it will advance that even more but it will also hopefully advance a little bit of the state of the art around some of the research that's being done within the working group. We've got a couple of universities that have participated in these discussions. I think our most recent one was a professor from NYU. I'm interested in trying to help advance the studies that are going on and really need tooling like this to be able to do it. It's pretty painful to see researchers, you know, like, try to pull together scripts and various things to like spending half their time and just trying to get the environment working when, when there's some easier to use tooling there that they can just go take and run their tests and so. That's the large part what get Nighthawk is about. There's an adaptive load controller in Nighthawk itself that that may change the way that those that are running service messages think about optimizing and tuning their mesh. So, exciting things in the project. That was an awesome job of describing so much of the great efforts we have going on in the, in the, in the six. So thank you for that. We, we kind of wanted to end the presentation asking for engagement and ensuring that you, you know, we're asked to engage it. We always hear that, you know, if we just have asked for them to, you know, people for being engaged with us we'd have more engagement. So, so we're going to have a call for engagement, you know, call for participation. We have meetings twice a month. They're on the first and third Thursdays of every month at 11am Pacific time. We have meeting minutes that we keep track of as you're welcome to kind of catch up on some of the things that we've talked about and everything that Lee mentioned there's you know links in this deck and there's also links in the meeting minutes to some of the projects directly. I definitely would love you to connect with us on Slack. We have a, you know, SIG network is our Slack channel.  We have, you know, my name is develop what list.cncf.io. With that, I, you know, I thank you very much for your time and I thank you Lee for, for co-presenting with me I think this has been a really useful and helpful, you know, use of the description of what we have going on in SIG. That's a lot. While, while Ken and I are sitting here fielding questions in chat. I've got a question. Can you were just saying, there's a call for participation people can jump into the meeting minutes jump into the meeting. I have a question. Do, do, do, do those that show up. Do they need to belong to a CNCF member company or do they need to be platinum sponsor, you know, like, what's what's the entry price into the to come and Swiss bank account. Yeah, that's a great question because that there are a lot of, you know, we do hear a lot of people worried about and getting engaged. We are, you know, first and foremost an open community and we welcome welcome your engagement and your involvement without, you know, being a member company or paying any sort of fees to to get involved and you know, unlike, I guess one of the concerns people have is if you don't pay for for entry how how good is your outcome and I think our outcome is awesome so I think you have to worry about the effort and the, you know, the desire that we have and the work group would definitely drive the right outcomes for the, for the community. That's a great question Lee. I appreciate that. Thank you so much for taking us to this can. I guess we'll, we'll see everyone. Next Q con is that the hope so hopefully in person this time.


Well, hello and welcome to Understand Men Now. I'm Jonathan Asley of JonathanAsley.com and I'm so excited to be shooting this short video for you today. Our topic, the five signs a man will fully commit to you. You need to know this before our first date. All right, really quickly, if you're new to my content and this resonates with you and you're a single woman looking for love, check out the link to a free discovery call to see if working with the coach is right for you. That call is with me. All right, we're gonna talk about those five signs he's ready to commit and let me just tell you, you need to know this before our first date. Okay, I'm just gonna be candid with you. I've just observed a lot of children dating, a lot of children dating and what I mean to say is people who are legally an adult by age but emotionally they're children. And I want you to visualize, I'm just gonna do a really quick circle. There's a circle like this, one here, one here and one here. And the circle here is child. The circle here is adult and the circle here is parent. And oftentimes when you're dealing with an emotional child in relationship, you have to become the parent or vice versa. If you're the emotional child, they have to be a parent in the relationship for it to work. And I'm here to encourage something different. I'm encouraging an adult way of looking at relationships. That's why I wanna recommend a new book to you. All How To Be An Adult In Relationships, How To Be An Adult In Relationships by David Rico. David Rico. I just got this book. I'm just getting into the depths of it. It's not where my content came for this video but I highly recommend checking it out because so many of you ladies are dealing with men who are in child mode and so many of us men are dealing with you ladies that are in a child mode and I wanna shift that to an adult mode because adults operate differently in relationship. They operate from a place of intentionality, of a purpose. They actually recognize the value of a relationship and they make a commitment to it. So what are the five signs that they're gonna be able, if you're meeting a man who is an adult, what's the five signs? Well, the first sign is the most obvious one. There's mutual chemistry. There's mutual attraction. There's a sense of you're into each other and usually you know that by the first, second, or third date so that's pretty easy to determine. It's a lot harder if that isn't there. In fact, a lot of people have been encouraged to date if there's no chemistry. Look, I have a real simple rule of thumb. If there isn't an energetic or emotional connection by the third date, it's probably never gonna get there. I've known so many people who have gotten married to people that they never had chemistry with only to have the relationship bomb out, okay? Number two is blendable lifestyles, blendable lifestyles. Here's the thing, for people in their 20s and 30s, their life is like a blank sheet of paper. It's so easy to build a life with another human being especially when the common purpose is raising a family, having children, raising a family but it's a lot different for those of us in midlife and let me just say this, at midlife it's really complicated to blend lives together. This is why it fascinates me how many people enter into relationships with people's whose lifestyles are completely different. One person is a morning person, one person's an evening person, one person loves to exercise all the time, the other person is a couch potato and I'm just picking a few things right here. I mean the list can go on and on. Now, I know a lot of you ladies, well if you love each other we'll just magically work out. No, your lifestyles will have to eventually blend and what I just shared with you were a couple base things about lifestyle. What about your work schedule, where you work, your children, that sort of thing is if it's unable to blend together it's gonna be very problematic. Number three, shared values and a shared vision. This is critically important. Esther Perel talks about this in quite a bit of her work in her book, Mating and Captivity but I highly recommend you understand that without shared values and a shared vision in your life it's gonna be hugely complicated to fully commit to another person. So this is why it's so important to ask those value-based questions early on in the dating practice. If you need some support on that that's what I do as a coach. Check out the link to a free discovery call. That's my area of expertise is helping you vet men and to vet for those shared values and a shared vision. Number four, and this has gotta be the hardest thing to recognize early on, is emotional maturity. Is emotional maturity. As I just said, most people are operating as children and the reason being is they most likely haven't established a daily self-love practice. Let me repeat that, a daily self-love practice and that includes meditation, that includes personal development, self-help and spiritual work as a daily part of their lives to establish that emotional maturity. This is why I wrote my book, What the Heck is Self-Love Anyway? I gotta scratch my nose by the way. What the Heck is Self-Love Anyway? By Jonathan Asley, that's the back cover. It's designed to help you begin that daily practice because without a daily practice for yourself and with the person you're with you're gonna most likely be in that child mode of relationship and I want to get you to step into that adult mode so you don't have to be in parent mode to make this relationship work. And the fifth and critical piece and this is really one of the hardest things to establish is that the person you're with is commitment oriented, they're commitment oriented. The reality is is most people today are seeking casual relationships. They're seeking what they want is companionship, connection and sex without any real commitment. And I'm not talking about monogamy or saying you're not gonna date others but a real commitment to the relationship. That's what an adult does. They say, I am committed to exploring this relationship. And if someone isn't in that space, if they just say, oh, I'm looking for something casual, I don't want anything serious, then you're setting yourself up for failure because without a commitment to the process, it's like, would you wanna be with a guy who's not really committed to his work life? He's not committed to his children. He's not committed to his family. Would you wanna be with someone who's not committed in those areas of their lives? In their lives, no, you wouldn't. Well, then you want to, at least this is my invitation for you is to choose men who are committed to the process of wanting to establish an adult relationship. All right, is this sinking in? Is this resonating? Please post a comment. If it is, I wanna hear your thoughts. I wanna hear your questions. Did these five things make sense? Post a comment below. All right, I'm gonna wrap up this video as I always do.  I'm gonna reach into the camera and give you a hug of love if that's okay. I'm gonna ask you to turn to someone, a friend, a pet, a pillow, or even a teddy bear and give it a hug of love because hugs are a great source of love and we can all use more love in our lives. I wanna thank you and say bye-bye.