From Oracle to AI Ops: Kellyn Gorman’s Playbook for Future-Proof Data Teams

Hello and welcome to Asking Good Questions, the podcast where we dig into the future of business by, well, we stuck it in the name, asking good questions. I'm your host, Edward Roski, and today's guest brings a really unique, powerful perspective to that intersection of data and technology and where it's going. She's a longtime engineer, a database architect, a speaker, a mentor, a multi-time published author, one of the few women in the world to actually belong to the Oak Table Network. At last check, it was 6, and we're talking to one of them. From her early Oracle days to leading AI at Silk, to her dual role as advocate and engineer at Redgate Software, ongoing consulting she's been doing, she has been reshaping how data systems operate across industries. On a personal note, I'm originally from Portland, Oregon. I was born at Kaiser Sunnyside out there, and I spent some time living on a floating home on the Columbia River, and now I I have someone on the show who can actually relate to that experience, and I am thrilled to welcome Kellen Gorman to the show. Hello. And I can't believe that, you know, the difference between floating home and barge and houseboat, because no one seems to figure out where I live. They're like, so your house moves? Like, no, it doesn't. No. Was there a flash flood and your home floated away and somehow— so Kellen, I wanted to start with something I, I love about your story. A lot of your biggest breakthroughs, and I can personally relate to this, have come from accidental specialization, working on those problems that no one else wanted. Falling into AI, stepping into DevOps even before it had a name. How did that happen? How did it shape the way you look at technology today? It's a complex answer because, one, I am a woman in tech, and I don't take a lot of, I don't know if it's advice or instruction well. I'm a handful, I know it, and by doing the things that nobody else wanted to do, I'm usually kind of left alone. Just do what needs to be done. And I am a doer. I don't like over-analyzing things. I just want to investigate, find out what needs to be done, get it done. I ended up doing a lot of the things that nobody else was interested in doing. I ended up doing a lot of the technologies that no one wanted anything to do with. What happened is that because I did have, thank my parents, a good work ethic, that I got things done right, that people started to rely on me and they would bring me the challenges that they thought were going to be a little too much for other folks. My first database, I did not understand why no one else raised their hand. I really didn't. And then I got in there and found out I had the largest SQL Server 7 west of the Mississippi. And I realized why everybody was running as fast as they could from it. But I learned, I learned very quickly and it set me up for a career for very large databases that I've enjoyed to this day. So, You've spent years in that database architecture, that infrastructure role. You just mentioned SQL Server, Oracle. You've also used Exadata, DevOps tooling, you name it, you've probably touched it, dealt with it, optimized it, and maybe even written a book about it. But in recent years, you've become a driving voice in figuring out how to integrate AI into what we do around areas like relational data, high I/O systems. How has AI changed the role of— let's start with being a database engineer. So, People would say, well, AI is now here and it can do it all. AI can do things. There's no question about it. It's pretty amazing, especially in the messy world we live in. But it needs guidance. It requires people who understand things at a very, very deep level, and experience cannot replace what AI is learning at this point. It just can't. It's figuring it out, but it can't do it for the deep technical data specialist. They can work hand in hand with it. It is your collaborator. Can it replace those folks? No, it can't. And especially with the softer skills that we have, the vision, the leadership, they absolutely need us for that. For newer people coming in, it's a little harder. It's, it's been a little bit of a longer road. Many of them may come in and what they're learning may not kind of translate into the requirements for what they're seeing for jobs. And they're being told that you need 10 years of database experience, and this is a starting position. And you're only going to have this salary and you need to know AI. And it seems like a much longer road. AI is changing the landscape. Is it changing it for the better? That one is a whole nother ballgame. Yeah, we could do a couple-hour talk on, is it going to leave the world a better place when it's done? But I agree with you. I keep hearing that X technology will replace either Y technology or Z people when it's done. I got my start in tech in S-Base in 1995. And the first sentence they would always say is, this will replace Excel. Excel. Access literally stands for Extended Spreadsheet Database. Once you have this, why would you need Excel? And then every single thing after it was supposed to replace the prior technology. And there are more people employed in all those different areas. Technology can even be democratizing, like it can, it can bring it to more people and remove a lot of those barriers to entry. And I, I don't know how much of that is intentional. We're going to learn from some successes. There's going to be things AI does really well and there are going to be some things where AI fails miserably. And then there's that third category of the things we don't even think will go down either path. It's just something unexpected. Expected is going to come out of AI. In your career, can you give me an example of something unexpected that, that ended up being transformational for good or for bad? Can you think of anything? That is a hard question. There's been so many transformations that I've seen, but one that really hit me was that, again, the relational database was going away. And you used that example of Excel just now. And the way that I explain this to folks is they're like, we're going to replace all relational databases with MongoDB or Cosmos DB, a document database. And I'm like, you've got Microsoft Word, Microsoft Excel. Just because you can embed a table from Excel in Word, are you going to get rid of Excel now? Well, no, that's stupid. Then why are you getting rid of your relational database? It cannot replace it. You're not going to just throw away your hammer to build your house because you have a screwdriver now. You need all of your tools. You need all of your tools in your tool belt. Every time I hear that document databases are replacing our relational databases, our traditional RDBMS, it doesn't make any sense to me. Because as much as I think there's a value for document databases and unstructured data, there's also value to structured data. And when we start looking at like transactional systems, that's what's feeding most of what we have for analytical systems. I'm like, If you don't have transactional coming in, you don't have analytical going out. We need to comprehend our workloads. We need to comprehend that a database is not just a database. One database is not like the other database. Use the right tool for the job. And I think that's probably the one kind of epiphany that I don't understand people do not get. So, when new technologies come in, let's use AI as the most current example, but if you have a better one for me, I'd love that. Oh, AI solves all problems. Come on. Exactly. Yeah. By Tuesday, we're not going to need humans anymore. And I think Wednesday is when the AI is scheduled to kill us. Yes. Admittedly, everyone who's ever predicted the end of the world up to this point has been wrong, but I have a chance. I could be right. When you're driving AI change, I've heard a lot of what you've heard about. This new technology replaces this old one, or if we do this thing, it's shiny, it's new, it's great. Let's go do it. Are you seeing that drive to implement AI come from the technology side of the house? Are you seeing it being driven by the business people? Is it market? I don't know, peer pressure? Oh, after AI, let's all try heroin. Where is the AI need coming from in what you've seen? Right now, for most organizations, it is being driven by their annual bonus and management saying you must have an AI product. That is in your annual goals that you have to meet. I've been watching this in just about every company. Big and small that I've been part of, you need to have AI as part of your product. And when you walk into a customer, they're like, what do you have that's AI? And the customer better hear something back. Because of that, we have AI built into everything. Does it make sense? Absolutely not. There are products— I just opened up something just a minute ago that was part of a Microsoft product that I said, if I have to look at Copilot one more time in this one product, I'm going to kill somebody. Because it made absolutely no sense whatsoever. It literally was in the way of the dropdown menu that I needed to get to, to use the product. And this is not just Microsoft. I talk about my Apple phone and the image generator. Every time I go to Settings to get my Apple headphones to connect, it would have the image generator in the way and say, "You need to install this. You should use this." I don't want it. I ended up installing it and then uninstalling it. It would stop prompting me. And this is where we're at. And I know that there are employees behind this that were said, if you don't create this, if you don't create some kind of AI solution built into the product, you're not going to meet your objectives for the year. You're not going to get your— it's usually driven by objectives that I find for the year to meet their annual objectives to get their bonuses. Well, in any, any new technology, any drive to change is going to be driven by the humans. The computer is not going to come up one day and go, you should make the following 10 changes. Oh, by the way, I did them for you, right? The humans are going to you're going to have to buy into that. And I think that there are definitely people in the industry that need some senior-level advice. You and I are to the point in our career where we can— Yes. Yeah, critical thinking. It's the next big thing, mark my word. But mentoring, community, including people in all that, like how do you turn that focus from the technology to more of the people side and make sure they're critically part of that conversation? Companies need to stop hiring just yes-men. I'm going to say that straight out. I have seen that happen over and over again, that we may have leaders that, as, and I came from organizations that had incredible leaders, and I'm going to use that term leaders, not just managers, leaders that made decisions for the right reasons. They would say what was on their mind and talk about the things that were critical to the business, disagree with things. That were critical to the business. That is a good leader. People that had vision. Now, not all leaders are going to have vision. Not all leaders are going to make good decisions, but they should surround themselves with people who help make those good decisions. As those people progress in their career, they're going to be promoted out. They may leave the company, and then you need to move up, folks. This idea that everyone needs to move up may not be the best decision. We all know, most of us know, or have heard of the Peter Principle. There are a lot of folks that are at that Peter Principle right now in tech. I've been saying for about the last 2 years that everybody should be really concerned about being in big tech, that they probably should be going to small tech. That has been advice that I give my mentees. And they're like, why? Because we are in that Peter Principle cycle of tech where big tech is kind of on fire, and there are a lot of leaders that are making poor decisions or have surrounded themselves by yes-men that are making recommendations around technology that's just do what the other guy is doing. Just do whatever the boss says. Don't ask questions. Don't say what's on your mind. And that we make poor decisions because of that. You need to hear the people that are saying, "I don't know if that's the best idea. Can we talk about this?" Those are really essential. We do. We've got some issues right now. Yeah, I always felt that rather than surround myself by yes-men, I could probably just buy a mirror because that's cheaper and would tell me literally what I just said right back at me. I've always believed that if it ever comes down to two otherwise identical candidates, go for the one that gives a more diverse opinion. Because if you have 10 people thinking the same way or 10 people that can provide different perspectives, different backgrounds, different viewpoints, why would you not want tiebreaker goes to the person who brings the more interesting viewpoint, not the one that is identical to everybody else that's up there? What I've discovered is that is oddly not common management practice out there in the world. Why? What leads to that? Is it just easier if everybody agrees or— There's a sense of comfort when you hire somebody that has a point of view yourself, that does things the way that you do them. You're like, I'm going to feel comfortable leaving this in their hands. And that's not a problem. It's mostly just asking yourself, why do I have somebody that will give me a different point of view, and then make sure that you have that balance as well. This is, this is all part of diversity. This is all part of inclusion, of bringing in differing points of view to make sure that you're not having a blindside. I think that's really essential. And I've seen that over and over again. When I first went to Microsoft, as I was going through the interview process, I did not think I was the best candidate. I didn't think I stood a chance for the position that I was up for. I knew the previous person who was in that position. He had recommended me. I knew other people that were applying and interviewing for it. And I started asking them as we were speaking at different engagements and that, I said, hey, are you still interviewing for his position? They were like, oh no, they didn't. They're not talking to me anymore. And I'm like, are you still interviewing me? Why? I've never worked in analytics before in my life. Why? I'm a field DBA. Why, why are they talking to me? And what had happened is they started to interview me. The manager looked at me and said, "Kellen brings a very different perspective to this role. She can take us that next step and really marry her skills with the rest of the people in this team. They already have those skills. We don't need another person with those skills. We need somebody with different skills." And it worked out. It was a game changer for us. A lot of people was with Microsoft. And at that point, they were trying to figure out how to get more Azure projects. And I came in and 4 months in, I said, you need me to move the Oracle databases. What? You need me to move the Oracle databases too. They're part of the ecosystem. You can't just ignore them. They have to go too. And I started moving those and that's all I was doing. And I had an incredible manager at that time, Benny, that came in and said, show me, show me what you think we need to do. And he let me just build that out on my own. There was no role for this. There was no support for this. He supported me. He backed me up and I started moving them and all of a sudden I had Azure projects. He says, can you do that for your teammates? I said, sure. Started doing it for my teammates. And then another person from a global team came in and said, I want you, come here. We're going to make a role for you. And you're going to become the SME for Oracle and Azure. And it became something. And then it became a team and Tim, they said, do you know anybody else with your skills? And I was like, I'm married to him. And they hired Tim. That's how this became a thing. But it was through the leadership and support of true leaders that were able to see that vision, were able to trust that vision. And I don't think that's as common as we would all like it to be. Yeah. I look at, I'll go back because this company is no longer in existence. It's okay if I mention them, but I remember going to Blockbuster. Their headquarters was in downtown Dallas and I was going there to build them a store-level dashboard. This is 2004, 2005, somewhere around there. And because it was the available spot and I was working really closely with their senior leaders, I ended up on the executive floor at the Blockbuster headquarters. And I will, I will summarize by saying all the leaders look like they had a whole lot in common with John Antioco, the Blockbuster CEO. They probably all went to the same schools. They probably all had the same class rings. They probably all golfed at the exact same places. They probably all drove pretty similar cars. And suffice to say, they all looked a whole lot alike. They felt, why should we change? Because we're on top of the world. And you mentioned it, when you kind of get in people thinking the same way, there's a level of groupthink that kicks in. And they went from being monopoly where 98% of America was within 5 miles of a of a Blockbuster store to gone in just a handful of years. Looking ahead, if companies don't want to end up in that situation, is there something that leaders can do if they want to build a truly inclusive team, starting with the technical side, because that one quite often ends up skewed. So what is a step that they can take? There is a document called, and it's still out there, I know that you can find it, it's called the Care and Feeding of Your Hackers. And what it's really about is How to Manage Neurodiverse or High-Performance People, and it's a great read. It's a great read. I am also one of those that I strongly believe in doing the Gartner assessment, skill assessment, the CliftonStrengths, because it tells you how somebody performs and how best to manage them. I bring mine to any place I work and I hand it to my new boss and say, "Here, I come with your employee manual." I let them literally read it and go, This is how to get the most out of me. I can produce if you really let me do these things and understand where I will be tripped up if you do these things. That's really important. But also— Oh, go ahead. Oh, good. I was gonna say, I'm a big fan of StrengthsFinders myself. I love the idea of figuring everybody has individual strengths. And even if you only understand like the top 5 of them, it tells you how to magnify those strengths and not try and fix their bottom 5. To use a sports ball metaphor, they're not running out to the quarterback and going, wow, you blew that tackle. You need to spend the next 6 months on a performance improvement plan figuring out how to tackle better. They go like, oh, your pass was almost perfect. Let's make your pass perfect, right? That's, that's what their main job actually is. I love that you're, you're giving people the user manual and saying, this is a way to operate me at peak efficiency. And I'm unlike most people, I, I don't expect this from everyone. I embrace my failings, I embrace my weaknesses, and I let people know them. Do not put me in this situation, I will fail you. I'm not good at this. Use this person in this position, bring I am into this situation. And they'll be like, really? Yeah, I'm not the right person for this. I am honest about it. I'm absolutely honest because I don't want to set anybody up for failure, not just myself, but my manager, my coworkers, everything. Not everybody is comfortable with that. Not everybody is comfortable saying, I'm not going to be good at this. I am willing to absolutely try, but I want everybody prepared. Understand that. Listen to your folks that are saying, I don't— I'm willing to take this on, but I may not be good at it. I'm one of those, I'll be the first to say this, is the reason that I took on things that nobody else would take on many times, it was because I wasn't scared to fall flat on my face. I really wasn't. I was like, I'm gonna fail miserably. And I've come out of situations going, that didn't turn out like I thought it was going to. That was horrible. And would laugh about it and walk away and try again. I also realized from My oldest child, he was 16 at the time. He's now, oh my gosh, 31. When he said to me, he says one time we were in an argument and he says, well, mom, look at you. You never screw up. I said, Sam, I always screw up. I never give up. I didn't realize, I thought my kids would look at me and go, mom is a total idiot. Mom falls on her face all the time. I realized that people don't often see your failings if you don't give up and you just keep trying. All they see is the last piece, the success. If you can be that way, you just keep trying, that fall down 7 times, get up 8, that really goes a long way. That really, really does. And it's something that I often tell folks, don't give up. So I personally have got pretty far in life with just asking myself, like, what's the worst that can happen? You know, if you put yourself out there, I like, you're probably not going to die or kill anyone. If you are, maybe dial it back, but putting yourself out there, it's a wonderful way to learn. Push yourself to the edges. If you stay back from the edges, you're never going to push push that frontier farther out. Yeah, I, by the way, I know you do like mentoring of a lot of people at the early stages of their careers. And is there advice you give them? Is it fall down 7 and get up 8? Or is it, how do you keep them? Because they're kind of afraid in those early stages. How do you encourage them to keep trying? I do have to say the women that I mentor are just fearless. Oh my gosh, the early, the younger generation that I'm seeing come up in the data infrastructure, AI world, And the SQL Server community, the Microsoft community is about 10 years younger than the Oracle community on average. They amaze me. What I'm really telling them is not to get such structured ideas of their path. Many of them will come to me and go, "I'm only going to work at this company. I'm only going to work in this area. I'm only going to do this." I recommend not to do that. Open up their minds and take on opportunities that they may not have considered to begin with. Some of my best jobs, some of my best career opportunities came from jobs that I never would have thought of. I didn't even consider applying, but somebody else told me to. The role that I had at Microsoft, Patrick LeBlanc told me, he says, you should apply for my job. Never done analytics. Oh, you'll love it, Kellen. Kyle Haley came to me for Delphix and said, apply for my job. I'm leaving. I was like, really? He's like, yeah. Yeah. I don't know how many times it's been like that. Redgate, I was very happy at Silk, and they were like, you're the person that we want in this role. We're just going to open it up. If you're interested, let's talk. And we were able to negotiate and figure out what was the right combination for me to stay at Silk part-time, but be full-time at Redgate. You don't know what you're going to get if you don't ask. And every place that I've been, I've created a role for myself that fit. In the last, I'd say, 5 jobs, fit what I am and what I can bring and how to be the most productive. So just ask and take opportunities that you may not have considered originally. Before we, we take a quick commercial break, I, I was actually thinking about subconscious bias the other day, and where it hit me is I was filling in a form and it gave— there was a place you're supposed to put name, and it was something like John Smith or something like that, and I wondered How often does it show up as a guy's name? And I started looking at the next few forms I had to fill in, and I couldn't find a single case where it wasn't a male name as the default. I, how do we, how do we stop that bias and exclusion from showing up in default design systems? Heck, AI, how do we make sure AI doesn't have our traditional bias and exclusions? That's a really complex question that you got to boil down to in a minute, but There's a lot of ways to do that, as in having checks into systems to go back through, because there is bias everywhere, everywhere. It doesn't matter what you're talking about. One that I went through the other day where they ask you for your previous names that you might be referred under. If you're a woman and you've been divorced, it automatically tells them that you've been divorced. Men don't usually change their names. And I call it the identity crisis of a divorced woman. And I'm past my quota. I always joke about that with marriages, past my quota. And having to put down those names, it is, it will probably be the one thing where I'm saying, oh, I'm fearless. Those ones, I put down my previous names and it's mind-numbing. It really is a bias that you realize that my husband who's past his quota too, doesn't ever have to. There are biases built into every system that nobody ever realizes until you have everybody. Test it. And you need testers that come from every walk of life to check the system out. Have those checks. And it is important to have white males check it as well, because I have seen reverse bias built into systems too. Yeah, that's an excellent point. You need diverse people giving a diverse— putting it all in context. Based on my background, based on my perspective, does this send a certain signal that you might totally not pick up on? I think we're going to run into more and more of that in AI, because it's trained on literally everything that's ever been written down. And historically, all those things written down down the farther back you go. Exactly. It was written by Western industrial— Western-educated, industrialized, rich, democratic nations, and tending to be kind of from the white male background. I do think we need— it's bias simply just needs to be— it's something we have to be aware of. We have to find it and we have to make sure, is this something that we can fix in the system? Are we perpetuating something? Like, is there a reason why we have to make that default this way? Is there a reason why we need the list of every person's name that they've ever put in in history? I appreciate you building those bridges between various people and technology. We're going to dive into more of that in a second. But at the moment, we're going to hear from today's sponsor about what they're doing in the wide world of AI, Caprice AI. This episode of Asking Good Questions is brought to you by the great folks at Caprice AI. As someone who spent over 25 years helping improve the office of the CFO, I am genuinely excited about what Caprice is doing. They're bringing the power of AI to finance and accounting teams in a way that actually makes sense, helping unlock insights buried in data and make better business decisions even faster. If you're in FP&A or accounting and you want to see how AI can transform your workflow, check out Capris AI. Trust me, your future self will thank you. Thank you, Capris, for being our sponsor for today's episode. We greatly appreciate you and all you're doing in the world of AI. What we were talking about right before the break was how technology can become become more inclusive. Kellen, what, what have you seen? What have you faced out there? Well, my husband and I have a very unique perspective because we have been in multiple companies, worked together, been in the same role, everything. And one of the challenges that comes in is that many of these decisions, when you talk about promotions and rewards, they're done without anybody in the room while it's happening. You've got actual leadership that's just Bias can come into play very seriously. Promotions, you have people that are just going, "I'm thinking with a biased decision and going to promote this person." It was easier for my husband to get promotions often, where I had to go in and have somebody be an ally, sponsor me, and promote me. The opposite was true when we started talking about rewards, where they felt that I wasn't getting a raise, "Women are bad at negotiating salary," or, "Oh, it'll look a lot cooler if the girl gets it than the guy." and the opposite would happen. So we need to be aware, we need to ask ourselves and almost have these questions that say, are we being biased in our decisions? Did we consider all the candidates for this promotion? Are we leaving anybody out? Do we need to refer to a list? Has that been done? Have those checks. And same thing in reverse. Did we give the rewards based on merit, or are we looking at a DEI decision here? Did we choose them because it looked cooler to give it to somebody else? Ask those questions. And I don't think we do that enough. One of the things that I'm very proud of is to be on the ODTEG Board of Directors, Oracle Developer and Technology User Group. At the time of recording this, my term is up in 1 month. When I leave, based on the new incoming class, the Board of Directors has 9 people in it. 8 of them will be female. There will be a single male on that Board of Directors. And this is not usual. This is not what tends to happen in the technology user group community, if I may put that politely. How— I'm very proud of that board and I love what occurs. I'm leaving voluntarily. I didn't run for reelection. I'm really happy with the transition. You've been part of Women in Technology for years and helping support— I started with them at OGITOC. They were lovely to me this year. How did you manage? That's a pretty measurable thing. This is not, we've given more opportunities. We've gotten women into leadership positions to the point that the president, the vice president of the user group are female. How— thank you for starting the WIT program way back in the day. How have you been able to create that group of leaders to get them out there volunteering and contributing and helping change that traditional culture of tech user groups? It's not easy that we are fighting. It's a complex issue. Again, when we start getting into women in tech and the challenges, and we haven't even picked up on diversity and all this other stuff. I am a user group leader. For the Data Platform on the Microsoft side for the DEI user group. I'm one of the organizers for that. And for Women in Tech on the Oracle side, I have tried to stay involved as much as I can, but I do mostly one-on-one mentorship at this point. That's, that's what I've been involved in. And the one thing that we've seen is that much of it goes back to older issues. We have heard about this since even before we're born. People are deciding what color our room's gonna be and what toys we're gonna play with and how people are gonna interact with us. When we're even young, we're being second-guessed. "Oh, do you think you just misunderstood him?" "Oh, are you sure that's what you meant?" We are second-guessed earlier so that when women get into the business realm, they're not prepared for that. They may second-guess themselves. They may not jump in and take on opportunities where boys are told, "Get in there and get going!" I have a much— rub some dirt on it. Yeah, yeah. I have to admit, I was the first girl in my generation. I have a much more male perspective mindset than other women. I, I just acted like the guys and I expect to be treated like the guys too. I will be totally honest. So back when I was an Oracle ACE, I remember looking around and Yuri Villanueva had just been given his ACE director. And the way that my brain works, I sat there and went, I'm doing more than Yuri. I'm doing a lot more than Yuri. I should be my— I get an Oracle ACE too, an ACE Director. I'm ready. And that's how I viewed things. I would look honestly, objectively, am I meeting these criteria? Yep. I should get it. That's how I viewed things. That's how I saw things. And I moved forward and said, I should be an ACE Director. And luckily for me, those people that were there for me sponsored me and I got my ACE Director within a year. Worked out great. But I don't think most women see that. They want to make sure that they're 150%, 190% prepared for it and that they have met all the criteria and then some. And I noticed that when I wrote my first book, I was writing on Enterprise Manager 12c and I was looking for authors and there were a number of women who really excelled in that area. And I reached out to them and said, I would love for you to be an author on this book, one of the chapters. And there were two women that I really wanted on this, but they came back and said, let me check, let me make sure that I can do this. I want to make sure that I don't overextend myself. And four months later, they came back and said, yep, I can do it, almost within days of each other. And at that point, the book was going to publisher and they missed out on the opportunity. And what hit me is I've seen this before. I've seen this happen to other women. Maybe a position, an opportunity came up and they would step back and go, I need to make sure that I meet all the criteria for this role. This opportunity, and by the time they stepped in and applied for it, someone else had already gotten it. So I often recommend, don't worry about if you're got the requirements, because there's some guy who says, I can spell it. I got the requirements met. Go in. Just do it. The A comes before the cool. I'm qualified to be your new— yeah, just do it. Just apply yourself. Just, just apply to the role, whatever it is, is, and you will figure it out as you go along, because I I don't see a lot of mediocre women in tech. They are kicking butt and they need to be recognized for it. I tell them, just go full on out. Don't worry about it. It'll all come together when it comes together. So, let's talk about that leadership going forward because we're in the middle— well, you've been in the middle of a lot of industry shifts. The rise of DevOps, the cloud migration wave, database virtualization. Now AI is getting embedded in everything. Most software vendors can't finish a sentence without saying there's some new AI part of what it is they're doing. What kind of leadership does does this industry shift moment call for, both from a technical but also a business perspective, if you want to lead people into this AI? Yeah, one is protect your company from shadow AI. I can't say that enough. And by shadow AI, of course, for those who are listening to this and going, I've never heard of this shadow AI, what is it? It is AI that has not been approved in any way, or you don't have policies and approved AI lists of products that are acceptable. Acceptable to use inside your organization. Right now, or I shouldn't say right now, as of Q2 2025, the free version of ChatGPT has over 20% critical data in it. That should not be happening. That is where we're at. Just the free version of ChatGPT. People have been uploading critical data in it. That means authorization codes, names, security numbers, employee salaries, all of this stuff that has no interest being in there. If you are not teaching your employees, your organizations, how to use AI responsibly, ethically, what is safe AI, what is unsafe AI, they're not going to know what to do. And you're going to put your critical data in a vulnerable state. And it is a problem. Yeah, I see a lot of companies that either are saying, oh, we're going to ban AI, which basically means everyone else is going to go do their own shadow AI because they're all going to go get licensed ChatGPT and load up corporate financials into an attached spreadsheet. Or they roll out the next simplest level. They'll roll out some level of Copilot or ChatGPT licenses with no education whatsoever on how to actually use it. Maybe it goes back to, well, they have to do something with AI. They don't know where else to start. But I agree with you, there has to be some level of both support, but then also Governance, understanding, control of what we're really doing. Governance, policy, committees. You must do this. AI is everywhere. There's no way to avoid it. There's no way to hide from it. Everyone had an annual review and their bonuses relied on putting AI in the— You have AI in your systems. There's no way around that. So when we talk to people and they, some are still concerned with their job, although I believe that this will be like every other technology in history and it will generate more opportunities than fewer. It will definitely result in disruption. There will be squishy. Is there advice you'd give to a professional that wants to stay relevant, that wants to make sure that they have a job that is important and adds value and is challenging in this rapidly changing AI environment? It is rapidly changing, right? It's more about learning at a surface layer. If you're not in it to win it right now, it's not part of your day-to-day job. If it is the AI in your technical area. Learn it. Absolutely. Go to webinars, go to hackathons, learn about it. But learning AI at a surface layer, you can learn that through webinars. You can become relevant in knowing those— what is an AI agent? What is an MCP server? What is— learn those things. Embrace Python. Everything is in Python these days. If you know Python, you're in business. If you understand ChatGPT, Claude, OpenAI, start to understand all the terminology. Don't just learn the buzzwords, learn the terminology, what's behind it, understand it, go to the meetups, go to free events and become part of that and talk to other people that are in your industry. Understand what's going on, but also don't fall for everything. You don't need AI in everything and learn how to disable AI in products because there is a lot of AI that is there for no reason that will not provide you any value. AI shouldn't be in everything. AI should be there because it has to have value. It should be justified, plain and simple. For people that's part of their job and worried about not staying relevant, know that technology, it stays. It's got stickiness, especially when it comes to data. Data is needed. It is what feeds AI. Without data, AI is worthless, plain and simple. And data comes from a lot of different places right now. Unstructured data is a big deal. People want to get value out of PDFs, out of JSON, out of all these different unstructured sources. But at the same time, that is messy and it doesn't impact what we have in a structured format. Our structured data is still what runs the world. FinTech, retail, manufacturing, all of that is still there. So if you're doing your job, you're not going to see a change to it day to day. And they've already proven this. And you go out to the Labor Statistics and that even though there are now, they're saying 93 million jobs that will be cost by AI, those will go away by AI. There's another 143 million that will be created by AI by 2026. And even with those numbers, when you look at the areas that they're at, data science, data warehousing, database technology is quite safe. Those aren't going anywhere. If you're an underwriter for an insurance company, yeah, you got something to worry about, but not in our fields. We still are incredibly relevant. Yeah, I think that people who have experience definitely are always going to be relevant. Ones who can look at the data and say, does this actually make sense? These recommendations make sense. I do wonder what entry-level jobs start looking going forward, and I'd love to dive into it, but I want to close with our quick hit round. So, I'm going to ask you a few rapid-fire questions. Say in one sentence or less, the first thing that comes to your mind. Most misunderstood thing about databases? That they are all the same, that I can just replace one database with another. I love the goal that people, because they'll be like, "Oh, Oracle's expensive. We're going to get rid of Oracle and we're going to put it on PostgreSQL." There is such a tiny itty-bitty percentage that are successful coming off of Oracle. And what they don't realize is that Oracle with its strong reliance on PL/SQL and the underlying DBMS packages, that code isn't going anywhere. It is like glue. Talk about the locked in. And if you look at DB-Engines, the ranking, that Redgate actually owns that site now, but I've used it for years and years and years. You'll see the numbers that back in about 2006, we're sitting about 1,400 on the ranking for MySQL, SQL Server, and Oracle. Oracle's sitting about 1,270 now, where SQL Server and MySQL have decreased incredibly because those are much easier to migrate off of. Oracle isn't going anywhere. Yeah. As much as you hear about that, it's lovely if you want to do a greenfield project on Postgres, it's brand new, but Oracle Database has got some sticking power. No question about it. Cool. One good reason to move to Portland. One good reason to move to Portland. Oh my gosh. You hear Portland's on fire. It is not on fire. We have no idea where white people are putting up videos of a few homeless people setting up a trash can on fire and saying that Portland's on fire. It is incredible here. You find out that this city has many different niche. I can drive around and I'll come into a block and I'll be be like, "This is cool. It is awesome here. Look at all these food trucks. Look at all these little shops here." The neighborhoods are incredible. That the idea of supporting your local mom-and-pop stores and local industries is something Portland does at a level I've never seen anywhere else. And yes, we got hit during the pandemic worse than anyone else because you didn't have these big corporate powerhouses to backfill and support as stores were closing. But Portland has come around and as much as people say, oh, it rains all winter, it drizzles during the winter, but during the summer it is incredibly glorious here. And I live on the river, so I can say that. Yeah, I have to admit I get happier when it rains. What is the right type of mist? I call it Portland rain, but last quick one. What is a database trend you wish would disappear? Database trend that I would like to disappear. I'm trying to think of this. Uh, vector storage inside databases. I know it's required. It's part of it. But this idea that in everything's going to be democratized. The idea that having the relational database, we were protecting all of that database. It was the golden source, the golden copy. I don't think anybody knows where that golden copy is anymore, where the gold is. They're just spreading that data out everywhere. They're changing it all. And I'm like, where is the gold copy? Where is the data, right? I don't think most people know we're getting more into the data governance area, people owning the data. Again, maybe that's keeping the DBA, but no one knows where it is. And that is a problem. That's that evolving answer. That's where I'm going with it. Perfect. Wonderful way to close. Kellen, thank you. This has been one of the most wide-ranging and insightful and thoughtful conversations that we've ever had on the show. Thank you. Thank you so much. And to our listeners, thank you for joining in. And a special thanks to Caprice AI for sponsoring today's episode. If you enjoyed this episode, make sure to follow us on Spotify, Apple Podcasts, wherever you get your questions answered. Click on the buttons down there that say things like like and subscribe. And until next time, keep asking good questions.