Podcasts about DevOps

The W. Edwards Deming Institute® Podcast

Play Episode Listen Later Sep 28, 2026 5:59

AWS Morning Brief for the week of September 28th, with Corey Quinn. Links:AWS Network Security Manager is now generally available in US East (N. Virginia) RegionAWS PrivateLink announces Tunnel Endpoints to access network segmentsWrong, not brokenIntroducing Amazon CloudWatch Omni: AI-powered observability for generative AI and agentic workloadsIntroducing enhanced custom event buses in Amazon EventBridge for enterprise-scale event-driven applicationsAdding custom domains to AWS Lambda MicroVMs with Application Load BalancerRunning self-hosted AI agent sandboxes with AWS Lambda MicroVMsHow BMW Group detects cost anomalies across 14,000 cloud accountsFour AWS CVEs in a row, escalating nicely

amazon ai cloud aws devops corey quinn last week in aws

John Willis: Why AI's Biggest Problem Isn't Technology

Play Episode Listen Later Sep 28, 2026 66:01

What if your AI strategy is creating more risk than progress? John Willis joins Andrew Stotz to trace how Deming's System of Profound Knowledge shaped the way he thinks about organizations, learning, and change. From his early days building DevOps to the AI transformations he's navigating with CIOs today. Along the way, John connects Deming to fast feedback loops, explains why leaders keep mistaking a learning problem for a technology problem, and shares stories that never made it into his book, Deming's Journey to Profound Knowledge. A fresh conversation for longtime Deming thinkers and those just beginning the journey. TRANSCRIPT 0:00:02.0 Andrew Stotz: My name is Andrew Stotz and I'll be your host as we continue our journey into the teachings of Dr. W. Edwards Deming. Today I'm here with featured guest, John Willis. John, how are you doing? 0:00:15.7 John Willis: Great, Andrew. I was just thinking, I feel like that song, like I got my picture on the cover of Rolling Stone. Like, I'm on the Deming Institute podcast. Yay. [laughter] 0:00:24.9 Andrew Stotz: We finally got you on. 0:00:27.8 John Willis: Yeah, yeah. 0:00:30.3 Andrew Stotz: Actually been a while and I wanna introduce you just briefly and then I'll let you do a little bit more of the introduction. But basically on Amazon, a book popped up and I was just looking at the date of that. That book popped up on, for me, it popped up on September 6, 2023 on Audible and I immediately bought it and I got the Audible book and the book's called 'Deming's Journey to Profound Knowledge. How Deming Helped Win a War, Altered the Face of Industry, and Holds the Key to Our Future'. And I immediately got it. Didn't know you, listened to it, loved it. Later you reached out on LinkedIn and we started communicating and you were kind enough to send a copy of it, which I then went through in more detail. I love the book. I really highly recommend the Audible version because it's just fun. Because the book is opening up a whole new Deming lens, a whole new way from somebody that never met Deming, and I just found that fascinating. So maybe why don't you take a moment and introduce yourself to the audience so that people know who you are, where you've been, what you've been doing and what you're doing now? 0:01:41.4 John Willis: Yeah, no, no, great. I... So, yeah, I... I've been doing technology, usually high consequence business, regulated industry, banks, retail, the biggest of the bigs, where the technology is incredibly important. Right? And I've been doing five decades of basic technology transformations, and I'm kind of the person who gets bored real easy. So I've literally gone through, like, you name it, mainframe, centralized computing, client server, distributed computing, priority systems, the Linux Open systems, you know, owned infrastructure cloud, and I'm consider one of the founders of the DevOps movement. And now today, like the cliché that I am, I've been doing a lot of organizational strategy on AI. So I don't come in and tell you how to turn 4,000 developers into AI coders. I kind of tell your CIOs to slow down. Wait a minute. So, yeah, so my day job today is I'm... I think these days finally in my life I would call myself an author first. I've written a number of books. The one you did, I had... My last book was a history of 100 history, 100 Year History of AI. And... But I'm an advisor, so I sort of... I take inbounds. I don't really look for work. Usually it's a chief of staff for a CIO who either has worked with me in the past and hey John, we're underwater with AI. Can you come in? Or they hear something I've said or I do a lot of podcasts and then I'm sort of a quasi investor. Although I probably should listen to your stuff a little better because I'm typically... I'm one of those guys that like, if I invest in it, you go short on it right away. So... [laughter] But yeah. But, yeah, no, so... But my day job today is really, is doing research. I'm actually just sure, this probably opened up a whole another discussion. Maybe later but I'm writing a book about the history of quantum computing right now and that's been just fascinating. So... 0:03:41.7 Andrew Stotz: Yeah. 0:03:41.8 John Willis: But my day job is helping CIOs and large high consequence organizations try to shuffle through technology transformations. 0:03:50.7 Andrew Stotz: And for the audience there that didn't catch what you were saying at the beginning, it kind of dated you because you were talking about the song called Rolling Stone by Dr. Hook. 0:03:59.9 John Willis: Yeah, yeah, totally. 0:04:01.3 Andrew Stotz: Dr. Hook published this in about 1972. And here are the lyrics. "Wanna see my picture on the cover? Wanna buy five copies for my mother? Wanna see my smiling face on the cover of Rolling Stone?" So here... 0:04:12.8 John Willis: Totally. Yeah. There you go. Deming Institute. Yeah, no, great. 0:04:16.7 Andrew Stotz: And one of the things that I found fascinating was just how you came to Deming from a very different angle. I was lucky enough that my boss at Pepsi sent me to study with him and I did two different seminars. The last one was in 1992. So I was 24, he was 92, was gonna live about one more year. I had... I could literally reach out and touch the man and hold his hand and sit next to him. I got a great picture of me sitting next to him. And I was just a young guy with a fresh mind compared to the 500 guys behind me that were older that he was bashing at times. But tell us a little bit about how you stumbled upon this topic and why you decided to do what you did with writing the book? 0:05:03.7 John Willis: Yeah, no, it's sort of interesting. I sort of say that for the first, I don't know, probably from 1980, my first job was running five distributed large computer systems for Exxon Research and Production, basically the geophysics work, right, during the most hottest period of the oil industry. And there were people doing that part of variation and understanding, but that didn't sort of hit my world. I was supporting geophysical processing and then so I rolled into other jobs. And then probably the closest I came... So in other words, I'm dealing with a lot of these major transformations and always focusing on the meta side, like the organizational. What are the things that are wrong? How do we fix the human and technology? There's a phrase called sociotechnical systems, right? And that's always where I've been most interested. And then even I was at GE Capital and I'll say this with all honesty, I was a Green Belt, but they gave out Green Belts for Six Sigma, [laughter] right? My wife was actually a Black Belt. And... But we would do... And I know Deming hated Six Sigma and all that, but we were doing... It was all around me, right? And then it wasn't until really the DevOps age that we really... That was a major shift in my career because before everything was sort of first generational from a technology or sociotechnical system, very command control, you sort of you installed software in a certain way. There were so many principles that were being broken by DevOps. And I was already an older guy at that point, but I was learning from these young kids and I'm known as the person who introduced DevOps to the US. 0:06:52.3 John Willis: And... But so there is where we started going back and understanding... We thought everything was new. We were creating DevOps, we were doing all this crazy awesome stuff. And I remember a friend of mine, well, a good friend of mine wrote a book called 'The Phoenix Project' by Gene Kim and it's a rewrite of Eliyahu Goldratt's 'The Goal'. And I was like, oh my God. And I read all of Goldratt's books and I was like, okay, this is the way, this is the way. I've seen a glimpse of some 30 or 40 year knowledge that I was missing. And then it was an open space seminar. A good friend of mine says, "John, you know." and I'm going off about Goldratt and he's like, "You know this all goes back to Deming." I'm like, "Who's Deming?" I'm like, "I just spent a year learning everything I could about Goldratt. He is my North Star. And now you're telling me..." And he challenged me. He said, "John, I'll leave it at this. You go read Deming's 14 Points and if you don't... I know you. I know what you're gonna do once you do that." And he was spot on. That was it. I was... And I don't... I'm more into the Profound Knowledge and we could talk a little bit about my journey there. But I was like, oh my goodness, this is the real and I love Eliyahu Goldratt and I love 'The Goal' and I love all his books. But Deming was hitting... Was like punching me right square in the face. 0:08:12.0 Andrew Stotz: So to what gap did it close for you? I mean, Goldratt is very specific about the main limiting point... 0:08:23.2 John Willis: Yeah. 0:08:23.3 Andrew Stotz: The bottleneck, how do we solve this? 0:08:25.6 John Willis: So the 14 Points, sort of one of the jokes is that it's mandatory to put the 14 Points in a DevOps presentation. So we were doing that dance a little bit, but then when I got a little serious about it, actually me and Gene Kim, we did a book. Goldratt has this book called 'Beyond the Goal'. It's an audio-only book, right? And I convinced Gene about five years after he had written 'The Phoenix Project' to do a Beyond the Phoenix Project. And so he did Goldratt, I did Deming. And at that point, I knew enough about Deming to say, "Okay let's..." And then we talked about DevOps and the principles of Lean and we did... I always, when somebody says they bought that audiobook, I'm like, "Oh, you're the 15th person that bought it." right? But it sold more than that. But the... But that's when Gene tapped me on the shoulder and did that. We went to the studio. It was a highlight of my life, literally going to the studio with Gene and literally recording for a couple of weeks. And he's like, "John, you really need to write a book about Dr. Deming." And then I started building a folder. And then the crash course then or the trajectory at that point not really crash course is that you realize the 14 Points are, no disrespect, but vaguely interesting. You're like, "Okay, Mount Everest is System of Profound Knowledge." Right? Because that's the mount... And that's the one where you're like, "Okay, I read 'Out of the Crisis', I think I get it, the 14 Points make sense, but like, what is this stuff he's talking about here?" Right? And then you read 'New Economics' and it's like, "I still..." And then, so for me then, it was, I'm just one of these person like I have... And again, I'm not trying to make myself look like I'm special, but I have to learn. I can't... I'm the worst person in a... If I was in your class, you'd kick me out of your class because I'd be sitting in the front row and you'd be, "Oh no, not you again." 0:09:26.2 Andrew Stotz: Another question. 0:10:26.9 John Willis: Yeah I know just another question. I mean, I've been cut off by professors and... But the... I'm like, "All right, I got to get to the bottom of this." And that was almost a 10-year journey for me of... I had to know. Because it was clear to me that Profound Knowledge or System of Profound Knowledge was not something he invented out of thin air. Like, I had to figure out, where did he get this? And that started the genesis of how I was gonna write the book, which is the journey, 'Deming's Journey to Profound Knowledge'. And that sort of took me into... And what that did, while I was learning that, of course, Deming opened the door to guys like Russell Ackoff and Ashby and just all these other sort of management thinkers and even Drucker or whatever, right? They all sort of started filling out a palette. But meanwhile, I'm still driving hard on Deming. And what that gentleman said to me, good friend of mine, Ben Rockwood, who I give tribute in the book, is when he said to me, almost like tapped me on the head, like, "John, John, John, it all goes back to Deming." Like, you start seeing the clarity of DevOps, Lean, Agile, it all had these things. And so I spent literally a long time really trying to figure out, okay, how did Deming get... We all know variation is relatively simple to understand where he got that from, right? Shewhart's work and all that stuff. And I'm not trivializing the impact of what he did for it, but knowledge was interesting. And knowledge I had to go to pragmatism. You had to understand what C.I. Lewis is. And that's a book that Deming said he had to read seven times. 0:12:03.1 Andrew Stotz: He had to read it seven times...there's no hope for me. [overlapping conversation] 0:12:05.2 John Willis: That's right. No, actually I did Tom Sawyer. I have a friend who's one of the smartest people I know. He's like, "I'll read that." And he explained it to me. But and then I read it. But so knowledge, this sort of, how do we understand? How do we know what we think we really know, right? That whole epistemology and all that. To me, this is like sort of, just give me more, right? And see more and feed me. And then system thinking was interesting, appreciation for system, because then that got me back to, okay, and there was some missing links there. And I found that one of the guys who came up with General Systems Theory, von Bertalanffy, him and yeah, Ackoff. Him and Ackoff had sat in a seminar of his like in the '40s and so there was some influence there. And there's a lot of work that's been going on in systems thinking after him. But so then I got that and then the psychology is tough, right? But so I put all that together. And then my... The thing I was telling you earlier is, when I do the research for a project like this, I read everything that there is about it. So my AI book, I read 25 books on AI, history of AI. I'm up to like 10 books on the history of quantum computing. 0:13:23.4 John Willis: With Deming, I've read every book that's been written by Deming, at least the ones that I know of, right? And one of the things I noticed, the pattern was that they all... Again, I'm just simplifying it. They all started off with a little bit about the biography, some a little longer than others, but in general, most of the book was about the management theory. And it was really a book that was being sold as a business book more than it was as a biography. And one of the things I've always loved about Michael Lewis or that sort of story of nonfiction storytelling is he tells a biography, it's a disguised biography and I thought, my God this... And as I kept compiling over the years all these great stories, you know, the Doris Quinn story, right? The woman who, she went to New Guinea and Deming... Spent the last two years of her life with Deming. I mean, most of the people that are Deming disciples didn't even know about this woman. And she spent the last two years of life traveling with him. So I met her and interviewed her. And the stories, you know Hawthorne, and there was such... It wasn't just that, I love the idea of trying to explain how he got to management theory and epistemology, how did he get to the science of variation? That's all good stuff. But I wanted the stories, and the stories were just glorious. As you enjoyed the book, right? 0:14:52.4 Andrew Stotz: Yeah. 0:14:53.3 John Willis: I think that was the fun part of not just explaining the sort of tech, if you will, but it was the, like the, oh my God, this... I've got to... I had three chapters like six years before I wrote the book. 0:15:06.9 Andrew Stotz: Yeah. Well, here's chapter 15. And you say, "Being a student of Deming, I came across an untold firsthand account of a beautiful story from one of his acolytes, a woman named Doris Quinn," who you're talking about. 0:15:20.0 John Willis: Yeah. Yeah. 0:15:20.2 Andrew Stotz: And... But the... I also had marked a section related to talking about the final days, saying... 0:15:29.7 John Willis: Yeah. 0:15:29.8 Andrew Stotz: "Doris said he was a very, very driven man. He went nonstop. I remember one time we were in Kansas City and a reporter asked him, "Dr. Deming, when are you going to retire?" And the master said, "Why would I do that?" "Well, so you can do what you want." the reporter said." 0:15:45.7 John Willis: Yeah, yeah, yeah. 0:15:46.4 Andrew Stotz: "Dr. Deming looked at him and said, "I am doing what I want." 0:15:50.2 John Willis: Yeah. You know what I love about her? There's a really good book from Amazon called 'Working Backwards'. And they tell us... The guys who wrote it were pretty high up early on in Amazon. They tell the story how if they traveled with Bezos and you didn't have a whole set of questions on the plane ride, you got in trouble. And so Doris Quinn tells that story, how she literally, she tells the story of how she traveled with him and he's like, "Doris, what other questions do you have for me?" And if she didn't have one, he'd get mad at her. He wouldn't talk to her. They'd have to wait a day because normally they'd go and have gin together. But if she didn't have questions... And some of it's in the book, some of it was in conversations had... He'd literally get mad at her and not talk to her for the rest of the day [laughter] because she didn't have any questions. You got to love that, right? 0:16:39.2 Andrew Stotz: And you also did a little follow-on about more stories that you didn't get in the book, I believe. 0:16:48.1 John Willis: Yeah. Yeah. 0:16:48.2 Andrew Stotz: Tell us about that. 0:16:50.1 John Willis: Well, so I wrote the DevOps Handbook, right? And that was a collaboration with four other authors and took us six years to write it. So my wife says, "What parts did you write?" I'm like, I don't know, man. There were a lot of parts that went in and out and moved around when you have four authors, and it was really a very techie book. So 'Deming's Journey to Profound Knowledge' was really the first book where I literally... It was my book. And so I had written the book. In fact, my favorite story, and Doris Quinn is a great story, my favorite one was... It was basically called The Devil Wears Prada. And so, and Kevin... I don't think Kevin, his mother even knew this when we were talking that his grandmother literally was... I mean, I think they knew that she worked for the pre-BLS, she was a statistical mathematician and all that. 0:17:45.3 Andrew Stotz: Right. 0:17:45.4 John Willis: But after the war, she worked before she... I don't know if she met Deming, but she certainly wasn't married to him, Dr. Deming. She worked on the mail-order business was getting all these returns for women's sizing. And so whatever the pre-BLS was, Bureau of Labor Statistics, commissioned her to do a study. And she's the one who invented women's sizings. Because before, they didn't really have all the different measurements. So she ran a whole statistical study. And so today... So I use the whole story of the Anne Hathaway, the 14 is the new seven and all. So I start that off. Anyway, so I go to my publisher and my editor, who I love, she'd already knocked out a lot of stories, but this is the one where, "You're not taking this story from me. You're not... This one is not." And then she's so good, she'll be like, "John, let me ask you this. Does it fit the arc?" By this point, she understands System of Profound Knowledge, she's read my book quite a bit, and she says, "Does it fit the arc of System of Profound Knowledge?" "Uh, I hate you." And I took it out. And then she said, "Well, why don't you make a blog post out of it?" And I'm like, "Oh, no. I'm gonna make another book." And I took all the stories we cut out and I called them Profound Stories. And yeah, so... 0:19:06.6 Andrew Stotz: And for the listeners and viewers, you can get it on Kindle and then you can read the stories. And I think for the Deming community, that's one of the best parts about this whole thing, is just there's no great collection of stories that has an arc to it, as you said. So I enjoy that. I wanna also... It'd be interesting to understand how your thinking has progressed about Deming, because obviously you talk about this introduction phase where you got to know him, then you have this intense phase that you seem to have a knack for, then you write the book, you have all the excitement about that, but you're on to other things. 0:19:46.8 John Willis: Yeah. Yeah. Yeah. 0:19:46.9 Andrew Stotz: And there are remnants of Deming that remain with you, but there's others that have fallen by the wayside. Maybe they're not as critical as you may have thought or... I'm just curious, how does the Deming thinking unfold in your life now? 0:19:59.7 John Willis: I... It's become sort of a fabric. So, and I wanna get back to that, but I do wanna say one thing... I'm so... Whenever somebody tells me the story that they met Deming, I have two reactions. One is the hair on my skin, my arms go up thinking, "Oh, I wish that was me." But then the other one is like, I'm sure he would have yelled at me and got mad at me. Because he would basically be like, "That's a stupid question, Mr. Willis." So I have this fantasy of which way it would go. But anyway. Yeah, the question around what do I think now? I think, so if you go back to the narrative, he... And it's hard not to be a sycophant of Deming, right? But I am a sycophant of Deming, but I try not to be. And... But even in the book, I tried not to be a sycophant, right? I went out of my way. But so when I say this, Deming was in my DNA before I even knew who he was, right? Like at Exxon, at GE Capital, the Six Sigma stuff. And again, I understand for people listening, oh, the Six Sigma went the wrong direction, but it originally was stemmed from a lot of his ideas. And so it was there. So it was sort of foundational, and he was the lighthouse to put it in... And then System of Profound Knowledge became the taxonomy for me for this stuff that was in my DNA. And so in one way, there is this thing where you move on to a new transformation. And we're in one right now. We've been in one. I've been in one for five years now, which is with the AI. And again, same thing for me is it's not about the AI, it's organizational behavior, organizational patterns, what is the sociotechnical science behind how do you do these things? 0:21:48.4 John Willis: But so you forget... I always say technology shifts are like fluorescence. People use the metaphor of like spring and winter, like AI winter, AI spring, and they've used it for other things than AI. And that's sort of like a rebirth. The fluorescence is good because it's like an energy. It's always rolling forward. It just gets a fluorescence bright glow periodically. And so what the problem with the metaphor works for me because the energy is there, and the energy are the patterns that are consistent. The fluorescence is the blinding effect. So back to like, did anything fall off the wayside with Deming? Yes, for a little bit. Because in 20... Basically I started playing with the early versions of GPT, the OpenAI models, back at version two, and that was like around 2020, right? Even before ChatGPT, right? So that whole experience before we started even thinking about what this was gonna look like at a large-scale bank was fluorescence. Like I'm not thinking anything about Deming from 2020 to 2023. In 2023, 2024, I start getting asked to come into some of my larger clients. And I'm following it too, and I'm sort of... I'm starting to become aware that this is becoming... In fact, I'm pretty sure in the grand scheme of things that don't matter in the grand scheme, I'm pretty sure I got first use on shadow AI, in an article I wrote in like 2022 or 2021, right? 0:23:27.2 John Willis: So I had already been recognizing there's a problem pattern here. We got the shadow IT with the cloud stuff, now the shadow AI, and I could see this steamrolling happening so... And then I started getting called in organizations, and then I still was the wayside of the Deming. Like, I didn't walk in going, "Hey, I'm gonna hit the punching bag with Deming." I was coming in trying to figure out what do I know about patterns with this fluorescence metaphor that are new and shiny, and what are the things that are old that have been relevant for the five decades and the six transform... At least six transformations I've been through that are common in everyone. And I started seeing that. And then what was funny, as I'd be writing and researching with AI, it knew so much about me that even as early as like 2024, I had loaded in my Deming book. In fact, one of the ways I learned AI is I took the 'Deming's Journey to Profound Knowledge' and I turned it into an augmented general retrieval, or what they call RAG database. So I learned a lot about AI because I knew what my book was, and I could validate what was hallucinations. 0:24:36.3 John Willis: Anyway, but it knew enough about me. And then what it would periodically do, it would say, "Would you like Deming's version of this?" I'm like, "Yeah, I would love that." And then I... It started refreshing my memory of what the real context going back to my friend Ben Rockwood, it all goes back to Deming. And so now it's actually on the... It's more than ever, it's on the forefront because I'm being brought into major brand organizations that are seemingly failing on AI at the institutional, organizational level. And there's not a line of these people. In fact, most of them don't wanna talk to me because they don't wanna hear what I got to say, which is slow down. And I'm okay with the ones that don't wanna hear that because I don't really wanna work with them anyway. But now I'm seeing with absolute clarity two things. One is it all goes back to Deming, and all the problems that we're seeing can be classified in Profound Knowledge. 0:25:37.1 Andrew Stotz: Tell us more about that. Because for those people that... There's so many different components. When I got introduced to Deming, it was the 14 Points, 'Out of the Crisis'. And then I left America in 1992, so I wasn't there for 'New Economics'. And it... And I did other stuff for 20 years, 15 years, and then I found New Economics. It's like, "Wow, this is different from that." 0:25:53.1 John Willis: Yeah. 0:26:09.1 Andrew Stotz: Yeah, so between the deadly diseases, the 14 Points, the System of Profound Knowledge, there's so many parts to this. 0:26:15.9 John Willis: No, I've got... Yeah, I definitely got. And I'll tie it right back to the... In 'Deming's Journey to Profound Knowledge', I tell the story of Knight Capital. And Knight Capital is an interesting... It was the second highest high-frequency trading, black box, latency arbitrage on the NYSE. A sysadmin made a configuration error. They lost $450 million and don't quote me on the exact numbers, but like 450 million in 45 minutes. They were arbitraged at billions of dollars. They were literally out of business with a cease and desist from the SEC. And I always tell people, like, that's the last thing you want if you have a business is a cease and desist from the SEC, right? And at that point, we would say things like the consequences are high on how you think about humans and technology. Well, guess what, sports fans? Knight Capital is a drop in the bucket of what we're gonna start seeing with AI. We are going to see these... And there's the Equifax breach, there's all the... We're gonna see non-survival. I mean, Knight Capital didn't survive. Equifax lost five billion market cap in a week and then recovered all of it, right? But I'm saying there's been some major brand recognition problems pre-AI. You're not going to be able to survive these with the power... [overlapping conversation] 0:27:41.7 Andrew Stotz: Abilities are gonna be shaken out. 0:27:43.6 John Willis: Yeah. I mean, and the brand damage. Brand damage by the escape routes of how... I mean, let me just step and I wanna go back to answer your question. But one of the things that people don't recognize right now is the machine that we have now has infinite knowledge at machine speed, and it's probabilistic. I mean, just add those three things up, that it has the ability of infinite knowledge, something no human could even close to. So it'll make decisions, it will escape, it will figure ways out, it will try a clever way to do something that probably no human would do that could be a disaster. Right? So the consequences are incredibly high. So then now, okay, let's really dust off: it all goes back to Deming's stuff. And so to your question, I think that I would love to see, like, you write a fantasy novel about how Deming came back to the future and was sitting here listening to what was going on, and he'd be screaming. He'd be telling everybody... And this is the thing I'm... I don't scream, I'm too old these days, but like, I literally cut off a CIO real quick in my conversation. I interview a CIO, they think they're interviewing me, I'm interviewing them. And if I'm like, "Yeah, no, you know what? This isn't right." "Well, what do you mean, John? We had..." "No, no, no." 0:29:09.1 John Willis: Because I can see right away that what the CIO or the leadership is... They think AI is a technology transformation. It's an organizational learning transformation. Deming would see this and scream this out loud. And that's the part of the blinding fluorescence that we're missing. We should know this by now, right? And so all these technology shifts, they think they're technology revolutions. They're really... I mean, they go back to the basics. What are the systems are they changing? Are we understanding what variation is? How do people learn? Are people not learning? Are people... A good example is, in every organization that I travel and this has been true for almost every technology transformation, but now it's glaring. I like to simplify. I say there's three groups. Let's take AI, right? Three groups in an organization. And usually, again, I don't care about really start-ups. I do care about startups from an investment standpoint, but I don't care about them from my day job. And so this is a bank or a large retail or insurance company or manufacturing. And so the CIO is like, "We have an AI strategy." And by the way, let me step one more thing, we learned a lot in the DevOps revolution, but DevOps was never a board-level conversation and it was never a Wall Street conversation. 0:30:37.1 John Willis: AI was immediately a board-level conversation. And so the pressure on a C-level, a CEO and a CIO, is "You must do AI yesterday.", right? And so now what's happening is the CIOs are literally doing knee-jerk reactions of like, "We're gonna have... We got 30,000 employees. If we can get all 30,000 employees using AI with a 3x productivity rating, we'll have..." you know, like, oh my God. And then they say, "Make it so." And I call this the strategy versus talent systems gap. And I don't mean how talented they are, I mean understanding what your talent system looks like. And to keep it simple, most talent systems look like this, they have one group that is passive-aggressive. They don't like change. They've been doing the same job forever. In this new world, they don't believe AI works, and they're passive-aggressive about it because they know they can't say they don't want it. When the CIO says, "We must do AI." they have to go, "Oh, we'll get to it next month. Next month. We'll get to it next month." And then you have the second group in the middle. They wanna do the right thing, but they're high enough... As we know, if you work for a bank and you're in a high enough position, if something really goes wrong, you're lucky if you get fired. You could get a fine for two times your salary, or you could actually go to jail. 0:32:02.3 Andrew Stotz: Right. 0:32:02.4 John Willis: Right? So that group is like, "I wanna use this, but you're not clear. There's no clarity from your... You guys all wanna do all this... [overlapping conversation] 0:32:11.7 Andrew Stotz: There's risks everywhere. 0:32:13.3 John Willis: But we've got the OCC and there's no clarity on FDIC and like, what does this mean?" "Well, I don't know." "Well, then I'm not touching this stuff. And do you have my back?" No. Right? And then the third group is the classic, do now, ask forgiveness later group. And so you could put this all back to driving out fear. Because what happens is you've got a strategy. What is that, it's number eight, I think. I think that's right, but it doesn't matter, right? It could be nine, it could be seven in the 14 Points. So the CIO has said, "This must happen." And then, again, board-level, horizontal, vertical pressures. And then everybody's... And they're not even understanding, do they have the capability? Do people wanna do it? Does the middle group even understand the clarity? And so the first thing that you should be doing is, in the clearest sense is driving out fear. So the do now, ask forgiveness laters are fear that if they don't do it, they won't be the leaders. The middle group is pretty clear what their fear is, you don't give them clarity of what they can and can't do. And the third group is fear of changing, losing their job, "AI is gonna replace me." So that's all a spectrum of understanding fear at the human level. And so maybe that is one of the first things you should address before you actually set a grand strategy. And we know Deming has a lot of thoughts about this, and then we break into sort of like... 0:33:48.6 Andrew Stotz: Okay, so let's stop at that. 0:33:50.1 John Willis: Yeah. Yeah. 0:33:51.6 Andrew Stotz: Fear. 0:33:53.0 John Willis: Yeah. 0:33:54.5 Andrew Stotz: That is something that remains in your belief system that is supported by Deming. Did you have that awareness when you were in... Let's just think about before you came across Deming. 0:34:08.1 John Willis: Oh, oh, yeah. 0:34:08.9 Andrew Stotz: Let's say you were doing all that stuff with Goldratt and all that but then when you came to Deming, did fear come up as, oh, wow, this is obvious, or did you learn that later and you see it now more? 0:34:21.3 John Willis: Andrew, this is why you're good at your job. This is good. This is a great question. No, really good... I love questions where I have to really deep think about it. So I think that I kind of always... It wasn't until DevOps that I understood what failing was about. So just before, like the nanosecond before I'm learning what Deming's saying about PDSA and failing and how the whole structure of learning is, I had this sense, but I don't think I was baptized yet on... And to me, I'll put fear and failure in the same bucket, right? Because it's a very... They are, in a lot of senses, the same thing. But certainly I can put them in the same bucket. So I had a sense, but it wasn't until we started seeing fast fail in DevOps. So DevOps, one of the things with DevOps was shorten the feedback loop. That was one of the core tenets of DevOps. Like, instead of waiting three, four weeks, five weeks, six weeks to deliver some software, or six months, and then by the time you deliver it, you're onto... The whole group that built it is now doing something else, let's just be able to turn a line of code into a delivery now. And that was revolutionary, right? And it's changed the universe. I mean, you don't have the big AI providers today if you didn't have DevOps. 0:35:46.4 John Willis: You would not have Airbnb and Uber and all that if you didn't have DevOps. Right? So that... And that sort of realized that this fast feedback loop is really an interesting thing, right? And the fact that it is telling you fail fast because then you learn fast and then you correct fast. And you... And so right around that time, I'm doing this research on Deming and starting to understand epistemology, the theory of knowledge. And so, again, I don't think... Like I said earlier, I don't think I had the... And vocabulary's too loose of a word. I don't think I had the structural understanding. Like, I didn't know what the word epistemology meant [laughter] before I started learning Deming. So I... So it was really... There were flavors of understanding what learning was, but it was DevOps that literally sort of put it to the front of why this works, how it does. And then I got... Again, a lot of careers is just being lucky, right? I just happened to sort of tap into this Deming thing through meeting Gene, learning about Goldratt, and then having this good friend tap me on the head and say it all goes back to Deming. And so, so and then that point, then it sort of opened up the whole world of epistemology. And it wasn't until I wrote the book where I started realizing it was pragmatism. 0:37:07.2 Andrew Stotz: And did that... Does that fail fast, does that method of accelerating the feedback loop that happened through DevOps as you've explained, does that remove a lot of fear from where people would be... 0:37:19.6 John Willis: Oh yeah. 0:37:19.7 Andrew Stotz: Much more... So that all of a sudden says, "No, no, no, it's okay to fail. We'll see that in a day, in two days, and then we're gonna iterate from that." So, okay, I understand how that kind of reframes fear of failure. But then you now talked also about the idea that it's a big element that you see, everything goes back to Deming. Nowadays you see this fear. How does it connect with how you see fear today in the workplace or in organizations? 0:37:50.6 John Willis: Well, again, I think it's the same thing. I mean, I hear people talk about now that one of the big discussions right now and I always look for the anti-pattern of where the discussions go, right? There's this big discussion about AI slop, right? In fact, last year it was we were all concerned about hallucinations. And I'm not dismissing that, but like, if you know how to run AI and infrastructure harnesses and build ground truth in an organization and you understand how your internal audit works, hallucinations are not, let me repeat this, are not a problem in 2026. They are not a problem. You could make them a problem by not understanding what I just said, but they are not a problem. So today's hallucination frenzy scare is what's called AI slop. And I guarantee you in 2027, it'll be something else. But... And I'm not saying it doesn't exist. It does exist, right? But so people are sort of calibrating, what is the cost... There's this counter-reaction to AI coding, not even assistance, people are now using pure agent coding, right? And the question that I think Deming would ask and maybe if there is some divine proxy of me speaking through Deming or Deming speaking through me is that the question that people are now looking at is, "Slop is so bad, we're creating so much code, should we ease back to the longer cycle for ideation and delivery and that process?" Because it's costing us a lot of money on the implementation side. 0:39:20.8 John Willis: The error, the time it takes to remediate the slop is starting to outweigh. Well, that's just bad organizational behavior and design. But okay, but so now I've had this argument with a major corporation, the CIO the other day, where I was saying you have to create this hourglass effect. For you got to create the funnel and then you got to have the control system that slows things down and speeds it up. And he was saying, "But yeah, the cost of the slop is all this stuff." And I said... What I said is, "Yeah, but what you're missing is..." and this is a company that did really well in DevOps, I worked with them years ago through the DevOps transformation and they understood the fast feedback and I had to re-explain the idea that, yeah, there's a cost to AI slop, but if you're not calibrating that with the cost of non-fast feedback and learning because your fear is this slop is gonna get us back or make you knee-jerk reactions, we're gonna see if we can slow down the ideation, maybe we move too fast. And again, I don't... There are scenarios where that is absolutely true, but that is, first understanding your problem. And your problem isn't slow down the ideation process. Oh, we should spend more time ideating because what does that do? It goes back to the old school where we're spending way too much time in the ideation. By the time it actually gets implemented, the feedback loop of learning is way too long. So I think you're better off at least measuring... And this is where variation comes into play. Measuring if I decrease the ideation time, do I get more value from the fast feedback because I can understand the problem, I can fix it faster? And again, that was one of the core tenets of DevOps. But I find people now pushing back because they're scared of AI slop and it's costing more remediation time. So again, I think these are multiple ways of thinking about how fear... [overlapping conversation] 0:41:26.9 Andrew Stotz: Yeah, so besides... 0:41:27.1 John Willis: The fear... And I was just gonna say one... Sorry to cut you off. 0:41:29.0 Andrew Stotz: Yeah, go ahead. 0:41:31.0 John Willis: But one of the biggest problems I've seen over the years is I think the knee-jerk reaction is the symptom of fear. Right? And so I've seen this over and over where a bank gets pawned and so they put out a req for a hundred IT sec professionals in a city where you can best case hire 10 one year. Right? So again, I think that there's that combinatorial fear, knee-jerk reaction. 0:42:00.5 Andrew Stotz: If you were to pick one other area of Deming that really stands the test of time for you, as opposed to a Deming disciple, let's say someone that's trying to implement everything that he's talking about and they're trying to do it in their little manufacturing company or their service business, which I interview those guys. 0:42:09.1 John Willis: Yeah, yeah. 0:42:17.6 Andrew Stotz: But in your case, in some ways it's like you swam through a Deming period of time, absorbed everything and now you're on to other stuff. I'm just kind of interested about what else is lasting? 0:42:35.2 John Willis: Yeah, no... 0:42:35.3 Andrew Stotz: Just one thing. 0:42:35.6 John Willis: And I think maybe, Andrew, maybe part of a problem of the institutionalized Deming conversations is it doesn't always have to have the word Deming in it. In other words, I'm not criticizing you. I'm just saying that I see it more as it's in my DNA. It's part of how I look at things. And so I'll give you a great example. This is pure Deming, but I wouldn't think of it as, "Oh, let me explain this way I want you to evolve in AI because Deming would say..." I don't start that way. But I will tell you that when I came up with this idea and it's called an ideation, AI ideation hackathon. Right? Because everybody's running tech hackathons, AI hackathons. And that's a terrible, terrible, terrible idea. And there's technical debt, you're just making a lot of mistakes there. 0:43:01.7 Andrew Stotz: Right. 0:43:27.8 John Willis: It's a knee-jerk reaction. So the ideation hackathon is sort of something unique. I was doing some consulting for the CMO of a large database company, but got into AI and I helped them, it's called MongoDB, I don't do any work for them anymore but I helped them launch their AI solution. And I did a lot of technical hackathons and I just kept seeing how all the chaos of these technical hackathons, people would build stuff, it would just wind up in GitHub repositories, it would go nowhere. And I finally said, "Why don't we just strip out the technology and focus on the ideation process?" Right? And so that becomes a pure implementation of PDSA. Right? Because in a PDSA, if I was gonna sort of explain it in a Deming way, a hackathon would be a terrible way to implement a PDSA. "So let's build the Sistine Chapel and then let's figure out, let's study the results." Or why don't we start small as an organization? This is why I tell my first... Right now, CIO asks me, "Okay, John..." and usually the conversation ends at this, "What would be your 30-day, 90-day plan, 180-day plan?" 0:44:41.0 John Willis: I'm like, "Not to have one." Yeah, but then I sort of, I talk about two ways to deal with where they're at. And I say that one is something I've done over years, was a qualitative. I do these large where I interview 300, 400 people and I use true qualitative analysis approach to interviewing people, build categories, and structurally design what the place looks like. Right? And that's very... But it's very expensive and it takes... Expensive not in the money, but the time. The new sort of one that CIOs, at least a small percentage of bite onto is, "Why don't we run some ideation hackathons?" And here's the value, you're not writing any code. You're letting people focus on learning how to ideate. Because remember I said earlier, AI is not a technology transformation, it's an organizational learning change. So let's focus on the organizational learning structures without giving any of the technology or the code. But do the hackathon, and the readouts are what you would have built minus the specific tools. And it's glorious because you actually you get to see all the stuff without expending tokens. You don't build the risks. Because anybody who tells you they can sandbox experiments in AI is lying, absolute lying. If anybody's followed the recent Open AI Hugging Face one, it was the most insane escape. 0:46:10.9 John Willis: So, and then the other idea is I don't want 30 of my executive administrators all picking their own tools and all trying to solve all their C-level bosses' problems. And by the way, there's the whole security exposure is, I've done ideation hackathons where an EA says, "I got this idea. I wanna take my P&L or my profit or whatever of some proprietary information on a spreadsheet and throw it into Claude and have Claude..." I'm like, "Yeah, no, no, no, no. Let me explain how that goes into Claude." It literally, it traverses through a bunch of internal structures that leave stuff laying around. And by the way, even though they say they don't train on your data, they have your data. Like, you don't want that data in there. So the ideation hackathon, I think, is a really good... And so I think the main point to that is, although I don't walk in the door and I think one of the... Again, your listeners, I'm like attacking your listeners basically but I think one of our problems is, we try to build our, some people try to build their skill set around like, "I'm a Deming expert. I'm gonna teach you how to do Deming and everything's gonna be great because of Deming." as opposed to let's just make the water Deming, the water, the fabric of what we do. And every once in a while it does make sense to be able to say, "Hey, you know that..." And I won't go back and say I won't lead and say, "Well, Deming tells us..." because I'm not gonna get the gig if I just go too much on Deming anyway. But I will say at some point, I'll say, "Here's the deal. We've got over 100 years of management knowledge on how to do the right things. Let's pay attention to those things." Right? And that's the Deming, that's the Shewhart, that's the Ackoff, it's the Ashby, it's the... We can go down the list, right? Senge. 0:48:06.2 Andrew Stotz: One of the things I was thinking about a while ago was, when Dr. Deming wrote 'Out of the Crisis', he was telling us that we were in a crisis and that we needed to think a new level of thinking. Did it work? Are we out of the crisis? Did people take on board what he taught? Where are we now? That was 1986. 0:48:30.7 John Willis: Yeah, I know, I know. 0:48:31.7 Andrew Stotz: On the one side you can say America's brought incredible amount of innovation and businesses are huge and other countries and other regions struggle to catch up with America. So on the one hand, you could say materially it appears like we're there. But on the other hand, when you look at the way things are managed, you could argue, yeah, not much has changed. 0:48:56.7 John Willis: It's a tough one. It's a tough, I mean, let's just face it, large-scale organizations of high consequences are so full of bureaucracy. Humans interacting at that scale is probably the hardest organizational problem there is, right? You can study anthropology for the next 40 or 50 years and still not have a good clue of how to. And people do, right? So, yeah, it's hard. And why things work, why they go through the... I mean, I talk about the Peterson at Ford, right? And then Ford, turns out there were a lot of other... There are these other conflicting things that happen, industry changes, financial models change. Why did Ford have this incredible success when Peterson called Deming? And then some number of years later, they're back to the old ways, right? We got General Motors, we got all that. I will say this, and I hadn't really thought about this until you asked the question. One of the things I did focus pretty heavy on is Deming's influence on Toyota. And now there's a lot of debate and this is where people get pretty mean with me. I mean, Dr. Spear, I love Dr. Spear. He wrote 'High Velocity Edge' and he's a genius. He was MIT Sloan. And every time I'd see him, "Well, you know, John, Deming and that Six Sigma stuff never worked." And I'm like, "Alright, first off, he didn't do Six Sigma. Second off..." 0:50:21.6 John Willis: And then he told me one time, he said that Deming had no influence on Toyota. I'm like, "Yeah, that's just not blatantly untrue. I'm sorry, you're a PhD genius, I'm not. You're wrong." And so I've been hitting him... Over the years, I hit him with a lot of evidence of Deming's influence on Toyota. And it even goes back to Denco Densco and some of the same. But here's the thing, right? I... There's a woman called Katie Anderson. She's got a book, Learning to... 'Leading to Learn, Learning to Lead', where she met a guy who spent four decades at Toyota, this Dr. Yoshino, and she interviewed and wrote a book about his career. She runs a Japan study trip. I did a Japan study trip a couple of years ago and I got to meet him. And I... He hired at Toyota in 1966. He worked alongside Ohno, Shingo. He was there. He was a junior guy, but he was the guy they were yelling at, "Do this, do that, do this." right? So he was there. 0:51:23.9 John Willis: I told him, I said, "There are people that believe in the US that Deming had no influence on Toyota." He could not believe that that question even could come up. And he told me, he said, "John...", he doesn't really speak good English, we had a translator, he said, "Let me tell you what Deming taught us. He taught us to understand data." And at first I didn't grok that, but then I started thinking about variation. And although there's a lot of people that say that that didn't carry through too, but if I look at what Agile, Lean, and ultimately become DevOps, I in that book trace it pretty strongly back to Deming's influence on Toyota. And you can't deny Lean is not the core of Agile Lean, today's Lean, right? Toyota Production Systems, to be clear. So then I would say that the lasting impact of Deming is not what happened in the '80s when the Americans started understanding what he did, because maybe that translation, maybe it had to be... I asked Doris Quinn this and she said, "Oh, that's interesting." Because I said this, I said, "Could it be that Japan influenced Deming as much as he influenced Japan?" And I think it did. And I think the point was they were... 0:52:45.6 Andrew Stotz: It was a love affair. 0:52:46.3 John Willis: And yeah, and they were more malleable to his messaging. 0:52:50.3 Andrew Stotz: Well, they were more malleable because of their condition, but they also were more susceptible because of the structure of the society. 0:53:01.6 John Willis: Exactly. Yeah, but even the sort of community structure. I'll tell you another quick story on that study trip where we visited an elementary school. And in the elementary school, they had no janitors. Every sort of public school is like this, right? They have no janitors. And the kids, they literally clean. At about 2 o'clock, a bell goes off and some kids rotate and they do the bathrooms, some people... Imagine in an American school, some ritzy parents, "My son cleaned the bathroom?" It'd be on CNN. And they rotated serving food. 0:53:20.7 Andrew Stotz: Child slave labor. 0:53:39.7 John Willis: Yeah, yeah, yeah. And then we got to interview a couple of them and they understood Kaizen and all. So me, I start thinking about like, oh my God, this is our... Western culture is so broken because we basically teach everything that's antithetical to that. They get out of college and then maybe they get lucky and get into an Agile, Lean-like structure and we have to break it all down, where their kids come out completely in that sort of community. And we went to a lot of tier-one distributors. You could see the understanding of community and the power of it. And so what I'm saying is, what Deming was giving them saturated to have such an impact on TPS, and it's unquestionable the impact TPS has had on Lean and Agile and DevOps. And if you follow my thread, Lean, Agile, and DevOps have certainly impacted... You don't have places like Google for good or bad, Facebook for good or bad, Uber, because they could never scale... 0:54:40.0 Andrew Stotz: Yeah. 0:54:40.1 John Willis: Without that. So again, I think, I really hadn't thought about this until you asked the question, is I think actually the Deming 1980s renaissance of Deming was a... Seemed like a bubble in retrospect, unfortunately. But actually indirectly, he's had more... And there's a good part of the book that tries to cover that. I do the "What would Deming do?" after he died, if he was alive and all the stuff that happened there. 0:55:06.3 Andrew Stotz: Yeah, I mean, definitely DevOps. And then Eric... What was his... The Lean Startup one? 0:55:14.0 John Willis: Eric Ries. Yeah, Eric Ries. Yeah. 0:55:17.3 Andrew Stotz: That also... Those two really probably did more to promote PDSA and that aspect. 0:55:23.4 John Willis: Yeah, that's right. Oh yeah, scientific method. There is a copy, and I cannot find it anywhere, there is a copy of Eric, one of Eric Ries' Lean Startup books that does attribute to Deming, and I cannot find it. 0:55:36.5 Andrew Stotz: It does or does not? 0:55:38.7 John Willis: Does. Does. He's got this thing about the 75th birthday or something. Do you have it? Because I can't find the copy, at some point I read a copy where he does a tribute to Deming. 0:55:50.0 Andrew Stotz: Yeah, I think there's some... 0:55:53.0 John Willis: And then... 0:55:53.1 Andrew Stotz: I have the book and I think there is some reference in the book. 0:55:57.5 John Willis: Yeah, there was one, was like... It was like... I don't know if it was the 70th year, 75th year, and he... So yeah, no, I mean that directly. Lean Startup is literally... Yeah, so yeah. 0:56:10.9 Andrew Stotz: And if we think about people that are listening to this podcast, the people that I really want to listen to this podcast and I really want to get something out of the podcast is people that just don't know Deming. They've never heard of it, but they've stumbled upon it. One of the Deming community said, "Hey, you should listen to this podcast because you'll learn about Deming." And maybe they listen to a couple of episodes and it's a bit overwhelming when they hear someone talking about a lot of detail about this or that. Maybe they bought 'Out of the Crisis' and they got a chapter or two into it and they thought, yeah, that's also a bit overwhelming. What would be your message to that person who's listening right now to say, here's the reason why you shouldn't abandon it because of XYZ or whatever that message is that you've got about what they need to know about Deming? 0:57:01.4 John Willis: Yeah. I mean, I will say this, learning is hard. Change is hard, right? I mean, it sounds cliché, but, yeah, I think all of us who came into Deming, I didn't... When I read, we talked about this, I read 'Out of the Crisis', I was like, I don't know what's going on here. One of the worst things I can advise you to, I hate to say this, and this is probably anti-Deming Institute, is start off by reading his two books. You're better off going out to podcasts like this or other stories. I found that healthcare was chock-full of great stories, particularly about Profound Knowledge, of great examples. And then I went back and read the book and then like, oh my God, this is, now I get it, right? So I think a lot of things that we sort of encounter, a lot of them have... The things that are really valuable have this sort of facing counter-intuitiveness nature to them, and you have to sort of work at that. 0:57:55.9 Andrew Stotz: Yeah. 0:57:56.9 John Willis: And so Deming is hard. I mean, you... If you wanna understand Deming, I would say most people are not gonna get it on the snap. And what I would say to them is, it's worth figuring out what are the parts that he says and he did and his philosophy that could become part of your DNA, 'cause that I don't think anybody disagrees on. And then... And one other sort of short story. And I love Bill Bellows and I would say listen to all his podcasts. He's an amazing guy and just incredibly insightful on a lot of, I didn't really understand Taguchi, but so I did some podcasts with him. But I remember, and I'm not calling anybody out, but he runs the In2:InThinking Group and I've been to a couple of those. And I remember one time we were sitting there and we were having a conversation around sort of a roundtable and somebody asked, as I was talking about a company, they said, "Are they a Deming company?" I'm like, yeah. And I couldn't actually get through the room that, no. Nobody's a Deming company. Like, what is a Deming company? That's the wrong question. So again, back to, you got to be careful about how you think about Deming as using his philosophy to help organizations, because the more you focus on that it is a "Deming philosophy" as opposed to these are the right ways to think about the problems, you fall into this trap of maybe getting lost. Well, that Deming thing worked for about a year or two years and now it doesn't work. Well, if you don't call it a Deming thing, then what were the things that stuck and what are the things that didn't? 0:59:42.5 Andrew Stotz: Yeah. I just wanna remind the listeners and the viewers out there, just go to Amazon and find 'Deming's Journey to Profound Knowledge'. For me, I listened to it as an Audible book, which was fun because I enjoyed the stories and it just reminded me to go back and listen again. And also the additional stories, which I actually hadn't bought until, I had been wanting to buy it, but I didn't. So while you were talking, I got that on Kindle. So that's gonna be my fun. 1:00:13.9 John Willis: Those are great stories. There's a story about Gene Cernan. He was the last guy to land, be on the moon. And as you go through the book, it's really interesting. I did like seven or eight... So I was in no rush to publish the Deming book. I was in a rush to do the AI book. So I would literally get to the third rev, the fourth rev, and every time I'd have more new friends point things out. And by the time I got to like eight revs and I'm like, okay, it's probably time to put this book out. But what happens is as you go with the editor, they just start carving things down. And a good editor makes the strong point, like my 'Devil Wears Prada'. But again, there were so many great stories, like the Gene Cernan one is the last guy to be on the moon, but there was a story about Tracy's Rock and it's just a fabulous story, but it didn't have any place in Deming's Journey of Profound Knowledge. It was just an add-on that sort of took you off course. But now, in a standalone book, it's a great story. So there's a ton of those. The guy who created Piggly Wiggly was this genius. Like, again, it didn't really fit in there. But as a standalone story and I even do a little bit of, like, this would have been in chapter 15, so if you read both, you get a sense. And the worst thing I can tell you, though, is I had one person, I was at a conference I was laying the book, the Profound Stories book was laying around, and I guess I came back, he was at a booth, and he read it, and he goes, "John, can I talk to you about your book?" I'm like, "What?" He goes, "I don't know." I'm like, "Oh, dude, you can't read that book without reading 'Deming's Journey to Profound Knowledge'. It would be a terrible book if you didn't know what the premise was for where it came from." So, yeah. 1:01:59.7 Andrew Stotz: So in wrapping up, what would you like to leave the audience with from this discussion and from your journey into the teachings of Dr. Deming? 1:02:11.3 John Willis: Yeah, I think you have to start thinking about... And again, I know it sounds like I'm trying to sell the book and you're doing a better job than I am anyway but the last third of 'Deming's Journey to Profound Knowledge' was what would Deming do had he survived another 20 years? Right? And probably nothing because he was pretty old and not healthy. But the... So, I mean, question then is, as we think about organizational behavior, what are the core things? And I think Profound Knowledge is a great way. I, again I... Again, I don't walk in and say, "Oh, we're gonna... CIO, we're gonna solve this problem by applying the four elements of Profound Knowledge." That's not how I start that conversation. But I'm certainly thinking about systems thinking because that's first and forefront. Like, how are you thinking about... Like one company recently I was with, they got... Some of the big AI providers are giving well-branded companies all-you-can-eat AI. Like OpenAI is saying, "Hey, you know..." That's a terrible idea, terrible, terrible. Because now you're just building technical debt up the gazoo, right? So again, to be able to see the forest behind the trees, what's the systems thinking effect of that? How are you learning? What's the epistemology, the theory of knowledge behind that? 1:03:39.2 John Willis: Are you applying... In the book, I tried to codify my understanding of, like, the theory of knowledge is, how do we know what we think we know? The variation is, how can we see what we think we know? The psychology is, what are the... Let's take a second and what are the blind spots? And then I think of it as a feedback loop is, are we continually like if you listen to Bill Bellows, he does a great job of sort of explaining systems thinking through the sort of vehicle of Taguchi or Ackoff but are we just continually looping through that process as, "Let's take a bigger chunk, let's take a bigger chunk, let's take a bigger chunk"? So Profound Knowledge, not so much that you have to walk in and be an expert on 'Deming's Journey to Profound Knowledge', or more specifically, The System of Profound Knowledge. The idea is, can you use those... And the reason I fell in with 'The System of Profound Knowledge', why that was what hit my core, because I will say, out of my five decades of doing all this crazy stuff in technology, I can't think... I mean, there's a lot of cool frameworks that I use as auxiliary, and frameworks I'm using loosely but The System of Profound Knowledge is the one framework that to me beats all other frameworks because it covers epistemology, it covers understanding statistical analysis or analytical statistics. Right? Which is very important. It brings in the biases, the... All the sort of things about how people think, blind spots, and then it throws together the wrapper of appreciation of a system, so... 1:05:23.2 Andrew Stotz: Yeah. Well, John, on behalf of everyone at the Deming Institute, now you see your picture on the cover. [laughter] 1:05:32.2 John Willis: There we go, man. 1:05:33.7 Andrew Stotz: I wanna thank you. It's a great discussion and it's long overdue. 1:05:37.7 John Willis: Sure. 1:05:37.9 Andrew Stotz: And for listeners, remember to go to deming.org and jump into DemingNext to continue your journey. This is your host, Andrew Stotz, and I'll leave you with one of my favorite quotes from Dr. Deming, which is, "People are entitled to joy in work." 1:05:42.4 John Willis: I love that you end with that.

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BONUS Why AI Is Agile's Best Use Case With Melissa Reeve

Scrum Master Toolbox Podcast

Play Episode Listen Later Sep 26, 2026 35:47

BONUS: Why AI Is Agile's Best Use Case With Melissa Reeve AI is often framed as a technology rollout, but Melissa Reeve makes a different case: organizations that already know how to learn, adapt, and improve are better prepared for AI. In this BONUS episode, we connect Lean, Agile, DevOps, and AI-native work, and explore why Scrum Masters may be closer to the center of AI adoption than they think. From Toyota Production System to AI-Native Work "I didn't really have words for what would later be my career. I didn't know about systems thinking. I didn't know about this thing called Agile." Melissa traces the through-line from studying the Toyota Production System in Tokyo, to early Agile marketing, to developing intellectual property at Scaled Agile, and finally to AI. Her point is that Lean, Agile, and AI-native work are not separate conversations. They all depend on sensing what is happening, shortening feedback loops, learning from reality, and improving the system instead of only optimizing individual tasks. The DevOps Lesson for AI Adoption "People go from doing the task to building, monitoring, and maintaining the automations that do the task." Melissa's AI turning point came after ChatGPT arrived in November 2022. At first she was skeptical, then she started seeing end-to-end marketing workflows that could be changed with AI. That reminded her of the DevOps shift, where software teams moved away from throwing work over the wall and toward automated testing, deployment, and delivery pipelines. For Scrum Masters, the lesson is practical: AI is not only about automating Jira tasks or writing user stories faster. It changes the workflow, the roles around the workflow, and the learning loops that keep the work useful. Scrum Masters as AI Change Leaders "What are Scrum Masters really good at? They're good at helping teams adopt new ways of working." Melissa sees a positive opening for Scrum Masters and Agile coaches. Organizations have bought AI licenses and told people to experiment, but many leaders are still unclear about how AI should change real work. Scrum Masters already work with flow, bottlenecks, experiments, psychological safety, and improvement backlogs. That gives them a useful place to start: map one or two workflows with the team, clarify decision rights, identify where AI can remove or improve steps, and surface concrete wins that others can learn from. From Linear Organizations to Hyperadaptive Work "A hyperadaptive organization compresses both of those dimensions." In Hyperadaptive, Melissa contrasts linear organizations with hyperadaptive ones. Linear organizations move through strategy, execution, concept, and delivery with many handoffs and delays. Hyperadaptive organizations compress those delays by organizing around value, distributed decisions, and continuous learning. She points to Tomorrow.io as an example of an AI-native company that could run a much smaller marketing team because workflows were designed differently from the start. She also uses Moderna to show the other side: a large pharmaceutical company using AI to pursue a goal that would be impossible under normal industry timelines. Learning Loops, Communities of Practice, and the Retrospective Backlog "We surface our backlog of improvement items and there they sit." For Scrum Masters, Melissa brings the conversation back to familiar territory: communities of practice, retrospectives, and improvement backlogs. Moderna's AI rollout included ways to identify power users and spread learning through a community. Scrum teams already have the bones of that system, but the weak point is often follow-through. Teams identify improvements, then lose track of them. Melissa's challenge is to use AI to manage those learning loops better: keep improvement items visible, help prioritize them, watch capacity, and make sure learning from retrospectives turns into action. The FOCUS Framework for Choosing AI Use Cases "Is it organizational? Does it fit with your organizational goals or your team goals? Or is it just a random act of AI?" Melissa uses the FOCUS framework to help teams choose high-value AI work instead of chasing every new possibility. Fit asks whether the idea connects to team or organizational goals. Organizational pull asks whether others will use it, or whether it is a one-person tool. Capability checks whether the team can actually build it. Underlying data asks whether the data is good enough. Success metrics ask how the team will know the AI initiative made a difference. This is a natural fit for Scrum Masters because it connects AI adoption to value, capacity, and inspect-and-adapt thinking. The Five Stages of AI Adoption "AI learning is social learning, and we need to harvest the learning from each other and spread it." Melissa outlines five stages of AI adoption. Stage 1 is foundation: named AI leads and AI councils. She warns against assuming the best power users are automatically the best AI leads, because the role needs change-agent skills. Stage 2 is AI augmentation, where teams examine workflows and build support structures such as an AI Activation Hub. Stage 3 is automating end-to-end workflows. Stage 4 is scaling those automations. Stage 5 is interconnected value streams driven by AI and AI telemetry. Stages 3 and 4 are the messy middle, because jobs shift, roles change, and organizations move from functional silos toward value-stream orientation. AI, M-Shaped Skills, and More Complete Teams "I'm hopeful that in the age of AI, with these adjacent competencies, that we can create more complete teams." Vasco and Melissa connect AI-native work with the idea of M-shaped people: people with deep skills in some areas and useful range across others. Melissa notes that AI can unlock adjacent competencies, making it easier for teams to cover skills that used to require fractional specialists. For Scrum Masters, that means the future is less about defending a title and more about understanding durable skills, purpose, and the contribution they can make as team boundaries and role boundaries keep changing. About Melissa Reeve Melissa Reeve is the author of Hyperadaptive: Rewiring the Enterprise to Become AI-Native. She's worked with the Toyota Production System, Agile marketing, and executive leadership at Scaled Agile. She helps organizations move beyond AI pilots by building the human, learning, and operating-model capabilities needed for AI-native work at scale. LinkedIn You can link with Melissa Reeve on LinkedIn and learn more about her work at Hyperadaptive Solutions.

JFrog's Focus on Supply Chain with Agentic AI

Tech Disruptors

Play Episode Listen Later Sep 25, 2026 44:06

Jfrog CEO Shlomi Ben Haim sits down with Mandeep Singh, Bloomberg Intelligence's global head of technology research, ahead of their swampUP 2026 event. The evolving software supply chain, driven by AI-agent deployments, MCP servers, and reusable skills, is emerging as a major trend that could reshape the broader DevOps market. They also discuss the security vulnerabilities with increasing model capabilities and the OpenAI-Hugging cyber incident.

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Open Source and the Future of Databases with German Eichberger

Screaming in the Cloud

Play Episode Listen Later Sep 24, 2026 23:45

What happens when open source, AI, and decades of database technology collide?Corey Quinn sits down with German Eichberger, Principal AI Engineering Manager at Microsoft, to dig into DocumentDB, why it's built on PostgreSQL, and the realities of MongoDB compatibility. They explore how Kubernetes and databases have evolved to better support stateful workloads, why MCP servers could give AI agents safer database access, and how AI may dramatically increase the number of databases organizations need to manage.Show Highlights: (0:00) Databases in Volatile Environments(00:12) Welcome and Introductions(01:20) AI Titles and Pay Signals(02:53) Why DocumentDB Exists(05:04) Mongo API on Postgres(07:15) No Forking Postgres(08:09) Compatibility and Standards(12:12) Governance and Roadmap(15:15) Kubernetes and MCP AgentsSponsored by: duckbillhq.com

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RR019: Season 6 Kick-off with Dave and Rob

Cloud Realities

Play Episode Listen Later Sep 24, 2026 70:06 Transcription Available

We're back and Season 6 of Realities Remixed starts now! After a summer packed with new ideas, major industry shifts and relentless innovation, Realities Remixed returns with fresh perspectives on the forces transforming business, technology and society.In this season-opening episode, Dave and Rob dive headfirst into the biggest opportunities, toughest challenges and emerging realities facing leaders today. From AI and digital disruption to leadership and the future of work, they set the agenda for a season filled with bold conversations, powerful insights and remarkable guests. TLDR00:22 – We are back after the summer break!03:00 – Hang out: Dave is confused and favorite summer cocktail11:03 – Before we begin, let's review a few important safety considerations13:27 – Dig in: The Trends13:55 – The AI Economy and model behind it19:37 – Adoption lag26:22 – The technology stack is being reset again34:50 – Cybersecurity, sovereignty and trust become strategic priorities39:20 – Summary Part 141:17 – Part 2, The Human experience 47:39 – Society is rebalancing after digital saturation 56:42 – Leadership responsibilities are expanding 59:54 – The next frontier is already emergingHostsDave Chapman: https://www.linkedin.com/in/chapmandr/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett: https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgeminirealitiesremixed@capgemini.com

Iterative Incremental #3 - Vibe Coding: My First Reaction and the Reasoning Behind It

Dan The Dev

Play Episode Listen Later Sep 24, 2026 22:43 Transcription Available

When vibe coding went mainstream, my first reaction wasn't panic. It was curiosity. Then came a sharper question. The speed never bothered me. What bothered me was that not understanding the generated code had become part of the workflow, something you were supposed to accept.In this episode I talk through how I reasoned about it, based on years of XP and DevOps. TDD, refactoring and continuous delivery aren't rituals to skip: they're the brakes that make speed safe. Vibe coding takes out the understanding loop that comes before the tests. Public incidents showed what happens when understanding is treated as optional at the moments it matters most. This isn't an ideological stance against AI. I'm against using AI without discipline, and I wanted AI to help me carry the cost of discipline instead of skipping it.Follow & subscribe Connect on LinkedIn for the ongoing conversation and the reflections that don't make it into an episode:https://www.linkedin.com/in/daniele-scillia/One framework or practice per week, straight to your inbox — subscribe to the newsletter:https://learnagilepractices.substack.com/subscribe

ai public vibe agile coding devops reasoning xp incremental first reactions tdd iterative refactoring continuous delivery

In case you missed it....How Do You Build AI That Actually Works 99.999999% of the Time? With Tina Tarquinio Chief Product Officer of IBM Z and LinuxONE

IBM Analytics Insights Podcasts

Play Episode Listen Later Sep 23, 2026 44:07

Send us Fan MailDive into the powerful world of mainframes! Chief Product Officer of IBM Z and LinuxONE, Tina Tarquinio, reveals the truth behind those eight nines of uptime and explores how mainframes are evolving with AI, hybrid cloud, and future-proofing strategies for mission-critical business decisions. Discover the cutting-edge innovations transforming enterprise computing—from on-chip AIU and Spyre AI accelerators enabling real-time inferencing at transaction speed, to how LinuxONE is redefining hybrid cloud architecture. Tina discusses DevOps integration, AI-powered code assistants revolutionizing mainframe development, compelling AI use cases, and shares her bold predictions for the mainframe's next 100 years. Plus, career advice from a tech leader and what she does for fun!00:46 Tina Tarquinio03:18 The Most Mainframe Surprise09:12 What IS the Mainframe Really? 8 Nines!14:40 On Chip AIU, Spyre Inferencing18:11 Mainframes with Hybrid Cloud19:11 The Linux One Pitch19:59 Exciting Mainframe Innovations22:09 DevOps23:36 Code Assistants26:03 AI Use Case27:49 Future Proofing Decisions37:17 Regulations38:45 Bold Prediction38:58 Mainframe 10040:48 Career Advice42:24 For FunLinkedIn: linkedin.com/in/tina-tarquinioWebsite: https://www.ibm.com/products/zWant to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

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In case you missed it....How Do You Build AI That Actually Works 99.999999% of the Time? With Tina Tarquinio Chief Product Officer of IBM Z and LinuxONE

Making Data Simple

Play Episode Listen Later Sep 23, 2026 44:07

ai discover reach missed ibm devops chief product officer actually works nines mainframe mainframes al martin ibm z aiu linuxone

Cloud Posse DevOps "Office Hours" (2026-09-23)

Cloud Posse DevOps "Office Hours" Podcast

Play Episode Listen Later Sep 23, 2026 60:46

Cloud Posse holds LIVE "Office Hours" every Wednesday to answer questions on all things related to AWS, DevOps, Terraform, Kubernetes, CI/CD. Register at https://cloudposse.com/office-hoursSupport the show

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Episodio 160 - ¿Le darías las llaves de producción a una IA?

Dynamic Devs

Play Episode Listen Later Sep 23, 2026 43:25

La IA ya no solo está ayudando a escribir código. También empieza a entrar en el terreno de la infraestructura, el DevOps y el SRE. En este episodio, Anastasia Kondratieva conversa sobre agentes que pueden tomar decisiones, escalar infraestructura y operar en producción, y sobre la gobernanza que necesitamos antes de darles ese nivel de autonomía. ¡No se lo pierdan!

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#57 Como nasceu a TechFX? A história por trás da carreira internacional com Eduardo Garay

LowOpsCast

Play Episode Listen Later Sep 23, 2026 65:57

Trabalhar para uma empresa no exterior parece o sonho de muita gente.Mas o que acontece quando você precisa transformar esse sonho em uma carreira de verdade?Neste episódio do LowOpsCast, conversamos com Eduardo Garay (https://www.linkedin.com/in/eduardo-egaray/), fundador da TechFX (https://www.techfx.com.br), sobre carreira internacional, empreendedorismo, tecnologia e os bastidores de construir uma empresa voltada para profissionais globais.Eduardo já morou em Londres, hoje vive como nômade digital em Barcelona e criou a TechFX para simplificar a vida de brasileiros que trabalham para empresas no exterior.A empresa já movimentou mais de R$ 3 bilhões e ajudou clientes a economizarem mais de R$ 14 milhões em taxas de câmbio.Mas antes da TechFX existia uma trajetória cheia de decisões, mudanças e experiências que ajudaram a construir essa história.Neste episódio, falamos sobre carreira internacional, empreendedorismo, fintech, câmbio, trabalho remoto, tecnologia, mercado global e os desafios de construir uma empresa do zero.E sim... também tem a história de como o Eduardo quase foi parar no mercado de cogumelos.Porque toda carreira tem alguns capítulos que não aparecem no LinkedIn.

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T8i Instances Bursting With Mild Enthusiasm

Play Episode Listen Later Sep 21, 2026 3:33

AWS Morning Brief for the week of September 21st, with Corey Quinn. Links:AWS Direct Connect announces flat-rate pricing for dedicated connectionsAWS improves regional resiliency for root user sign-inAWS Elastic Beanstalk introduces Cluster ModeAWS reimagines the getting started experienceNew low-cost burstable Amazon EC2 T8i instances are generally availableReduce time-to-hire for quality candidates with AI-powered Amazon Connect TalentAWS STS simplifies session token size limits and adds session token size monitoringSeven AWS CVEs and the client-side patching tax

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The Model Writing Your Code Shouldn't Be Securing It

Resilient Cyber

Play Episode Listen Later Sep 21, 2026 30:56 Transcription Available

Jonathan Rende of Checkmarx on why the model writing your code cannot also be the control that validates it, and why rules-based and AI-driven scanning turn out to find almost entirely different bugs.In this episode I sit down with Jonathan Rende of Checkmarx. Jonathan worked with Fortify and SPI Dynamics back in the day, spent most of the last decade leading product teams in developer and DevOps tooling, and came back to security eighteen months ago because, as he puts it, this is the heart of the hurricane. His argument is that AI is a bigger disruption than the internet, SaaS, or mobile were, not because of any single capability, but because it hits roles, process, and productivity all at once.We get into the two waves he has watched play out with CISOs and their CEOs, why the pendulum has swung back toward program and posture questions in the last quarter, what his research team found when they benchmarked deterministic and probabilistic scanning side by side, and why he thinks agentic AppSec raises the profile of the security team rather than automating it away.In this episode:● Why the first half of 2026 became a real inflection point rather than another AI talking point● The two waves: engineering told to run at any cost, then the pendulum swinging back toward posture and program design● Why functional AI-generated code and secure AI-generated code are still two different things● Separation of church and state, and the conflict of interest in letting the model that generates code also validate it● Benchmarking deterministic and AI-based scanning across dozens of open source projects, and why the overlap stayed consistently under 10%● Fidelity, F1 scores, and the absence of real standards or shared benchmarks in AppSec● Why an incentive to reduce risk and an incentive to sell tokens are not the same incentive● Why agents free AppSec professionals for higher-order work, and why this is not a dark factory● Shadow IT becoming shadow AI, and early scans where half surfaced models, agents, and MCP servers security teams did not know existed● Why new threat vectors show up first in fast-moving unregulated companies while regulated ones see more code-level issues● Low-priority vulnerabilities chained into real impact, and why backlogs now matter as much as incoming code● What to change first: metrics defined up front, in-workflow AppSec, and security reviews that went from annual to monthlyChapters:0:00 Intro0:18 Fortify, SPI Dynamics, and a decade in developer tooling1:24 Why he came back to AppSec2:54 Why the first half of 2026 was the inflection point5:27 Two waves, and the pendulum swinging back9:08 Functional AI code versus secure AI code11:58 Layered defense and the condensed lifecycle15:04 What agents free AppSec teams to actually do17:50 Separation of church and state20:15 Fidelity, F1 scores, and not selling tokens23:25 New threat vectors and organizational maturity25:47 Shadow AI and what the inventory scans found27:58 What to change first in your AppSec program30:44 ClosingConnect with Jonathan:LinkedIn: https://www.linkedin.com/in/jonathanrende/Checkmarx: https://checkmarx.comResilient Cyber: https://www.resilientcyber.ioSubscribe for more conversations with security practitioners and leaders.#appsec #aisecurity #devsecops #shadowai #vulnerabilitymanagement #ciso

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A single API for multicloud with Control Plane

DevOps and Docker Talk

Play Episode Listen Later Sep 18, 2026 54:26

Control Plane CEO Doron Grinstein joins me to discuss how they've created an AI-native cloud API that virtualizes multi-cloud and hybrid cloud to simplify management and ship faster.Watch the video of this episode.

N4N064: A Gentle Introduction to Border Gateway Protocol (BGP)

The DevOps Kitchen Talks's Podcast

Play Episode Listen Later Sep 17, 2026 70:12

Border Gateway Protocol (BGP), the routing protocol of the global internet, is finding uses in all sorts of places in 2026 beyond internet routing. It's a huge topic. Large books have been written about BGP and its related technologies, so Ethan and Holly are here with a gentle introduction to BGP. They break down what... Read more »

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DKT101: BORIS, контекстный layer и стоит ли делать AI-продукт в 2026

Play Episode Listen Later Sep 17, 2026 105:27

Говорят, если стартуешь бизнес в 2026 и ты не AI-native, можно не стартовать. Позвали Андрея Девяткина, со-основателя FivexL: он строит AI-продукт BORIS и уже несколько раз его переупаковал. Разбираем контекстный layer, MCP, Bedrock, экономику токенов и почему AI SRE выглядит мертворождённой категорией. О ЧЁМ ВЫПУСК • Как всё началось: на митапе Amazon Q CLI не смог понять, почему упал Vote App на ECS. • Harness как упряжка: LLM даёт лошадиную силу, а Claude Code, Codex и Kiro CLI решают, куда её направить. • Архитектура под паранойю: данные в аккаунте заказчика, Bedrock в zero retention, отдельный аккаунт на клиента. • Живое демо: чистая сессия Claude без памяти, ответ про сервис за минуту и 38 центов. • Пивоты: «context engineering platform» никто не понял, DevOps-агент не дал traction. • Почему AI SRE выглядит мертворождённой категорией и чем от неё отличается AWS DevOps Agent. • Граф и temporal: троублшутинг serverless, RAG без понятия о времени, корпоративная амнезия. • Стек честно: Bedrock Knowledge Base, S3 Vectors, лимиты Titan, сломанный Kimi. • Нужны ли DevOps дальше: три разные позиции и спор про то, умирает ли навык чтения. • Стоит ли стартовать AI-продукт в 2026 и кто платит за токены. ГОСТЬ Андрей Девяткин, со-основатель FivexL (AWS Advanced Tier), AWS Community Builder, лидер AWS User Group в Лас-Пальмасе. У нас во второй раз, первый был в DKT65 про ECS и EKS.

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D2DO313: Operations is a Reconciliation Loop (Sponsored)

technology networking operations cloud reconciliation infrastructure loop aws ned azure devops gartner

Play Episode Listen Later Sep 16, 2026 45:37

In this sponsored episode, Paul Delory of Gartner joins Kyler and Ned to discuss the reconciler pattern for operations and the shift toward continuous operations. Together they discuss how immutable infrastructure, policy as code, and platform engineering help bridge the gap between traditional IT and modern automation. They also highlight Gartner’s upcoming Infrastructure, Operations &... Read more »

TCG084: Is AI Going to Kill Us All? Separating Frontier Risk From Frontier Theater

Play Episode Listen Later Sep 16, 2026 51:11

Is AI going to kill us all? Frontier systems are producing real security failures, but extinction forecasts are being used to support policies that could consolidate control over AI. Eyvonne and William discuss Jacob Coxon’s high-profile resignation from Anthropic, the gap between real technical risks and speculative extinction narratives, and the commercial incentives driving calls... Read more »

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D2DO313: Operations is a Reconciliation Loop (Sponsored)

technology networking operations cloud reconciliation infrastructure loop aws ned azure devops gartner

Play Episode Listen Later Sep 16, 2026 45:37

TCG084: Is AI Going to Kill Us All? Separating Frontier Risk From Frontier Theater

technology networking operations cloud reconciliation infrastructure loop aws ned azure devops gartner

Play Episode Listen Later Sep 16, 2026 51:11

ai risk theater saas frontier separating aws anthropic azure devops cloud computing kubernetes kill us paas gcp digital ocean iaas aiops gke

D2DO313: Operations is a Reconciliation Loop (Sponsored)

Day 2 Cloud

Play Episode Listen Later Sep 16, 2026 45:37

Cloud Posse DevOps "Office Hours" (2026-09-16)

Cloud Posse DevOps "Office Hours" Podcast

Play Episode Listen Later Sep 16, 2026 57:59

live cloud register aws devops posse kubernetes office hours ci cd terraform hourssupport

The Big Problem with GPUs and How To Solve It | Randolph and Kandan, MantisGrid AI

100x Entrepreneur

Play Episode Listen Later Sep 15, 2026 42:45 Transcription Available

We don't want the industry to fall apart, that's why we started this company.6 months ago, everyone was talking about model deployment. Now everyone has moved on to agentic AI deployment and autonomous agent swarms. But all of this is running on an infrastructure that itself is not automated.And this underlying infrastructure has massive GPU cluster systems. If even one GPU fails the whole training workload fails. You can't have 100,000 employees managing 100,000 GPUs. But LLMs are not the right solution for managing the infrastructure.Kandan and Randolph have spent decades operating large-scale telecom and cloud infrastructure, in a world where pagers used to run lives of people managing it. With MantisGrid they have come together to build 'The' model for AI infrastructure.Watch the episode to understand why making AI infrastructure autonomous is so important, why LLMs are not the answer, and what it takes to build the systems that will keep millions of agents running.00:00 — Invisible Infrastructure Behind AI01:05 — The Pager Nightmare04:01 — The GPU Problem Nobody's Solving05:38 — The Cloud Infrastructure Story07:53 — Why Just Watching Isn't Enough09:35 — Building the Waymo of AI Infrastructure15:00 — How an Autonomous AI Infra System Works20:35 — What Happens to DevOps?22:46 — Why LLMs Shouldn't Run Production29:14 — The Path to a Billion Dollars32:06 — The Problem Hyperscalers Can't Solve37:03 — Earning Trust to Run Infrastructure39:55 — When Agents Start Managing Agents-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

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Lambda Slowly Becomes EC2, One Feature at a Time

Play Episode Listen Later Sep 14, 2026 3:51

AWS Morning Brief for the week of September 14th with Corey Quinn. Links:Amazon API Gateway now supports 1 MB execution logs with configurable delivery destinationsAmazon S3 Object Lock now supports variable retention with event holdsLambda's slow-motion reinvention of EC2Amazon EC2 now supports specifying compatible instance types on AMIsAnnouncing second-generation single-rack AWS OutpostsHow AWS thinks about FinOps Automation and TrustIntroducing Amazon EBS Volume Clones across AWS accountsHow to migrate from Amazon CloudSearch to Amazon OpenSearch ServerlessIntroducing Pizza Bot, an open source inbox for AI agents that work in the backgroundThree consecutive CVEs, all AWS-authored code

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The Invisible Network Powering AWS with Matt Rehder

Screaming in the Cloud

Play Episode Listen Later Sep 10, 2026 36:43

AWS VP of Global Networking Matt Rehder joins Corey Quinn to pull back the curtain on the massive network infrastructure behind AWS. They explore resiliency at scale, AWS's move toward flatter networks, the advantages of building custom hardware, and why AI is making networking exciting again.Show Highlights: (01:08) Meet AWS Networking Lead(02:01) Why AWS Avoids Global Outages(05:23) RNG Flat Network Explained(10:08) Overbuild Capacity And Custom Hardware(17:37) VPC Virtual Network Origins(19:50) Why TCP Still Wins(20:38) SRD Inside AWS(21:54) Opt In SRD Transport(25:31) Networks As Utilities (27:24) Learning And Growing Engineers(29:22) Training Talent In House(31:27) AI Rekindles Networking(34:26) Where To Learn Networking

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D2DO312: Networking at Scale: AWS Transit Gateway War Stories

Play Episode Listen Later Sep 9, 2026 42:46

How can network architects successfully manage 95,000 hosts while navigating the complexities of large-scale cloud migrations? Devender Singh, a Principal Cloud Architect, joins Ned and Kyler to discuss the practical realities of managing network chaos, the migration from Transit Gateways to AWS Cloud WAN, and strategies for addressing the technical debt often encountered during enterprise... Read more »

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Play Episode Listen Later Sep 8, 2026 27:46 Transcription Available

Topics covered in this episode: EuroPython 2026 videos are online The State of Django 2026: Boring is so back htmx 4.0.0 has been released

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Claude Fable 5.1 and Other Bedtime Stories

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Play Episode Listen Later Sep 8, 2026 5:46

AWS Morning Brief for the week of September 8th with Corey Quinn. Links:AWS Lambda now supports SnapStart for container image functionsAmazon CloudWatch now supports warm-up periods for alarmsAmazon Kinesis Data Streams announces data delivery to general purpose Amazon S3 bucketsAmazon Linux 2027 is now available in public previewAmazon CloudFront announces API support for flat-rate pricing plansAAA games on a $35 stick: How Luna removes the hardware barrier with AWSHow t54 built a trust layer with Amazon Bedrock AgentCore paymentsIntroducing Claude Fable 5.1 on AWSTokenomics at scale: How Jamf built real-time spend enforcement for Amazon BedrockHow PGA TOUR automated live profanity detection with AWS using Amazon TranscribeAWS and Microsoft Azure collaborate to expand multicloud networkingWe invited a direct competitor into Security Hub Extended. Here's why.Detect stalled Amazon S3 live replication to prevent unexpected storage costsSix AWS security bulletins in five days

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371: MrBeast Bets on Gemini for Survival

The Cloud Pod

Play Episode Listen Later Sep 8, 2026 73:51

Welcome to episode 371 of The Cloud Pod, where the forecast is always cloudy! Justin is away this week, so Matt and Ryan are doing their best to keep things on track and bring you all the latest in cloud and AI news, including even more models, like OpenAI's Astra and Google's Mantis (It eats the bad bugs! Get it?) Plus news from GuardDuty and a chat about the BPG hijack that's giving Ryan an eye twitch. There's a lot to cover, so let's get started! Titles we almost went with this week AI Agents Need Babysitters, AWS Says Zero Trust Softaculous Gets Hacked, Signs Nothing, Regrets Everything GuardDuty Watches the Robots, So You Don’t Have To Cloudflare Hires AI Bouncer for Vulnerability Nightclub AWS Ships Linux From The Future, Enforcing Included Amazon’s Guard Dog Learns 35 New Tricks OpenAI Launches Astra, Bills You By The Token GPT-6 Goes Agentic, Legacy Apps Never Saw It Coming MrBeast Bets on Gemini for Survival Non-Critical Daemons Get a Permission Slip to Crash GuardDuty Gets Choosy With New Detection Rules Astra Rises After Hugging Face Escape Room Incident MrBeast begs Gemini for Survival A big thanks to this week's sponsors: We're sponsorless! Want to get your brand, company, or service in front of a very enthusiastic group of cloud news seekers? You've come to the right place! Send us an email or hit us up on our Slack channel for more info. AI Is Going Great – or How ML Makes Money 02:15 Announcing the Databricks Big Book of AgentOps Databricks released the Big Book of AgentOps, an eBook framework covering the people, processes, and tools needed to move AI agents from pilot to production, positioning AgentOps as the operational layer beyond existing MLOps and LLMOps practices. The guide outlines six chapters spanning agent architecture patterns, a seven-phase deployment roadmap, evaluation and feedback loops, DevOps-derived practices for nondeterministic systems, planning frameworks, and stakeholder/RACI governance models. Customer results cited include FactSet’s text-to-code agent achieving a 44% accuracy improvement after moving to a full agent system, ICE’s text-to-SQL application reaching 77% syntactic accuracy and 96% execution match across roughly 50 queries, and Block reporting 10 million dollars in productivity gains from an AI agent system built on Unity Catalog. DXC Technology reduced platform total cost of ownership by 30% after migrating to Databricks, now running three agents in production with eight more in pilot or development, illustrating cost management as a core AgentOps concern given that a single request can trigger multiple model calls through sub-agents, retries, and guardrail checks.

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080 — A DevOps engineer on DevOps engineering

DevOps Diaries

Play Episode Listen Later Sep 8, 2026 46:13

What if the ultimate goal of a great DevOps engineer is to make yourself unnecessary? Jack sits down with Alex Louderback, Salesforce DevOps engineer and the voice behind The Developer's Developer blog, to unpack what happens when you do your job so well someone else takes it over. Alex and Jack dive into why mapping the human process always comes before touching a single tool, the security risks lurking when AI-generated changes skip proper governance, and Alex's hot take on flow testing. They also get into the real story of turning a Gearset skeptic into the team's number one promoter.

Why the Death of UI Could Change Everything for Businesses

Microsoft Business Applications Podcast

Play Episode Listen Later Sep 7, 2026 38:41 Transcription Available

Full Show Noteshttps://www.theintelligenceagepodcast.com/839Mark Smth speaks with Ashish Bhatia about how his move from Microsoft to Audible changed the way he thinks about customers, AI, and product design. The conversation centers on personal AI, running OpenClaw locally, and why owning your memory, workflows, and data matters more as AI systems become more capable.They also explore Audible's role in learning, the future of interactive audio, and how agents are beginning to replace clunky app-based workflows with more direct, personalized experiences.Key topicsAshish explains the shift from B2B at Microsoft to B2C at Audible, and how that changes the way you learn from customersHe shares why personal AI matters to him more than ever, especially when it involves health data, finances, and memoryMark describes building a large OpenClaw setup with 26 agents, including a nine-agent DevOps team and automated bug fixingThey discuss why running AI locally teaches real systems thinking through failure, debugging, and repeated iterationAshish talks about using OpenClaw to manage daily life, including lunch ordering through Grubhub as a mission-critical workflowThe conversation highlights the importance of owning your memory and being able to move your AI system across machines and platformsThey explore the idea of the death of UI, where agents increasingly bypass app interfaces and handle tasks directlyMark raises concerns about AI companies ingesting books and content, leading to a discussion of copyright, hypocrisy, and cultural attitudes toward booksAshish shares how Audible supports different learning styles, especially for commuters, slow readers, and people who learn better through audio plus textHe outlines Audible's direction toward interactive, multilingual audiobooks with AI-powered recall, discovery, and personalizationResource Recommendations:The Infinity Machine - Demis Hassabis - Amazon.com: The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence: 9780593831847: Mallaby, Sebastian: BooksThe Thinking Machine - Jensen Huang - The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip: Witt, Stephen: 9780593832691: Amazon.com: BooksSapiens - Yual Noal Harari - Sapiens: A Brief History of Humankind eBook : Harari, Yuval Noah: Amazon.ca: Kindle StoreThe Apple Podcast that I have curated - https://podcast.ashish-bhatia.com/feed.xmlAshish Bhatia's website - ashish-bhatia.comIf you want to get in touch with me, you can message me here on Linkedin.Thanks for listening

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N4N063: Link Layer Discovery Protocol

news discovery networking cloud infrastructure analysis protocol networks layer devops ipv6

Play Episode Listen Later Sep 3, 2026 51:16

Ethan and Holly tackle the Link Layer Discovery Protocol (LLDP). They explain how this protocol helps network engineers map network topologies and validate wiring. They also discuss how LLDP devices use frames to send information, mandatory and optional type length values (TLVs), and why security on edge ports remains critical. Episode Links: Watch this episode... Read more »

TCG083: Superintelligence for Everyone: Who Actually Holds the Power?

Play Episode Listen Later Sep 2, 2026 53:22

Mark Zuckerberg argues that broadly distributed personal AI, or a “superintelligence” in his parlance, can increase prosperity and counter the risks of AI being controlled by a handful of government and corporate entities. Drew Conry-Murray joins Eyvonne and William to engage in a lively roundtable where they examine whether distributing access meaningfully distributes power when... Read more »

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TCG083: Superintelligence for Everyone: Who Actually Holds the Power?

Play Episode Listen Later Sep 2, 2026 53:22

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We Wasted 4 Months Optimizing for the Wrong Leads ft. Saif Al-Jabbar Khan

PPCChat Twitter Roundup

Play Episode Listen Later Sep 2, 2026 45:34

Saif Al-Jabbar Khan shares his journey from a DevOps engineer to a successful paid search marketer, highlighting key lessons from his experiences with client management, conversion tracking, and AI integration in digital marketing. Key topicsSaif's career transition from DevOps to marketingImportance of defining qualified leads earlyCommon mistakes in conversion trackingUsing AI for nuanced account analysisThe role of WhatsApp in Middle Eastern marketingStrategies for managing client expectationsThe impact of landing pages on campaign successLessons learned from account auditsChapters00:00 Introduction and Guest Background03:58 The Importance of Qualified Lead Definition11:52 Improving Lead Qualification Rates15:49 The Role of Landing Pages and Client Communication20:04 Adapting Strategies Based on Data Insights22:09 The Impact of Data and System Changes24:00 Advice for Paid Search Marketers Facing Crises26:00 Reviewing and Refining Lead Criteria30:03 Common Mistakes in Account Management33:56 Using AI for Nuanced Account Analysis36:02 WhatsApp as a Key Channel in Dubai38:08 AI and Privacy Considerations42:09 The Role of Journey Aware Bidding43:47 Final Tips for Paid Search Success45:02 Fun Question: PPC Movie Title45:57 Upcoming Events and Networking OpportunitiesFind Saif on LinkedIn Join us on ⁠⁠⁠⁠⁠⁠⁠⁠Slack⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Happy 20th Birthday EC2, You Beautiful Disaster

AI and the Future of Work

Play Episode Listen Later Aug 31, 2026 5:03

AWS Morning Brief for the week of August 31st, with Corey Quinn. Links:AWS Lambda functions now support full IAM resource-based policiesAWS Security Agent (now part of AWS Continuum) now supports budget controls and finding revalidationAWS Secrets Manager adds managed external secrets support for Cisco Security Platform and NetskopeAutomating filtered Cost and Usage Report exports with AWS Data ExportsAWS Glue 6.0 now available with 30% lower price and full Apache Iceberg v3 supportHappy 20th Birthday, Amazon EC2I'm an Amazon SVP who hadn't coded in 25 years. Then I wrote 100,000 lines of code with AI.AWS and DuckLabs: Building the future of analytics togetherState of Kansas modernizes mainframe file transfer using AWS Transfer FamilyFive AWS security bulletins, zero AWS-side fixes

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403: Nancy Wang, CTO at 1Password, on Why Identity Is the Tech Problem of the Decade

Play Episode Listen Later Aug 31, 2026 45:42

Send us Fan MailNancy Wang is the Chief Technology Officer at 1Password, where she leads the global engineering team securing the digital safety and identities of millions of prosumers, families, and enterprise workloads. An expert in building highly scalable systems and data protection platforms, she holds seven patents in cloud infrastructure and serves on the boards of early-stage cybersecurity leaders, including Observo AI, which was recently acquired by SentinelOne to power the data intelligence layer for its SIEM products. Prior to joining 1Password, she became the youngest person ever promoted to Director and General Manager at AWS, at age 31, leading AWS Data Protection to serve 98% of the Fortune 500 and building a multi-billion dollar business within five years. She also helped build cloud and data protection products at Rubrik, held engineering roles at Google and in the U.S. intelligence community, and now brings a rare combination of deep infrastructure expertise and security-first product thinking to the age of AI agents. In this episode, Nancy sits down with Dan to explore the massive security responsibilities of the agentic era.In this conversation, we discuss:Why the transition to autonomous AI agents doesn't require brand-new credentials, and how familiar principles of human and machine identity extend to the agentic era.How a proprietary confidential computing architecture built on specialized enclaves protects sensitive user data, even in the event of a catastrophic central breach.Why 1Password actively chose not to release a public Model Context Protocol (MCP) server despite intense market pressure.How a specialized DevOps agent trained on human incident response can learn to navigate real-time outages, runbooks, and cloud traffic monitoring.Why AI is compressing the cost of execution in software, and why the real career advantage now shifts toward taste, judgment, systems thinking, and deep fluency with AI tools.Why prioritizing potential and tenacity over traditional resumes is the key to building diverse engineering teams, and how sponsorship accelerates the rise of high-slope talent Explore the Conversation00:00 Intro and AI Fun Fact: EvilToken and the Rise of AI-Driven Phishing03:48 Introducing Nancy Wang, CTO at 1Password and AWIT Founder09:07 Secure by Design: Inside the Origin Story and Expansion of 1Password13:32 The Business of Trust: Why 1Password Is in the Security and Relationship Game15:31 Zero-Knowledge Architecture: What Actually Happens if 1Password Faces a Breach?24:06 The Phishing-Resistant Future: Biometrics, Passkeys, and Agent Identity28:17 Inside the Machine: DevOps Agents and Real-Time Incident Response31:22 Rejecting the MCP Server: Why AI Safety Trumps Instant Velocity34:28 The T-Shaped Engineer: Why AI Compresses Execution and Elevates Human Taste39:18 Be a High Sloper: Sponsoring the Next Generation of Tech Leaders Resources:Subscribe to the AI & The Future of Work NewsletterConnect with Nancy Wang on LinkedInAI fun fact article: Hackers use AI to bypass passwords in large-scale phishing attacks Other episodes mentioned on the show:Episode 167 with Amr Awadallah, CEO of Vectara and co-founder of Cloudera, on the tech behind AI search-Join Dan Turchin and 4 seasoned technology and people leaders on Sept. 17 for an executive discussion on AI, leadership, and the future of work. Attendees will receive a complimentary personalized AI Maturity Industry Benchmarks Report ($499 value). Reserve your seat: https://go.peoplereign.io/virtual-event-when-intelligence-is-everywhere-intelligence-is-nowhere

AI Can Do the Work, But Should It? with Adam Larsen

Screaming in the Cloud

Play Episode Listen Later Aug 27, 2026 29:51

On this episode of Screaming in the Cloud, Corey Quinn sits down with Adam Larsen, Principal Developer at Aurora Educational Technologies, to explore what technology and AI should actually look like in K-12 education. They discuss using tech to empower teachers rather than replace them, the risks of outsourcing critical thinking to AI, student data privacy, and what happens when schools become dependent on tools that may not be affordable forever. Adam also shares how AWS became his go-to platform for solving complex education data problems, and why sometimes the best technology is simply the one that reliably gets the job done.Show Highlights: 00:00 Critical Thinking Warning00:15 Meet the Guest01:07 From Psych to Edtech02:07 Teachers and Tool Whiplash07:29 AI as a Teaching Aid10:07 Process Over Shortcuts14:29 Tech Misconceptions in Schools16:38 Privacy and Picking Vendors21:50 AI Costs and Ecosystem Bets26:33 Building on AWS and Wrap UpSponsored by: duckbillhq.com

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D2DO311: Code Review Is Dead – Long Live Peer Review

Play Episode Listen Later Aug 26, 2026 49:41

Traditional peer review processes are breaking down in the new AI era. Dylan Ratcliffe, founder and CEO of Overmind Technology, joins Ned and Kyler to discuss the importance of treating AI as a machine to be audited rather than a peer. Together they share practical advice on how to adapt peer review processes and culture... Read more »

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D2DO311: Code Review Is Dead – Long Live Peer Review

Play Episode Listen Later Aug 26, 2026 49:41

ceo ai technology code networking cloud traditional infrastructure peer aws ned long live azure devops

London Gets an AZ, You Get an Outage