Podcasts about ai llm

As a nurse with MS, I’m interviewed about AI’s real role in care: pattern recognition, human-in-the-loop skepticism, and the Three T’s and Two C’s framework. Click here to view the printable newsletter. More readable than a transcript. Click here for a verbatim transcript Summary I sit in the guest chair on Practical AI in Healthcare with Steve Labkoff. I walk through my experience feeding my own symptom logs, lab results, and ten years of clinician notes into an AI LLM: a physical therapy referral I needed and hadn’t scheduled, a medication side effect my neurologist later confirmed, and a rating scale buried in my chart that no one had surfaced. I describe the less impressive side: the four-pound box of unsorted paper my primary care practice mailed me and the 296 pages of unsearchable PDFs I got back from another system in fifteen minutes. Along the way, I lay out my framework for judging any digital health tool, the Three T’s and Two C’s: time, trust, talk, control, and connection, and explain why I insist on keeping humans in the loop even though the research on that is more complicated than people assume. This isn’t a pitch for AI in healthcare. It’s a working nurse and patient’s honest field report. What’s your experience been feeding your own health data into an AI LLM? Tell us in the comments. Episode Transcript Proem I usually ask the questions. This time I'm the guest. I met Drs. Steve Labkoff and Leon Rozenblit a couple of years ago at a DCI Network conference. They host Practical AI in Healthcare, a show I've listened to steadily, though it creates more tension for me than any other podcast I keep coming back to. Usually, I jettison podcasts that do that. I stay with this one because I approach AI in healthcare the way I approach best health; I'm an N of one and resist generalizing, while most guests do a fair amount of it. I bristle at most of them, wanting the shades of gray that reflect deep understanding. In four of 33 episodes, the guest has had lived experience: ePatient Dave DeBronkart, Amy Price, Hugo Campos, and me. I invited Steve and Leon to join my virtual Reckoning group, which I've hosted since 2019. We give podcasters warm critiques of selected episodes: the kind of feedback you give when you've made a hundred mistakes yourself, can spot them quickly in someone else's cut, and have endless thoughts about production, audience, dissemination, and life. They took the critique well. When Steve later asked me to come on his show to talk about how I use AI, not the theory but the daily grind, I readily agreed. They let me publish it here unchanged, apart from this Proem and Reflection. I struggled to prepare for this conversation. I wanted to wear all my hats, but had to narrow my focus to two. I chose my lived experience and nurse hats. Underneath it all was the question I keep circling back to. Not a cure. Best health, the most function, and Hello, and welcome to this week’s edition of Practical AI in Healthcare. My name is Dr. Steven Lapcoff, and this week I’m actually on my own because my partner, Dr. Leon Rosenblatt, is actually on spring break with his kids, so I am covering for him and he’ll be back in the next week. This week we have a guest who we met at a conference in Boston a few months ago at the Beth Israel at the DCI network. Steven Labkoff: We have Danny van Leeuwen. Danny is a nurse. He has background in giving actual physical care to patients. He actually runs his own podcast called Health Hats, the Podcast, and he’s been using AI in both his personal life and in his professional life very extensively. Also, Danny has a significant medical condition, and I’ll let him explain that in the course of the discussion because it’s with that lens that we got introduced at our patient-centric AI conference, and that’s why we thought it’d be a good idea to have Danny come and have a chat with us. So welcome to the podcast, Danny. How are you today? Health Hats: I’m good. Thank you. Thanks for having me. I appreciate it. Steven Labkoff: So Danny, as you probably have heard because you’ve helped us with our podcast, and for that I want to say thank you. For those who are listening in, Danny runs actually a group that actually helps folks running podcasts improve their podcasts, and he’s had Leon and I on many times to listen to critiques and feedback, and it’s been very, very helpful. Danny, we often start our podcast with asking for folks’ origin stories, like how did they get their cape and their superhero tights. What did you do to get you to this point in your life? And just tell us the background of what brought you here. Health Hats: Oh, thanks. So I’m a child of Holocaust survivors, and my parents– when I was young, my parents were active in the civil rights and fair housing movement in the ’60s. And when I was 16 and I was thinking about the war in Vietnam and worried about getting drafted, I wanted to learn what I could learn about the draft and how I could protect myself and manage. And I went to a church in downtown Detroit, and I went for a session of draft counseling as, you know, a little precocious at 16, and I found it fascinating, and they found me fascinating, and they encouraged me to become a draft counselor. And so I, uh, I actually took their course and became a draft counselor, and what I learned is that you change systems from the inside, not the outside. And I learned how the sausage was made, and that, uh, really pointed me in a direction. The way I got into nursing is really because I didn’t want to cut my hair I had an opportunity for a job at one point, and I could have read water meters or become an aide at the Detroit Psychiatric Institute. And reading water meters paid more, but I didn’t wanna cut my hair, so I got the job as, as nurse’s aide. And while I was there, they introduced me to the idea of going to nursing school, which was amazing. Steven Labkoff: It was more– You got paid more to read meters, water meters, than you did- Health Hats: Yes. Steven Labkoff: That’s unbelievable. Life gives you some real interesting turns and twists, doesn’t it? Health Hats: It does. And I was really fortunate because my first jobs in nursing were in physical rehabilitation and home care. I just happened to be in a place where the Holyoke Visiting Nurses was dying to hire a guy, and I was a brand-new nurse, and they ended up hiring me. And so my first introduction to nursing was not in acute care. It was in home care, and actually, I was the first male public health nurse in Western Massachusetts in 1976. And really, what I learned there was that most healthcare does not occur in the medical system. It occurs outside the medical system. And so when I ended up getting into medical care, it was always so interesting to me that everybody there thought this is where, you know, health happened, which it doesn’t. So over the 20 years of working as a nurse, I’ve worked in, other than the rehab and home care, I’ve worked in the emergency department, I’ve worked in ICU, I worked in pediatrics, behavioral health. And after about 15, 20 years, I shifted from becoming a student of individual health to a student o- of organizational health. And what I mean by that is I got into performance improvement. I led a couple of electronic health record implementations. I had a couple of gigs in the C-suite. I did some consulting. Now, in 2009, I was diagnosed with multiple sclerosis, and when I was diagnosed, I learned that I had had it for 25 years. And since my father died young, he died at 45 when I was 19 of his second heart attack, and so every time I would have some kind of episode, I would get a cardiac workup. And by the time the cardiac workup was done, you know, the episode was over, and this went on two, three, four times a year for a long time. And there was a pattern there, and nobody was connecting the dots for 25 years. That’s very important to me because the pattern of what was going on was in my records for 25 years, but nobody had synthesized it. Steven Labkoff: Yeah, they may have been biased, right? Because of your family history and having these episodes, you know, as a clinician, you get very biased by family history, and that can actually lead you down roads which may not be correct, and it sounds like that’s precisely what happened with you. Health Hats: So I’ve– I wanna bring in the caregiver role because I have been a caregiver for my grandmother, my mother, and a son in their end-of-life journeys. So I’ve been on many sides of very difficult decisions. As you said, that my shtick is health hats, and I’m health hats because I’m a patient, I’m a caregiver, I’m a nurse, I’m an advocate, I’m an informaticist, I’m a podcast host. I wear a lot of hats. And wearing many hats has gotten me a seat at many tables because they can check off boxes. When it was really different to be bringing patients o-on board, I was an easy choice. Uh, I was at the table for technical expert panels at CMS, at National Academy of Medicine, at AHRQ, National Quality Forum, PCORI, Patient-Centered Outcomes Research Institute. But really, I wasn’t really there in it for the seat itself. My goal was always to open seats for people who weren’t there yet Now let’s build the bridge, since this is a podcast about AI, let’s build that little bit of that bridge. So my first, like, serious experience with– Well, I don’t know about my first. I was involved in something that you probably are familiar with, which was the Blue Button Plus program, and my goal in that, I was there both as a patient and as somebody who was working with people with disabilities. I, I was VP of quality for an organization that supported about 40,000 people with disabilities. And my goal for that couple of years of weekly or every other week, I can’t remember, calls was, uh, to add a f- a caregiver field to the data set, and to also introduce the idea that what people needed was information that would be able to say what works for me when I’m in pain and what works for me when I’m afraid, which was an issue for me, and it was an issue for the organization that I was working with at the time. Now, I have to say that the caregiver field got added, so I felt some success in that. But as a nurse leader in the informatics group I was part of, really they were only interested in putting a name in the field, not doing anything with that information, which I- Just collecting, so just collecting the data. Steven Labkoff: They didn’t care what the data was used for? Is that what you’re saying? Health Hats: Correct. Yeah. And I couldn’t– got no traction on the pain and fear, which now that I’m older, I understand why, how difficult that is. Nevertheless, it’s something that’s important to patients and caregivers. So I think I would close this section with that I am both an early adopter of technology and a rapid skeptic, that I’m kinda making this number up, but I’ve probably tried over 100 health apps, and I would say that I’ve used five more than three times. And so I think there’s a gap between what’s promised with digital technology and what’s useful for people. So that’s really why I’m here and what’s guiding for me in this. Steven Labkoff: So let’s take it to the next step. In our prequel, I didn’t even know about your personal background to that degree. Mm-hmm. We can take that one offline later about the Holocaust survivor issues. We, we have family, I have family in that same situation, frankly. Let’s change gears and talk about the challenges that you’ve seen. You opened the door a little bit on that a few minutes ago- Yeah … in terms of people wanting to collect data but not necessarily doing much with the data, not being able to understand the true value of the data to some degree. And you said it yourself, people weren’t connecting the dots. Medical records have always been complicated. They’ve always been bulky. They’ve always been full of information, some of which is really relevant, a lot of which is not so relevant, and connecting the dots to making that a, uh, an important information source is not always an obvious task. So what, what was the particular angle on that challenge that you were trying to gun at? Health Hats: Well, I think we have to take a step back- and think about what is– Well, I’m just gonna speak for myself, okay? I know that I often, you know, as I said, I get asked to sit at the table because people can, you know, check boxes, like is that I’m a patient. I wanna be clear that I’m a privileged white old man with MS living in Boston, but I’m an N of one, and I don’t represent other patients. I’m representing myself here and my perspectives. My goal in terms of my health is best health, and what I mean by best health is optimal health and function, physical, mental, spiritual. Not a cure, but best health for where I am, what I have right now. And to get there, I need my own health data, not just what’s in my clinician’s chart, but what I know about myself, my circumstances, my environment, my history, my habits. Not just my medical history, my life history, my treatment responses. And so that’s like patient-reported data, and that’s stuff that’s only exists because I observe it and sometimes I record it And that’s where it falls apart right away. You were just alluding to some of it, that there’s all this medical data and what’s useful about that. I think Dave DeBronkart was a guest on your show. And when he launched his Gimme My Damn Data campaign, I responded to him with, “Watch what you wish for. You’ll be trying to drink dirty water from a fire hose.” And, and that was years ago, and it’s still true. So six months ago, I, I’d been on a mission to gather my medical data, and my– I’d been with my, uh, primary care practice since 2011, and I wanted all that data from 2011 to 2025. This was, like, in December I started on this crusade of trying to get my data. And actually, two months later, I got a box, a four-pound box of paper, and it was paper that was not in chronological order. And it’s just sitting right here. I’ve scanned it in. It’s not, um- Was it in– Steven Labkoff: Was it a printout of Epic or something, or was it actual- Health Hats: It’s a computer printout. It seems like it’s a vendor that they use to- Steven Labkoff: It wasn’t digital. They sent you, literally sent you a box of paper. Health Hats: Yeah, it was a box of paper. Oh. And then I use a lot the, the Beth Israel Lahey Mount Auburn system, and I asked for the last three months of my records, and I got 296 pages of redundant, non-searchable PDFs, and I got that in 15 minutes. Uh, I see a lot of doctors, so maybe I had seen Hmm. I think I had maybe eight or nine visits, and it just happened to be a three-month period that was busy for me, but I got s- 296 pages. And so that really adds to your comment, which is that access to data and access to usable data are really different. Steven Labkoff: Oh, absolutely. And yeah, I’ll tell you, in my world, I think you know that I’ve worked in the life sciences for many, many years, and we are consumers of healthcare data on many levels. We consume medical claims, we consume electronic medical records, and one of the hardest things about using medical records for research or for outcome studies and things like that is the very fact you’re describing, which is the data tends to be sparse, it tends to be poorly organized. It doesn’t always come in an encoded fashion. Thank God most of what we get these days is at least digital. No boxes of paper for us these days, but it wasn’t so long ago that when it was all paper, we couldn’t get that data in the first place. It just wasn’t even gettable. So at least you’ve made some progress. And- Yeah … yeah, I know that you sit on some national level boards, uh, around outcomes, and you can talk about that in a moment. But those are, you know, those boards are trying very hard to come up with outcome studies and ways of– Let me back that up. They’re coming up with ways of using data to perform outcome studies by harmonizing and, and distilling down to usable forms of this EHR data, which is so challenging. Health Hats: I think what’s key, I– like I, I think I w- I’d like to focus on my data. And so what I wanna do is I wanna see patterns. I wanna see patterns that takes my circumstances, my environment, my habits, my treatment over time, and because I think that these patterns are how I formulate the right questions, so the right questions before I go into a clinical encounter. They’re how I track when something is actually working, and it helps me to coordinate across care teams that don’t talk to each other and make decisions that I can live with that help me attain this goal of best health. So that’s the job, formulate better questions, g- seek better answers, make better decisions. And AI is the tool that I try to use to do it. Now, whether it’s up to the task or not is different. I wanna stick in the nursing angle, if you don’t mind- You know, one of the things that I learned the way I got started in nursing is that my goal as a nurse was to put myself out of a job. Steven Labkoff: So that sounds counterintuitive, but what I mean is from minute one with a patient and family, I’m planning my exit. Like, and to do that, I need maximum face time. I need real present, real conversation, real relationships, not less charting. I was gonna say not charting, not documentation, so that’s just ridiculous. Health Hats: But less, you know. The way you do that, I think, is, you know, less charting, less documentation, you know, not hunting through information you can’t find. And that’s where nursing, that’s a genuine promise. So pattern recognition across specific cohorts of patients. So as a nurse, even though I worked a lot of different places, in each place I worked, there was commonalities. In– When I lived in West Virginia and I was an ER nurse in a super rural hospital, if I had had more information about my patients, their families, I could get– an AI could help me surface those patterns that exist for the people that I’m taking care of, I think I could get time back as a nurse. And if the nurse gets time back, then the patient and family gets the presence of the clinician. So that’s the trade that I’m interested in I wanna go back to that thing about pain and fear. I wanna add what I’ve learned working on the blue button, plus I wanna add cognition. So when you think about it, the data almost never captures the variability of pain, fear, and cognition, and those things are really important because pain changes what you can do and what you can decide. Fear closes your heart. It closes your mind. And so when you’re scared in a clinical encounter, you’re not making good decisions. You’re just saying yes to end it. And cognition is, you know, it varies. Like I can absorb better at 10 in the morning on a good day compared to 3:00 in the afternoon when I’m spent. You know, you could extrapolate this to other people. They have their own particular patterns and circumstances. But I think What I’m trying to get at in all of this is it isn’t first about the data, it’s first about what about life and what about the things that are important to people, uh, patients, caregivers, and the clinicians that they partner with, and how can AI help them? Steven Labkoff: So you’ve explained to me in the pre-call that you’re doing some of this work, so maybe you can unpack a little bit about what it is you’re actually doing with it and how it’s helping or, in some cases, not helping those efforts. Health Hats: Well, what have I done? I, I’ve done different things. One of the things that, that I’ve done is to try to build my toolkit. You know? So when I say build my toolkit, I’m a, I’m a, a conglomeration of symptoms. I mean, you know, I’m, I’m not MS, I’m not my symptoms, but they’re big and they’re there, and I feel like I’m trying to, I’m trying to figure out for anything that I have to deal with, whether it’s any of the different kinds of pains I have, my, my anxiety, my bladder, you know, my mobility, I have challenges, and I, I need a toolbox. I need a toolbox, and the way I think is I need at least three things that will work so that when they happen, I got something I can go do, and pretty much the most common thing is drink water. Drink water is by far the most successful intervention across all of my symptoms. It’s kind of amazing. It’s so cheap, so easy. It isn’t the drugs. Okay, but so how do I do that? Well, for me, I’ve done that partially just in my head. Partially I’ve done that by keeping lists. Like, I keep track of the steps I take. I keep track of the amount of time I play music. I keep track of my falls. I keep track of my weight. And so I use digital tools to do that when I can. Steven Labkoff: I also record my clinician visits because- When you say record, do you mean like audio record or dig- Health Hats: Yeah. Yeah, audio record, right. And, uh, until recently I used Abridge, which is a company that, um- Steven Labkoff: How did you get to use Abridge? You– I thought Abridge was only selling basically into doctor’s offices, uh, from the clinician side. Do you- Health Hats: So I was before that. Ah. And they started as a patient-facing product, and actually they sponsored my podcast for three years. So I was pre that. So putting all that together, so I play with, you know, trying to put into Claude There’s nothing magic or special. You know, it’s me playing, just trying stuff. You know, some of it, you know, my wife will say, “Hey,” she sees a pattern. My kids will see a pattern, or I’ll- Steven Labkoff: Give, give, give us an example of what, of what this looks like. I mean, you’re saying you’re giving Claude or another LLM- Yeah … a series of symptoms, or you’re giving it a series of, plus your data. Like, unpack it and let us know. Yeah. What have you did- Okay, so what- … with the system, and how is it working for you? Health Hats: I’ve done a couple of different things. One is, you know, I have a spreadsheet, and I just put the spreadsheet in, you know, as a document or whatever you call it when you have a project and, you know, you load. I load my spreadsheet. I keep a annual summary, and I keep the year that I’m working on. And I will have fits of journaling. You know, I, this is not something that I am, like, super consistent on, but I’ll, especially when I’m struggling with something, if I’m struggling with my blood pressure or I’m struggling with my mood. I have a progressive mobility thing going on, and I’ll put that in and I’ll prompt. I’ll say, “Can you– do you see a pattern in this?” You know, and I’ve gotten, you know, that there’s- Steven Labkoff: Has it given you some insights? Is it… Like, give me an example of some of the insights it’s actually given you that you didn’t see yourself. Health Hats: Well, I’ve gotten, like, uh, it’s kind of humorous. But, but I’ve gotten, like, you know, “Have you thought about seeing a physical therapist?” And I, I have. You know, I have a physical therapist, uh, that I don’t go to very often. You know, my relationship with her is I go for a tune-up. But they’ll– I, I want– It’ll show, like, I’ll do my sort of things are clearly, you know, I’m not walking as far, I’ve fell on a few times, you know, and I’ll get this suggestion, you know. I also– What else have I done? Oh, oh, uh, once I had a medication that I was taking for neuropathy, and I was– my mood had, like, changed considerably and, you know, I got a thing on that might be a side effect. You know, “Have you talked to your doctor about this?” Steven Labkoff: And I- And you got that out of the LLM? You fed that to the LLM? Health Hats: I did. Yeah. Steven Labkoff: And it suggested it was a side effect, which you didn’t figure out. Health Hats: I didn’t. A neurologist said that he thought– He said, “It sounds like you have an allergy to it.” And, you know, he wanted it to be listed as an allergy because he thought it was very possible that he’s had people that have had a problem. Steven Labkoff: When you tell me that you’ve loaded your data, you give the LLM your signs, your symptoms, you give it your labs, you give it what’s in, in the system, and it comes up with a recommendation that you hadn’t thought– Now, you’re a clinician. You’re a nurse. Yeah. You’ve been a nurse for many, many decades. Health Hats: 50 years. Steven Labkoff: 50 years. And does it surprise you that it comes up with stuff that you didn’t see? Health Hats: No. Steven Labkoff: Cause I, to be honest with you- I- … if I, if I did what you just said and it came up with something completely radical that I’d never thought of and it was right- I would be scratching my head and thinking, “Okay, that’s in- that’s beyond interesting. I better pay more attention to this, and maybe I wanna use it differently.” Because not, it’s not just yous using it. Like, people around everywhere are starting to use it for the same, in the same sim- in the same exact way. So that’s the simplification of the medical system, right? Health Hats: It does. I mean, like when I tell my neurologist, he laughs, and he’s like a whatever works kinda guy, you know? That he feels like he doesn’t have all the answers, and that he likes- those stories. I feel like I’ve learned, I think you know Amy Price, right? Steven Labkoff: Yeah, very well. Health Hats: Yeah. We’re buddies. And so one of the things that I’ve learned from her is how to query and how to be skeptical and how to ask questions from different angles, from different perspectives so that you– And that’s why I think that’s where the unexpected comes up. Steven Labkoff: Well, you’re describing something that we did at the conference. I don’t know if you were in the room in the working group that we did this on, but you’re describing, and actually we’re submitting a paper on it very shortly, on AI literacy. Yeah. And you, you didn’t label it as such, but you’re describing yourself as being AI literate and understanding how to use the tools, most importantly, how to be skeptical of the answers, how to interpret the information that’s being presented to you. Health Hats: A- and that, those are all components of literacy, of AI literacy specifically. One of the things I’m finding in my world is that painfully few people are indeed AI literate. Even the folks in IT departments in large life science companies or hospitals who even work in the space and think that they’re good at it and are literate sometimes are not. That has other implications, which are if people are taking on these really impressively powerful tools and they don’t quite know how to use them as well as they should, and if they query them incorrectly, to your point earlier about making good queries, the responses that come out may or may not be the point. And if patients use that information inappropriately because they didn’t know how to ask the right questions to start with, that could have deep implications to the healthcare system. You could say that same thing about doctors. Steven Labkoff: I will say it about doctors. I mean, not about AI, about the advice that doctors give. Health Hats: There’s a, a tremendous variation, and it is very different. When I am feeling good enough to be organized and to be directive in the conversation with a clinician, I get a very different output than when I’m not. And I still have to be skeptical of what doctors tell me, and until I build some trust. And, and then I, you know, then there’s just too many decisions to make when you’re a person with chronic illness. It’s like putting in a kitchen. There’s so many decisions to make, and I’m happy for the doctors that I trust to make the decisions for me. But there are certain decisions I don’t want to give to the doctor or to AI, like I don’t wanna mess with my pathological optimism. I wanna progress as slowly as possible, and I wanna keep playing my horn. These are really important things to me, and I don’t give those decisions that affect that, I don’t give up. But all the rest of it I do, and, and I’ve worked really hard to build the team that I have that appreciates me and my strangeness and my assertiveness, and, you know, they’re not threatened by it. Steven Labkoff: Is your team AI literate? Do they also use the, these same tools in your care? Health Hats: Uh, like I don’t know. I mean, AI literate is like, is huge. You know? I mean, that’s just such a big thing. Do they use AI? Yes. Do I know how they use AI? Well, you know, they use what’s attached to Epic. I know that. Uh, I mean, look, my neurologist, who I just love, he thinks like he uses, he uses the portal well because he takes– he just keeps adding things to the end of the, a note. Yeah. And so he feels like… Well, I don’t find his notes at all useful, and I tell him that. I tell him, “What I really wanna know is, how am I doing? Am I getting better? Am I getting worse? Am I stable? What should I be paying attention to in the next six months till I see you again?” And I can’t find that in his note. That’s true. Yeah. Now, on the other hand, I’ve taken his note and asked Claude and say, “Here’s the note. How am I doing? You know, have I progressed? H-how is he measuring it?” Oh, well, then I find he’s using this scale, right? And it’ll come up with looking through this note, which is like 10 years running, and it’ll find, I can’t remember the name of it, but there’s a scale that he uses. And then we go back and I’ll say to him, “Oh, you’re using this scale.” And he goes, “Yeah.” And I say, “Well, why don’t you like put that at the top of your note?” You know, so that I can find it. You know, so we have that kind of conversation- Yeah … that AI has helped. Steven Labkoff: Well, that’s actually an interesting perspective that AI is helping to reorganize things, ’cause one of the use cases that has been discussed at, at length actually, and it was discussed at our conference, is using AI to digest medical records. Health Hats: And when I say digest, it’s not about like ingesting them, which is slightly different, but digesting, which means find all the different pieces, put them together, come up with a narrative that summarizes perhaps 300 pages of information which may be sparse and may be poorly organized, and bring it all together. And that’s actually a task that AI is actually turning out to be pretty darn good at. And that again changes the nature of the healthcare system and the healthcare journey. You know- And it does a fair job. You say it’s really good at it. So- It’s better than I could do. It’s better than I could do. Well, yes. Well, you’re not– First of all, that’s not your training, and you don’t have the time for it. And you still have to review it. Yeah, of course. Because I have never used AI that gave me a, “Oh, this is great.” I mean, the first time I read it pretty much every time I think it’s amazing. And then, you know, my rule is sleep on it and check it again. And then it’s like, oh my God, this, first of all, it either just said nothing very fancy or it got some very basic things wrong. And then I’ll say, “Oh, you know, you missed this and you missed that.” And it’ll go, “Oh, you’re right, I did.” You know? Steven Labkoff: Well, that also speaks to the concept of keeping a human in the loop- Yeah which is something that you espouse and many folks in the healthcare aisle- I do … espouse. Ironically, you know Adam Rodman, I think. He was at our conference, he spoke. Yeah. Uh, he’s done a study which shows actually having a human in the loop in some cases actually makes the conclusions worse, believe it or not. Ah. Which is w- a non-intuitive finding. You would think that the two together would be better than either one alone, but so that’s, that’s now relatively n- well, it’s not even that new anymore. That information came out about a year ago. So I, we gotta start wrapping up in a few minutes here. Yeah. You know, we didn’t cover the concept around outcomes around your three T’s and two C’s. Maybe we can cover that in the last bit here, and then we can get to closing. Health Hats: Okay. So I feel like one of the questions that you’ve asked is how AI helped, right? And so what I need to tell you is the framework that I’ve developed over the years, which I’ve actually shared in my AI Claude project that’s Danny’s Health, what I call the three T’s and the two C’s, and this is like the framework I use to evaluate any digital health technology. And so they are time, trust, talk, control, and connection. What I mean by that is time is, you know, you need time to learn, to plan, to talk, to build trust. So I say the clock isn’t the enemy, it’s the, the wrong things filling the time, so the, the time. The second is trust. You know, trust can take a really long time. It can happen really quickly. Sometimes you never have it, and you know in your gut when you don’t have it. And most digital health tools, AI, have a trust deficit, I think, not because they’re untru- untrustworthy, which maybe they are, but it’s really because the people who use them, use the tools, don’t, don’t trust them, and I think it’s really important. You c- you can’t shortcut trust in the use of any tool. I think talk is really important. It’s woven through all of it, real conversation. There is nothing like actual conversation that is making decisions together, which is a lot of what healthcare is about, is making decisions. AI can help you prepare for it, and it can help process it. And then control. I trust more when I have power in a situation. So if I’m feeling like an ant ready to be crushed, I’m not making good decisions. And finally, I would say connection is, it’s the human lifeline. You know, when somebody greets you when you cross a threshold, that’s a connection. When someone’s been where you’re going and they can say, “Oh, that helped me.” AI can extend that connection. They can help people find communities that are available at 3:00 in the morning, but you can’t manufacture it. I, I think that connection is really important, so that’s where I g- you know, time, talk, trust, control, and connection, and I use that framework when I’m evaluating. Steven Labkoff: And that framework gives you a better, you know, a how do I say this right? It gives you a, like a rubric, if you will, to go- Yes … through, uh, the information that’s coming out of it. Danny- Yeah … we’re gonna have to wrap up here in a second. Sure. Are there any last comments you wanna make that, that will, you know, help other patients in the, in the space in terms of how they might wanna think about adopting- an AI tool in their world? Health Hats: I think that I would say use it, use AI, keep using it, experiment with it. That, that i- i- just like anything else, it takes time to learn. It takes time to be comfortable with it. Use it. I would say advocate for humans in the loop. I don’t care what the study says. It’s about humans. We are human. Keep it humans in the loop. I would say find a buddy, you know. Do this with somebody else. Find a buddy- That’s good advice … and experiment. I would say, yeah, talk to your clinician about it. It’s a good barometer of a physician. If they don’t wanna talk or blow you off, that tells you something. Absolutely right. And I would say if you’re comfortable with it, mentor. You know- That’s a good idea … be the buddy. And for clinicians and for systems and developers, I would say you need to have patients, caregivers, and practicing partner clinicians in the design. They need to be there from the beginning. And, you know, so i- it solves the problems people have, not the problems that the developers think are there or the venture capitalists thinks are gonna make money. You know, y- and if you have an opportunity, join, you know, participate. Steven Labkoff: All good advice. Well, Danny, I wanna thank you very much for your participation in, in today’s discussion. Hopefully that there are other patients out there who listen to the podcast, they’ll take something away. For the clinicians out there who are listening, you know, you’ve heard it straight out from a patient who happens to be a healthcare provider himself, and he’s got very strong perspectives on how this can be used in a positive and productive way, and I think the framework that he’s put together is very useful. Danny, I wanna just say thank you for all the help that you’ve provided helping this podcast get off the ground. That’s been really incredibly generous of you and your friends who have helped us a lot, and a lot of the things that have happened on our podcast, uh, for improvement’s sake, have come directly from those conversations, so thank you for that. I wanna thank you for being a guest and sharing your journey and sharing your experiences here. And for the rest of us, I’m gonna say thank you for joining us, and we will see you again next time on another episode of Practical AI in Healthcare. Thank you for listening. Thank you for joining us this week on Practical AI in Healthcare. If you’re ready to go beyond buzzwords and hype and explore how AI is truly transforming healthcare, stay tuned for more conversations that get us to what works. Until next time, stay practical Reflection When Steve interviewed me, he didn't know that everything I told him is the origin story of TrustMyOwn.Health. The box of paper. The 296 pages that were technically my data and practically useless. Twenty-five years of a pattern that sat in my chart the whole time, that it took a person, my PCP, a year to put together. Could AI have done it in an afternoon?  I got tired of that being the normal experience instead of the exception. [Add: what specifically prompted starting TMOH, and when.] TMOH starts from a premise I didn't have language for until I said it out loud to Steve: trust isn't a feature you bolt onto a health platform after the engineering is done. It's the whole structure, or the whole thing fails. The three T's and two C's I use to size up any digital health tool turn out to be close to a design spec. Time, because a vault of your whole health history takes patience to build, not a single import. Trust, built into governance rather than promised in marketing; TMOH's Data Sovereignty Covenant binds the board and investors to the same terms as everyone else, which is the only version of trust I believe in. Talk, because the point was never to replace the conversation with my clinician, it was to walk in more prepared for it. Control, because I decide what goes in the vault and who sees it, the same way I decide which of my own decisions I hand to a doctor or an AI and which ones I keep for myself. Connection, which no vault can manufacture, but a good one can make room for. I told Steve that AI found a pattern in my chart that twenty-five years of clinicians missed. That's not really a story about AI being smart. It's a story about who owned the data long enough to ask the question. That's the whole bet behind TMOH: put the owner at the center, and let the rest of the ecosystem, the networks, the vendors, the AI, earn its place around that. See you around the block. Practical AI in Healthcare Episodes https://open.spotify.com/episode/4wA4ltjmZfIZ5VpmTeTTOF?si=KbEvc2_ERNWakJ3JeP2Ddg https://open.spotify.com/episode/0LDetUFJJrSV1cy6LtpGFx?si=qAqoqKBBSNm9PiwPjSIXYA https://open.spotify.com/episode/0wXEm1KnnGorOvTt9GTh7o?si=K_DKXzGyThusBPA6KoVkCg https://open.spotify.com/episode/6krV94ob6Lcv7VNo0qahZ5?si=B6lZDkvsQ9y2Z2FhkXzQGQ Referenced in episode Patient data access history: “Introducing Blue Button Plus: The Next Generation in PHRs” — HealthIT.gov (Office of the National Coordinator for Health IT) — https://www.healthit.gov/blog/consumer/introducing-blue-button/ The “Gimme My Damn Data” campaign Danny references: “Gimme My Damn Data (and Let Patients Help!): The #GimmeMyDamnData Manifesto” — Dave deBronkart, Journal of Medical Internet Research — https://www.jmir.org/2019/11/e17045/ Amy Price, mentioned as a mentor in questioning and skepticism: “Welcoming Dr. Amy Price as Editor-in-Chief” — Society for Participatory Medicine — https://participatorymedicine.org/2024/welcoming-dr-amy-price-dphil-as-the-editor-in-chief-for-the-journal-of-participatory-medicine/ AI literacy for patients, the concept Steve names in the episode: “Critical AI Health Literacy as Liberation Technology: A New Skill for Patient Empowerment” — National Academy of Medicine — https://nam.edu/perspectives/critical-ai-health-literacy-as-liberation-technology-a-new-skill-for-patient-empowerment/ Human-in-the-loop research Danny and Steve discuss (Adam Rodman): “AI and the Evolution of Medical Thought with Dr. Adam Rodman” — NEJM AI Grand Rounds (podcast) — https://ai-podcast.nejm.org/e/ai-and-the-evolution-of-medical-thought-with-dr-adam-rodman/ Abridge, the ambient AI scribe tool Danny mentions using: “Pioneers in Generative AI for Healthcare” — Abridge — https://www.abridge.com/about The DCI Network conference where Danny met the hosts: “About DCI Network” — DCI Network, Beth Israel Deaconess Medical Center — https://www.dcinetwork.org/about-us Please comment and ask questions: at the comment section at the bottom of the show notes on LinkedIn  via email YouTube channel  DM on Instagram, TikTok to @healthhats Substack Patreon Production Team Kayla Nelson: Web and Social Media Coach, Dissemination, Help Desk  Leon van Leeuwen: editing and site management Oscar van Leeuwen: video editing Julia Higgins: Digital marketing therapy Steve Heatherington: Help Desk and podcast production counseling Joey van Leeuwen, Drummer, Composer, and Arranger, provided the music for the intro, outro, proem, and reflection Claude, Perplexity, Auphonic, Descript, Grammarly, DaVinci Resolve, DaVinci AI Art Generator, OpenArt AI Creator Studio Inspired by and Grateful to: Steve Labkoff, Leon Rosenbilt, Amy Price, Leon and Oscar van Leeuwen, Laura Marcial Artificial Intelligence in Podcast Production Health Hats, the Podcast, utilizes AI tools for production tasks such as editing, transcription, and content suggestions. While AI assists with various aspects, including image creation, most AI suggestions are modified. All creative decisions remain my own, with AI sources referenced as usual. Questions are welcome. Creative Commons Licensing CC BY-NC-SA This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modified material under identical terms. CC BY-NC-SA includes the following elements:    BY: credit must be given to the creator.   NC: Only noncommercial uses of the work are permitted.    SA: Adaptations must be shared under the same terms. Please let me know. dannyhealthhats@gmail.com  Material on this site created by others is theirs, and use follows their guidelines. Disclaimer The views and opinions presented in this podcast and publication are solely my responsibility and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute®  (PCORI®), its Board of Governors, or Methodology Committee. Danny van Leeuwen (Health Hats)

Podcasting 2.0 July 17th 2026 Episode 265 - "Jihobbyist" Slop or Not! Lightning or Frightening! Adam and Dave go deep with the Boardroom after a 2 week break ShowNotes ------------------------------------------------------------------------------------------------------------------------------------- 00 - PODPING GOSSIP-WRITER → PRODUCTION + INDEX PLUMBING ------------------------------------------------------------------------------------------------------------------------------------- 01 - THE OPEN INDEX TURNS UP INSIDE AN AI SCRAPER (SUNO) @js flagged it: a hack at Suno reveals the AI music generator used PodcastIndex to do its targeting — "with the help of an online tool called PodcastIndex, Suno identified 420,000 different podcasts that had at least five 30-minute episodes and sought to download roughly 1 million hours of podcasts." Board question: the Index exists to be "free, for any use" — and here "any use" is an AI company bulk-harvesting a million hours to train on. Is that the deal working as designed, or does anything change? A live test of the open-index ethos. Ties straight to the on-device/namespace fight below and to the spam/AI-slop lane — the same extraction pressure from three directions. Hack reveals Suno scraped via PodcastIndex (404 Media) ------------------------------------------------------------------------------------------------------------------------------------- 02 - ON-DEVICE AI vs NAMESPACE TAGS — "DIDN'T YOU INVENT THE NAMESPACE?" Your own post set it off: Adam — Apple in talks to run a startup's compressed AI models on-device (PrisMML) — "More fodder for on-device features vs new tags." The core board fight of the week.

Podcasting 2.0 July 17th 2026 Episode 265 - "Jihobbyist" Slop or Not! Lightning or Frightening! Adam and Dave go deep with the Boardroom after a 2 week break ShowNotes ------------------------------------------------------------------------------------------------------------------------------------- 00 - PODPING GOSSIP-WRITER → PRODUCTION + INDEX PLUMBING ------------------------------------------------------------------------------------------------------------------------------------- 01 - THE OPEN INDEX TURNS UP INSIDE AN AI SCRAPER (SUNO) @js flagged it: a hack at Suno reveals the AI music generator used PodcastIndex to do its targeting — "with the help of an online tool called PodcastIndex, Suno identified 420,000 different podcasts that had at least five 30-minute episodes and sought to download roughly 1 million hours of podcasts." Board question: the Index exists to be "free, for any use" — and here "any use" is an AI company bulk-harvesting a million hours to train on. Is that the deal working as designed, or does anything change? A live test of the open-index ethos. Ties straight to the on-device/namespace fight below and to the spam/AI-slop lane — the same extraction pressure from three directions. Hack reveals Suno scraped via PodcastIndex (404 Media) ------------------------------------------------------------------------------------------------------------------------------------- 02 - ON-DEVICE AI vs NAMESPACE TAGS — "DIDN'T YOU INVENT THE NAMESPACE?" Your own post set it off: Adam — Apple in talks to run a startup's compressed AI models on-device (PrisMML) — "More fodder for on-device features vs new tags." The core board fight of the week.

The AI boom is still growing like crazy. Many organizations are trying to learn how they can use AI to improve operations and become more efficient, at a reasonable cost. Plenty of companies are spending crazy amounts of AI tokens, sometimes blowing their yearly budgets in months and not necessarily receiving substantial value back. Some companies are trying to train AIs to understand their operations and perhaps reduce their other costs, primarily labor. Still others are tip-toeing in the waters of AI LLM use and conducting smaller experiments, with limited access to AI technology. Meta has been a company on the forefront of trying to train AI based on the work employees already perform. There has been plenty of concern that their efforts are designed to lower headcount and replace humans with AI agents. That might or might not work, though I don't expect a lot of organizations to do this. It's likely harder than any of the hype suggests, and most organizations have much more complex types of operations than Meta. Read the rest of Security and AI Fail

È finita l’era dell’elettronica di consumo con prezzi in discesa e migliori prestazioni? La scelta di Apple di aumentare fino al 25% i prezzi dei suoi laptop potrebbe essere l’inizio di un trend generalizzato e diffuso, che potrebbe condizionare le prestazioni dei prodotti e interessare tutto il settore per almeno uno o due anni, spiega Gianfranco Giardina, direttore del magazine digitale Dday,it.I sistemi di AI come i chatbot hanno bisogno delle informazioni presenti sul web per rispondere agli utenti ed è quindi necessario creare motori di ricerca progettati per i modelli linguistici di grandi dimensioni (LLM) e gli agenti autonomi di intelligenza artificiale. Gli strumenti creati per gli esseri umani sono infatti lenti e poco efficienti spiega Antonio Mallia, Ceo di Seltz, startup che ha recentemente raccolto finanziamenti per un valore di 12,5 milioni di dollari.La Commissione Europea ha assegnato ad un consorzio guidato da Domyn una gara per la costruzione di un modello di intelligenza artificiale di frontiera “aperto” basato su oltre 400 miliardi di parametri. Ne parliamo con Luca Antiga, Chief Technology Officer di Domyn, azienda italiana specializzata in intelligenza artificiale.E come sempre in Digital News le notizie di innovazione e tecnologia più importanti della settimana.

For a while, I kept seeing that the cost of writing code was approaching zero. So many people felt that with an AI LLM, the costs would go way down to produce software. I'm not sure that's true. In fact, some companies are finding they spend more on AI tokens than salaries. However, the ability to produce more code, experiment with ideas, or generate proof of concepts has gone up. Whether it's worth the cost or not depends on the engineer, but some organizations are finding that they can try more things than they would ever had time to try in the past. The time of engineers was the constraint, and if you can afford the cost, AI LLMs can relieve that time pressure. Read the rest of Follow Your Hunch

Gareth McGlynn sits down with Luigi La Corte, Co-Founder and CEO of Provision, recorded live at Advancing Preconstruction 2026 in Phoenix. Provision is an AI platform built to solve scope gaps in preconstruction, a problem La Corte describes as costing GCs an estimated 0.5–2% of total project cost.Key Topics Covered:Career Path to Provision: From civil engineering at Arup, to infrastructure finance at Plenary, to founding Provision after observing scope failures at the largest GCs in North America.Provision's Pivot: From contract review to Scope Agent, targeting scope gaps after general AI models made document review defensible.Why Scopes Are Hard for AI: LLM limitations with image interpretation, thousands of edge cases around drawing legends and plan references, requiring purpose-built tooling.$1M Dataset Investment: Hundreds of thousands of estimator-verified line items across real projects, built to substantiate accuracy claims.Real-World Results: One customer from three weeks to four days on scope prep. Addenda changes caught before subcontractor distribution, preventing a six-figure issue.AI and the Estimator: Automating rote workflows (spec review, RFI conflicts, scope extraction) without replacing the estimator.You can connect with Luigi via his LinkedIn: https://www.linkedin.com/in/luigi-r-la-corte/

BACKROOMS is fascinating Dear Listener. The film's nostalgia for the analog seems to be a Trojan Horse that explicates that sinking feeling you feel about our culture when you engage with AI/LLM content. Recommended, with caveats. Subscribe on Patreon Apple - The Film Talk Spotify - The Film Talk Facebook.com/TheFilmTalk  

Hur automatiserar man marknadsfunktionen med AI? AI håller på att förändra marknadsavdelningen i grunden. Men de flesta bolag börjar i fel ände. I det här avsnittet av Sälj- och Marknadspodden samtalar Anders Hermansson med Hanna Musie, Marketing Lead på Women in AI och grundare av Seldi, som hjälper marknadsorganisationer att gå från ad hoc-användning av AI till att bygga system som faktiskt driver tillväxt. De går igenom tre konkreta områden som VD:ar och marknadsledare behöver ta på allvar: Kontroll kontra automatisering. Det farligaste med AI är inte att den tar över jobbet, utan att du slutar förstå varför det fungerar. Strategin, positioneringen och det som gör dig unik, det ska förbli mänskligt. Exekveringen kan du automatisera. Diagnostisera innan du automatiserar. Innan du köper fler verktyg eller bygger flöden, gå igenom en vanlig arbetsvecka och räkna ut hur många timmar som läggs på repetitiva uppgifter som inte kräver mänskligt omdöme. Där hittar du din första AI-potential. Framtidens marknadsorganisation. En AI-native marknadsavdelning på ett medelstort B2B-företag kommer inte bestå av tio specialister, utan av tre personer som dirigerar sina egna team av AI-agenter. Frågan är vad det kräver av de människor du redan har, och de du ska rekrytera. Avsnittet innehåller också praktiska tips om hur man väljer vad som ska automatiseras, vilka verktyg som är relevanta och hur du som VD coachar ditt team in i en ny verklighet. Hanna Musie är engagerad i Women in AI, Sveriges största nätverk för kvinnor inom AI med cirka 10 000 medlemmar i Sverige och närvaro i 200 länder. Läs transkribering Anders Hermansson (00:03) Hej och hjärtligt välkomna till Sälj marknadspodden från Business Reflex. Det här är ju podcaster för dig som vill kunskap och inspiration kring hur man säljer marknadsför till den digitala business och bisnisköparen. Jag heter Anders Harmansson. Idag ska vi prata om ett otroligt aktuellt ämne. Övergripande rubriken är… hur man automatiserar marknadsavdelningen med AI. Det kommer jag att prata med en otroligt härlig kvinna som heter Hanna Mose. Hon är jätteduktig på att jobbat med AI länge och vi kommer att diskutera vad man behöver tänka på för att inte gå fel i den här automatiseringen. Vi tar upp tre viktiga områden som jag tycker du ska lyssna absolut till slutet för då kommer konkreta tips om hur du som vd ledar för ett bolag som verkligen behöver tänka till kring AI och marknadsföringen hur du ska göra för att det inte går fel i den här djungeln. Så häng med på intervjun! Anders Hermansson (01:01) Hanna Muse, hjärtligt välkommen till Säljmarknadsbådden! Hanna Musie (01:05) Tack så mycket, väldigt kul att här! Anders Hermansson (01:07) Ja, vad roligt. Vi har haft lite försnack innan om det här med AI och jag är AI-entusiast, du. Så ska bli jättekul att prata med dig idag. Och det vi ska prata om, ämnet som vi har försökt mejsla ut här, det så hur automatiserar man marknadsavdelningen med hjälp av AI? Det är liksom det övergripande temat här. Det är ju superspännande verkligen. Som jag berättade för dig när jag satt uppe till två i natt och… Anders Hermansson (01:32) utvecklade med hjälp av klåden MCP-server som då är en koppling kan man säga mellan ett system och AIN så att den kan babbla. Så jag är lite trött idag, men jag var pigg och glad när jag såg dig. Så härligt! Hanna Musie (01:45) Det är härligt att bidra med energi. Anders Hermansson (01:47) Ja, eller hur? Men du Hanna innan vi drar igång kan inte du berätta lite grann om dig själv och hur din koppling och hur har landat i det här med AI och så. Hanna Musie (01:56) Jo absolut. Jag är ju marketing lead på Women in AI som är Sveriges största nätverk för kvinnor inom AI. Och sen så via mitt bolag Seldi så hjälper jag marknadsorganisationer att gå från att jobba väldigt ad hoc med AI till att faktiskt bygga AI-system som driver tillväxt. Och så föreläser jag på Bergs och har via Seldi också en slutgrupp för marknadsledare där de kan liksom dela konkreta road maps, sina utmaningar och faktiska beslut de tagit. Så bjuder vi in lite AI-experter, AI-entreprenörer och så för att säkerställa att de är i framkant. Anders Hermansson (02:37) Ja, spännande. Och det här med Women in AI, vad är det för någonting? Hanna Musie (02:42) Jo, med Women in AI, där jobbar vi mycket för att säkerställa att fler kvinnor blir engagerade och utbildade inom AI. Så att vi har mentorskapsprogram, vi kurser, har träffar och så. Så att det är väldigt uppskattat och våra event brukar vara uppåkade på 24 timmar. Så det är jättekul. Anders Hermansson (03:01) Snyggt. Och bara så man ska förstå ungefär hur stor rörelse det här. Hanna Musie (03:06) Nej men vi finns i 200 länder och i Sverige då så är vi en ledningsgrupp och sen så är det cirka 10 000 personer med i vår slackgrupp. Anders Hermansson (03:19) Fantastiskt, vad roligt! Och varför har inte jag hittat någon grupp för men in AI kan man fråga sig? Hanna Musie (03:25) Men det det här jag menar. Men vi går ju mer och mer mot att ha communities för man märker att folk vill ju bolla och prata med andra, liksom utbyta erfarenheter. Anders Hermansson (03:32) Ja, exakt. Lite av Dark Souls-aktigt. Men lite bakgrund då, hur landar du det här? Hanna Musie (03:43) Men jag har varit engagerad inom AI även när det bara var teoretiskt. Och sen har jag ju jobbat med marknadsföring i cirka tio år nu. Och läst på om AI och när det väl kom så blev jag ju så, herregud, det inte bara snack utan nu finns det att faktiskt använda publikt. Så att jag har ju följt utvecklingen från start och sen… Anders Hermansson (04:03) Mm-hmm. Hanna Musie (04:12) Gick jag med i Women in AI så fort jag flyttade upp till Stockholm egentligen? Anders Hermansson (04:18) Coolers, du vad heter det? Det kanske är en konstig fråga men varför ska vi prata om det här nu? Varför tycker du att det är relevant? Just nu går vi att prata om det här. Hanna Musie (04:27) Det är väldigt relevant för att marknadsföring och marknadsavdelningar är oftast i skottlinje när det kommer en ny teknik. Det ser man även nu med AI. Den traditionella marknadsavdelningen, både när det kommer internt till setupen, vilka roller som ingår och så där, men också när man konkurrerar mot andra bolag, har ju ändrats helt och hållet. För det behöver ju inte vara människor på ett bolag. Anders Hermansson (04:53) Mm. Hanna Musie (04:56) och vad man konkurrerar mot, utan det kan ju vara deras AI-agenter. Anders Hermansson (05:01) Det är väl om man tittar på olika listor över vilka yrken som påverkas mycket av AI så är marknadsidan de som ständigt ligger högt upp i alla fall. Det betyder väl att AI kan göra mycket nytta genom det området då. Hanna Musie (05:11) Mm, ja. Och det har man ju redan. Jättemycket nytta. Och det är just därför det är så viktigt att prata om för att jag som är i kontakt med mycket CMO, RCI och OER och C-suite, marknadsnära roller, man ser ju att många ändå känner sig fort ganska ensamma i ansvaret för slutresultatet av AI ändå. Anders Hermansson (05:26) Mm. Mm. Mm. Ja, stä. Hanna Musie (05:39) Och att man kanske är lite vilsen fortfarande i hur man faktiskt ska implementera det för att få resultat. Och sen kanske man inte har tid att gå en kurs eller så. Och då går man ju tillbaka till det här med nätverk att hitta forum där man faktiskt kan liksom lära av varandra så att man inte gör de dyra misstagen själv. Så det är… Eller skjut upp det till Imonja. Så att för… Anders Hermansson (05:46) Mm. Just det, eller skjuta upp det till imorgon för att man har så mycket att göra nu. Hanna Musie (06:09) Det kommer ju ändras framtidens marknadsorganisation som vi känner till den idag i alla fall. Så det är ju egentligen att se till att inte stoppa huvudet i sanden och hänga med i att troligtvis så kommer marknadsavdelningen som vi känner till den idag i alla fall bestå mer av AI-agenter än människor. Anders Hermansson (06:12) Mm. Mm, mm. Just det. Det kan vara lite deprimerande som marknadsföraren men jag hoppas vi kan få en positiv spinn på det här. Vi försöker i Sälj marknadspodden ta lite VDs perspektiv på det här så att man tittar på det uppifrån och ser hur man ska organisera sig kring det här. Så jag hoppas vi kan komma in lite grann på det. Men om vi kommer tillbaka till dagens ämne då med hur man automatiserar marknadsavdelning med AI. Och vad skulle du säga är de tre viktigaste sakerna man ska tänka på övergripande? Hanna Musie (06:46) Mm. Mm. Men övergripande så skulle jag säga att för att gå tillbaks i den här positiva spinnen då, att du är den som kontrollerar AI och att du inte ska låta AI att kontrollera dig. Och sen också då att du börjar med att diagnostisera innan du faktiskt automatiserar så att du vet att du gör rätt saker. Anders Hermansson (07:05) Ja. Jesta. Hanna Musie (07:22) och lite hur kommer marknadsorganisationen faktiskt att vara uppbyggd 2026 och framåt för att få tillväxt. Anders Hermansson (07:29) Hej då! Just det, och där bör man tänka på, jag antar, kompetensmix och så där. Vad är inställning man ska ha? Om man ska rekrytera in folk eller kompetensutveckla folk som man redan har så måste man förstå liksom vad ska de passa in i för någonting, tänker jag. Ska Hanna Musie (07:42) Hej! Prösters! Anders Hermansson (07:50) det här första punkten handlar om att du ska kontrollera AI istället för att AI ska kontrollera dig. Vad får du berätta? Vad menar du det? Hanna Musie (07:58) Ja, vad menar jag med det? Men det farliga med AI är ju inte att det gör jobbet åt dig. Det om du liksom slutar förstå varför det funkar. Om jag tar ett exempel, många jobbar med metaannonser eller andra typer av annonser. Förut bestämde du själv vilken målgrupp, vilket budskap, vilket format och så där. Nu bestämmer algoritmerna det åt dig, vilket är jättebra för att det optimeras och så vidare. Men det blir ändå att du tror att du är marknadsförd, men det är egentligen AI som är marknadsförd och du som godkänner. Anders Hermansson (08:34) Ja. Hanna Musie (08:35) Och problemet där blir ju att när det slutar funka och du inte vet varför, då har du ju låtit AI kontrollera dig och inte tvärtom. Anders Hermansson (08:45) Just det. Ja, men då tror jag att jag förstår. Hanna Musie (08:47) Ja, så det är jätteviktigt att separera det här strategiska tänkandet mot eller från exekveringen. Så att det strategiska liksom vem vi pratar med, vilket problem vi löser, varför vi finns, det är ju väldigt mänskligt och det ska behållas mänskligt. Medan exekveringen, så när skickar vi, vad vi testar, hur vi optimerar, det kan vi outsourca till AI. Men… Anders Hermansson (08:56) Ja. Jag försöker förstå skillnadssättet. det här är en grej. Jag har ju hållit på med AI sen, inte lika länge som dig, men sen dagen efter ChatGPT lanserades så var det bara okej, det här är grejen som man måste lära sig. Och jag har hela tiden backat i ett steg. Så jag har hela tiden backat mer. Men vad skulle du liksom säga är, var ska man dra linjen för vad man då… Hanna Musie (09:26) Mm. Ja. Anders Hermansson (09:44) inte ska låta AI bestämma och kontrollera vad man ska göra själv. För jag har liksom själv inte stått på samma plats hela tiden, utan jag har såhär, jaha, men jag har en strategi här, vänta nu varför ska jag göra strategi? Det berättar att den gör strategin. Och så backar jag. Hanna Musie (09:54) Nej. Ja, och det är skillnad på vad den kan göra och vad den bör göra för att självklart kan AI göra strategin. Men det man ser statistiskt sett är att i slutändan så ger JPP och många andra LLM-modeller liknande strategier och tips till alla användare. Anders Hermansson (10:21) ⁓ så klart. Hanna Musie (10:22) Så när det kommer till marknadsföring och även bolagstrategi overall så vill man ju säkerställa att man faktiskt sticker ut. Anders Hermansson (10:31) Mm. Hanna Musie (10:31) Det enda man egentligen kan vara bäst på är ju den kunskapen som du själv besitter som kan göra dig unik, kan göra så att ni har ett specifikt perspektiv. Så det är viktigt att inte bli en slav för AI, utan säkerställa att man sticker ut på något sätt och det är egentligen den största vallgraven som man har när det går att bygga vilket bolag som helst, vilken produkt som helst, väldigt snabbt. Varför välja dig? Anders Hermansson (10:59) Just det. Jag tror att jag förstår lite mer. Det här behöver man ju sätta in själv i sin kontext och försöka förstå vad är skillnaden som är skillnaden med det här bolaget som jag jobbar på nu. Det är liksom någonting som vi måste verka fram själva. att det inte bara blir en template från Chatt-QFT. Hej, får jag en marknadsstrategi och så får jag samma som alla andra. Och så blir det jättedåligt. Jag fattar. Men grymt. Vad heter det… Hanna Musie (11:21) Mm. Anders Hermansson (11:27) Finns det mer att kring det där med att kontrollera? Om man tänker att man automatiserar hela processer och sådär. Är det farligt eller är bra? Hanna Musie (11:37) Mm. Det är ju jättebra. Det har jag tänkt komma in på, men… Anders Hermansson (11:42) Ja. Mm. Hanna Musie (11:49) Absolut måste man bygga system. För det som många gör idag är att de jobbar väldigt ad hoc med AI. Att det är en del av en manuell process. Så att man kanske har en gemme-like gem eller någon typ av custom gem. Som hjälper den att skriva text eller skapa bild eller vad det nu kan vara. Men sen så är det fortfarande manuella steg till att lägga in det i hapsbåtor. Anders Hermansson (11:52) Mm. Mm. Hanna Musie (12:19) Det är jätteviktigt att bygga upp ett flöde, ett system för det så det kan arbeta. Anders Hermansson (12:20) Jöster. Så det är snarare positivt. Det ska man inte säga att då tappar vi kontrollen. Det är bra på något sätt. Hanna Musie (12:36) Exakt, det du inte vill tappa kontrollen är din kreativitet. Du vill hitta din position. liksom… Det som gör dig unikt ska du inte få hjälp med AI för att ta fram. Anders Hermansson (12:47) Just det. Jag såg en så intressant bild med tanke på att tappa kontrollen. Det är ju mycket prat, kanske mindre nu, ganska mycket prat om det här med att AI tar över världen. Då var det en bild på en… Det var fotot, eller teckningen var på en människa som satt i naturen med armen runt en hund. Hanna Musie (13:01) Mm. Ja. Anders Hermansson (13:15) Där… där… vad heter det… hunden då har varit en varg. Väldigt självständigt djur. Men sen har vi successivt domesticerat den här vargen till att den blir liksom en pickenes som vi går omkring med i en väska. Det var liksom det här med… med tanke på att tappa kontrollen. Det var ett scenario som AI, när man pratar med AI om det här, säger ja, men jag kommer att vänja dig vid att du slutar tänka, för det här är mycket mer bekvämt. Hanna Musie (13:22) Ja. Ej då! Anders Hermansson (13:43) Och till slut sitter vi där som en liten hund vid A-in Hanna Musie (13:45) Ja. Anders Hermansson (13:46) där den bara jajaja. Hanna Musie (13:49) Ja, men det ju så. Och jag ratar ju just nu ur ett bolagsmarknadsföringsperspektiv när jag säger att behåll din kreativitet. Men självklart finns det ju många fall där AI blir chefen. Alltså till exempel som jag vet inte om du har sett att det är ett café som har öppnat i Stockholm. Anders Hermansson (13:57) Ja. Jo just det exakt. Hanna Musie (14:06) Ja, som bara är AI-drivet. Där är en AI-agent, Mona, som har rekryterat och satt upp och leder det här kafet. självklart finns det ju fall där man kan släppa kontrollen men inte ur ett bolag som marknadsföringsperspektiv. Anders Hermansson (14:17) Ja. Nej. Sen var det en jäkla bra spinn för dem då att de marknadsför det faktumet och så får de värsta publiciteten för sitt café. Det hade de tänkt till i månaden tror jag. Ja men grymt, vad härligt. Då har vi fått lite koll på det här med kontrollen så att man ska tänka på det. Det finns liksom en linje där du måste tillföra egen kreativitet. Du kan inte ut i strunt i det antar jag men då blir det liksom vanilj och alltihop och du kommer att vara en i en massa men så du måste ha en edge som du själv måste komma på för att det här ska bli unikt då. Hanna Musie (14:37) Ja. Mm. Anders Hermansson (14:56) Ja, men grymt. Och det här andra grejen som vi pratade lite igenom. Det här med att diagnostisera innan man automatiserar arbetet. Hanna Musie (15:04) Jo, absolut. Det jag ser är att många börjar i fel ände så att de ser ett nytt verktyg och hoppar på det direkt för att det kommer nya lanseringar av klod, kommer nya AI-verktyg som poppar upp till höger och vänster som lovar guld och gröna skogar. Och det är lätt att bli inspirerad av vad AI kan göra istället för att fokusera på vilket problem kan det lösa specifikt för mig. Så det är viktigt att först och främst Anders Hermansson (15:23) Mm. Mm. Hanna Musie (15:35) analysera vart du kunde resa ny faktiskt läcker, vad som tar mest tid och är repetativt för er och vad som inte då kräver mänskligt omdöme om man ska koppla det till förra punkten. Och det tar liksom en vecka att göra en audit, men det tar ett år att städa upp efter felaktiga system som inte kan prata med varandra. Anders Hermansson (15:49) Mm. Mm. Hanna Musie (16:00) Ett tips för att förklara lite mer är att tajma och räkna ut hur många timmar marknadsföringsavdelningen eller andra avdelningar lägger på saker som inte kräver mänskligt omdöme. Och att det är där man hittar den första AI-potentialen. Anders Hermansson (16:17) Jag fattar. Jag ser en utmaning i att det finns fortfarande en ovana i att tänka på vad man kan använda datorer till. Eftersom vi har hållit på med datorer i så många år så vet vi att det är en jättebra räknemaskin. om jag ska lägga ihop två tal eller räkna ut ett medelvärde så öppnar jag Excel och så låter jag den räkna och så står det 4,3. Då slapper göra det själv. Gud vad bra! Hanna Musie (16:32) Mm. Mm. Anders Hermansson (16:47) Men det här är ju helt nya arbetsuppgifter ur det perspektivet som man kan använda sin dator till. Och jag tänker bara med diagnostiseringen. är ju klurigt att tänka på vad man faktiskt gör på dagarna. Har du något tips kring hur man diagnostiserar och upptäcker vilka produktivitetsvinster man skulle kunna göra med AI? För att jag säger inte att det är liksom svårt att tänka på det sättet. Hanna Musie (16:53) Mm. Ja. Ja. Tipset är att ta en vanlig… Om du följer dig själv i en vecka- och avsätter tid att för varje uppgift du gör, tajma dig själv. Se hur lång tid lägger på det här- och hur många steg du har gjort för att slutföra den uppgiften. När du har gjort det en vecka får du fundera på hur ofta du de här uppgifterna. Anders Hermansson (17:22) Mm. Mm. Mm. Hanna Musie (17:44) Och de delar då som du gör ofta, som är tidskrävande och som du har väldigt tydliga steg för hur du gör, det är de du kan automatisera. Anders Hermansson (17:55) Mm. Just det. Hanna Musie (17:58) Så att vi vill inte automatisera någonting som inte har en tydlig liksom steg för steg kedja av actions. att där är det… Jag brukar till och med tipsa om att liksom skriva ner det för hand typ. Vilka stegen faktiskt är. För då blir det väldigt tydligt hur du ska automatisera. Anders Hermansson (18:05) Ja. Hanna Musie (18:22) För annars så hamnar man där i att man försöker automatisera samtidigt som man inser att den här processen funkar ju inte ens manuellt. Anders Hermansson (18:33) Nej just det exakt, det är krångel när jag sitter själv och gör olika varje gång och så vidare. Så det finns två nyttor med det här, dels att mål för ordning på hur man gör någonting. Men sen kan man liksom turbo boosta det då med att man lägger AI på det dessutom. Hanna Musie (18:42) Mm. Precis. Och det där man bygger de här systemen som du var inne på då. För att när man har den här tydliga kedjan, jo men då kan man gå in med verktygen för att faktiskt sätta upp automatiska flöden som jobbar när du inte är vid datorn. Anders Hermansson (18:50) Ja. Mm, just det. Ja, jag fattar. Det som jag, om jag ska dela med mig lite mer då av mina erfarenheter av det här, är ju just att det är… Om man ritar ett flödeschema brukar jag säga så här, här är fem saker jag gör i rad, här är min process. Då har jag märkt att det är på pilen emellan två boxar Hanna Musie (19:19) Mm. Anders Hermansson (19:31) som du faktiskt gör någonting som du har glömt. Och det är det som AI kan hjälpa till med. Det är så här, ja men vänta, från steg ett till steg två, ja men jag kan ju med sjutton på att du gör någonting på pilen där, du tänker efter på något sätt eller analyserar någonting och förbereder dig för att du ska kunna det som är i steg två där. Där har du tidskiven liksom. Hanna Musie (19:47) Tack Mm. Ja men dels där, men det är därför precis som du säger att det är viktigt att logga varje steg man faktiskt gör. För att det finns ju massa tidskubbar däremellan. Anders Hermansson (20:04) Just det. Hanna Musie (20:09) Sen får man sätta upp många verktyg för att flytta från plats A till plats B. Till exempel Safe om man är nybörjare eller en EITN om man är lite mer tekniskt kunnig för att liksom flytta de här aktiviteterna från den här plattformen till den andra. Anders Hermansson (20:30) Du, det här var intressant. Vi pratar om automatisering. Vi sa ju först själva metoden att tänk nu för 17 efter vad det är ska automatisera så att du inte bara gör mer kaos av saker och ting eller egentligen inte får de vinst du hade tänkt dig tidsmässigt. Nu nämnde du några verktyg här. Hur skulle du säga att man… Vad finns det för någon sorts mognadstrappa eller sådär när man ska liksom olika grader av automatisering och vad är det för… ja, kan man säga… verktyg som gäller nu, kanske inte imorgon då men… vad är din erfarenhet av vilka verktyg som är bra att använda för olika ändamål? Hanna Musie (21:07) Ja, alltså, om man ska tänka ur ett flödesperspektiv så är det ju först och främst viktigt att man förstår grunden i det. Vilket är liksom trigger brain action. Om man ska vara väldigt lätt nu på grundläggande nivå. Och en trigger är ju någonting som kickar igång själva flödet. Och det kan ju vara om man ska ta liksom… Anders Hermansson (21:11) Hm? Mm. Hanna Musie (21:34) Generellt sett är det lättast att automatisera något typ av content. Så det brukar vara där många börjar. Så om vi säger att en trigger är att man laddar upp ett dokument på Google Drive, då börjar flödet. Då flyttar man… med hjälp av N8N eller Sapier över från Google Drive till hjärnan. Då kanske man har byggt upp en Gemini Gem byggt upp i klåd vad det nu är vill göra. Där har man byggt upp vad är vår tone of voice vilken är vår målgrupp hur ska det här case studyn vara strukturerad om det nu är en text då Om det är en bild så kanske man har använt Nanobanana eller Aima. Och sen så flyttar man över med en liten till Action som är själva utförandet. Och där kan det ju vara att lägg in den här texten i den här templeten i Hubspot till exempel. Anders Hermansson (22:35) Mm-hmm. Jätte. Hanna Musie (22:47) Och sen då, oftast så brukar man ha en human in the loop också så att man får någon ping till Slack så att man förstår att såhär, okej, nu behöver jag gå in och läsa för att se så att allting känns korrekt eller så godkänner man bara direkt Slack. Och så skickas det ut liksom. Anders Hermansson (23:07) Gästa. Hanna Musie (23:07) Så att trigger brain action är väldigt bra att ha i åtanke. Och sen så är SABRE eller NHDN det som faktiskt flyttar mellan trigger brain och action. Anders Hermansson (23:21) Ja just det. det den som sköter själva logistiken om man säger så. Jag fattar. Vi har själva byggt ett ramverk kring det här med hur man ska bedriva marknadsföring som då är superkopplat till AI-möjligheten. Så där finns det fem lager. Så det första lager är lager 0. Det handlar om företagets affärsidivision, mission och Hanna Musie (23:25) Precis. Anders Hermansson (23:48) De ekonomiska målen och eventuella budgetramar och vilka människor som är på bolaget. Allt det dokumenterat är ägarviljan. Är exit om tre år eller det här ett lifestyle brand som ska fortsätta längsomhelst. Det är det första. Lager 1 handlar lite mer om marknadsföringsgrejer. En väldigt definierad ICP och en person där AI vet allt om drivkrafter och rädslor och sånt där saker om den här personen som man vill påverka. Kopplat till företagets erbjudande, deras unika mekanismer eller nisch och så där. Och sen så finns det ett datalager där man helt enkelt samlar på sig information om vad det där man gör har gett för resultat. Och så finns det ett beslutslager där man har en beslutslogik för hur man ska utvärdera datat. Och sen finns det ett exekveringslager som du pratade om med skapa bloggpås, skapa whitepaper, gör manus till webinar eller allt det här. Gör ett outbound email och sådana saker. Men allt det bygger då på den här underliggande datastrukturen. Och anledningen till jag har rantat om det här det är ju så att… Vi har inte pratat om det nu men just det, ju mer kontext man ger de här AI-verktygen… Hur ska man tänka kring det? Ibland tänker man att AI vet ju allting, men vad vet AI och vad vet AI inte? Hanna Musie (25:14) Mm. Det beror på om du har på minnet eller inte. Nej, självklart är det viktigt att ge så mycket kontext som möjligt för att har den inte kontexten så är det här som man har pratat om mycket att input, ju bättre input man har desto bättre output får man. Så det är jätteviktigt att dela vad har AEN för roll, vad är det egentligen den ska utföra, vad har den för restriktioner och sedan dela så mycket. Anders Hermansson (25:45) Mm. Hanna Musie (25:59) PDF-er eller underlag som man har. Har ni brandguidelines eller har ni ett ramverk för hur ni vill att nånting ska vara uppbyggt? Har ni en lista på konkurrenter och vad som gör er bättre än dem? Ja men ladda upp det då. Men däremot är det viktigt att säkerställa att man har en AI-LLM som är enterprise-nivå eller som inte använder ens data för att träna på. Anders Hermansson (26:02) Just det. Ja, just det. Bra poäng, just det. Så att inte det där läcker ut i deras allmänna modell. Det dumt, för det var den här unikiteten vi pratade om förut, och den vill man ju hålla in-house. Hanna Musie (26:31) Exakt. Precis. Så det är ju viktigt att tänka på innan man delar allting. Anders Hermansson (26:40) Just det. då har vi det här med… Det var ju bra, du räknar upp bra grejer där. Och då blir det då som ur vd-perspektiv så kanske det så vi vet det där. Och sen kommer han bara, vänta, det är jag som vet det där. Jag har det i mitt huvud, vad vi har för personer. Så du vet vad som triggade om mitt säljssamtal och sånt där. Ja, precis. Du måste få ut det ur ditt huvud, ner i ett dokument. Dels för… Hanna Musie (26:52) Mm. Mm. Mm. Anders Hermansson (27:05) Tror jag vore bra för din personal om de kände till det lika bra som du gör. om man inte fastnar i founder led sales då som många startups fastnar i. Grundaren kan sälja vad som helst och så säger någon annan samma sak och kunden bara va? Jag förstår inte. Men det gäller ju att kunna förklara det där för en AI då. Vad är det som är skillnaden som gör skillnaden? Det måste dokumenteras. Då kan du föda och då kan ju AI hjälpa till mycket, mycket mer. Hanna Musie (27:08) Nu. Mm. Ja. Och det ju det du behöver träna, om jag ska gå tillbaka till det här trigger brain action. Braindelen är ju där du tränar din AI med all den här informationen. Och sen behöver ju inte du, då behöver du bara gå in och uppdatera när det är någonting som har förändrats eller om du vill justera på något sätt. Så det är ju ändå något som du gör vid ett tillfälle till att börja med men sedan behöver optimera såklart. Anders Hermansson (27:55) Exakt. Och sen så kommer vi säkert in på, om ett tag, något år, eller det går så fort, det är ju självkorrigerande system då, som lär sig själva vad de borde ha gjort, och så gör de bättre nästa gång och så. Men det är ganska advanced. Hanna Musie (28:06) Ja, och det gör de ju redan idag. Så det här var ju ett väldigt enkelt exempel på trigger brain action men sen det går ju att ha flera steg i flödet och sen också som en loop så att den själv säger till att oj nu har du nog missat de här aspekterna och så liksom kör den om loopen. det finns väldigt avancerade system man kan ha idag. Anders Hermansson (28:13) Mm. Jaster. Ja, precis. Jag är till exempel en white paper-skapare där det finns en critic på slutet som kollar av det som har skrivits mot ett antal kvalitetskriterier och sedan skickar en tillbaks till copyrighten om det inte är hög poäng nog. Så det där är ganska bra också att tänka på att man kan låta A-in kolla sig själv. Oftast så är det väl så att A-in… Hanna Musie (28:38) Mm. Mm. just nu. Mm. Anders Hermansson (28:57) Till att börja med tänk mig att AI har en roll. Det är min copywriter, vad bra. Och så får jag granska det där sen. Ja, men vänta nu. Behöver du granska det där? Vad skulle du göra när du granskar det? Ja, jag skulle göra exakt det här. Bra! Säg åt en AI då att göra det åt dig. får du ett steg till i din process automatiserat. Ja, grymt. Du, vad heter det? Tack för en liten exposé där kring verktyg och så. Det här är ju naturligtvis så att man… Hanna Musie (29:10) Mm. Spik sökt. Anders Hermansson (29:24) Det enda råd jag har när det gäller verktyg är att man ska försöka och inte investera sig tokfast i något speciellt verktyg eller en speciell tech stack i alla fall. För att det går så fort så det ploppar upp något nytt. Men har man dokumenterat det där som du sa, kontexten och även sina rutiner, hur man gör saker, då är det lättare att flytta över det till en ny plattform om det dyker upp någonting roligare. Du! Ja, du! Framtiden! Hanna Musie (29:36) Mm. Det är en jättebra poäng Anders Hermansson (29:52) Om vi nu säger att jag är marknadsförare som sitter här med sax och tape-rulle och tycker att det jättekul med marknadsföring och så. Hur ser min framtid ut jämfört med hur en framtida marknadsavdelning kommer att vara? Hanna Musie (30:06) Den traditionella marknadsförings- setupen tror jag kommer att dra ut. Det kommer att vara ännu viktigare för marknadschefen- går från personalansvar till att vara mer en dirigent av intelligenta system. Min spaning är att ett AI-native marknadsföringsteam- kommer att bestå av tre personer som dirigerar sitt team av AI-agenter. Och då kommer det vara en person som äger top of funnel, alltså brand, positionering, community, relationer och de delarna tillsammans med sina AI-agenter. En person som äger bottom of the funnel, alltså konvertering, automation, pipeline med sina AI-agenter. Och sen en AI native CMO eller motsvarande person som äger liksom helheten och då förstår både affären och och tekniken. sen allt däremellan kommer då bara av ägentlert. Anders Hermansson (31:12) Nu har vi fokuserat mycket på marknadssidan. Har du några tankar kring vad som förändras på säljsidan? Hanna Musie (31:23) Ja, men säljssidan tror jag kommer vara lite mer… lite annorlunda ändå för att det blir ännu viktigare med community, relationsbyggande och de delarna. Så det man ser är ju att det går väldigt mycket mot product led growth när det kommer till sälj. de här low intent kunderna där kör man mer att produkten säljer sig själv via olika… Nu kommer jag in på det då med marknadsföringskanaler medans säljarna har mer fokus på de här high intent stora kunderna och kanske blir mer att man åker ut till varandras kontor eller att man ses någonstans så att det blir viktigare med det här liksom mänskliga. Anders Hermansson (31:56) Mm. Mm. Just det. Precis, vi har sprungit runt kvarteret i ett varv och lärt oss en massa. Och så kom vi tillbaks till att då är det där, nu är det utkristalliserat att det är relationsbygget och den mänskliga relationen som kommer att bli skillnaden som gör skillnaden i många fall då eftersom allt annat kan automatiseras och så. En liten sak som man kan tipsa lyssna om här det är ju att era kunder kommer att trycka in er offert rakt in i AI och fråga vilken ska jag köpa? Hanna Musie (32:26) Mm. Pisses. Anders Hermansson (32:41) Det kan ni tänka på, som att AI optimerar era offerter. Det kommer att vara en vinnare i ett halvår till, innan alla har kommit på att man ska göra det. Hur AI tolkar sin offert. Hanna Musie (32:50) Men en annan grej som också är viktig att tänka på, eller som jag tycker att man ser redan nu, det är att… AI har ju redan börjat automatisera många processer, vilket har frigjort väldigt mycket tid. Men det är ju inte så att människor i timmen har mindre göra, utan då hittar man ju så här, oj, det här har vi väl att göra hur länge som helst. Den här kampanjen har vi väl att testa, men inte haft tid för. Låt oss testa det. Så att det är också det att det frigör ju tid till att utföra det som man inte har hunnit med innan. Anders Hermansson (33:04) Mm. Just det. Tipset är att inte omedelbart titta till att kan skära i personalkostnader med hjälp av AI, utan tänka så här, gud vad roligt, vad skulle vi nu kunna göra? Nu kan vi göra fem gånger så mycket med samma personalkostnad. Det är ett lite mer kreativt sätt att tänka på det. eftersom vi försöker ta VDs perspektiv här, då blir det så att om jag nu tänker att jag har ett gäng med marknadsförare idag och jag har en CMO och så vidare, vad är det för Hanna Musie (33:33) Precis. Anders Hermansson (33:56) Krav jag måste ställa på dem eller om jag sitter i situationen att jag ska rekrytera in ett gäng eller någon, en person. Vad är det liksom för, vad är det för, hur ska anställningsintervjun, hur ska det här arbetsprovet, vad ska det vara för någonting för att det ska vara relevant i den här nya världen liksom? Hanna Musie (34:03) Mm. Ja, nej men det är en väldigt bra fråga och jag skulle säga att… Det viktigaste är att kanske inte leta efter de kriterierna som man har gjort innan eller leta efter specialister utan framför allt så här har de hur snabbt lär de sig och hur bekväma är de med att arbeta med verktyg eller en verklighet som man inte fullt ut förstår för att ingen av oss vet vart vi kommer vara om ett år eller två år eller liksom sex månader till och med. Så jag skulle säga att det viktigaste att fråga i en intervju mer hur lärde du dig det senaste verktyget du inte kunde få sex månader sedan? Och vilket var det? Alltså mer den typen av frågor. Anders Hermansson (35:00) Just det, mycket bra. Mm. Jag brukar ju då fråga såhär, va, ja, du säger att du är såhär nyfiken och såhär, va kul! Vad lärde du senast? Då brukar jag såhär, eeh, vad lärde jag mig senast? Då bara, då behöver du såhär tank i paus. Och sen frågar jag såhär, ja, okej, va kul! Vad, vad, vad brukar du leta efter kunskap? Vilken är din favorit YouTuber? Eeh, aaah, nej, det såhär, aha, okej, så nyfiken var du! Kul! Nästa! Hanna Musie (35:12) Ja men precis. Ja, men precis att det blir viktigare att man är snabb lärd och accepterar att saker och ting, du kommer behöva lära dig hela tiden. Det du har kunnat tidigare, det är ju jättebra erfarenhet att ha för att man då lättare kan träna AI-agenterna. Men man behöver vara öppen för att vi kanske behöver byta verktyg varannan månad. Anders Hermansson (35:59) Just det. Att det inte bara är sock och stön kring det. Det är väl… Jag tänker att det finns ju… Man behöver som ett tips till folk som lyssnar som kanske känner att de borde göra mer med AI. Och det är ju så jag har ju gått igenom hur gammal jag är liksom. Jag har gått igenom när marknadsföring blev digital från början. När det verkligen var sax och tape roll till att det vart digitalt. Då var det ju liksom bara att plugga på nätterna. Det är ju så här, det är ingenting som… Hanna Musie (36:02) Ja. Anders Hermansson (36:28) Det går att bara någon timme här och där på jobbet när man har lite över utan det är liksom okej nu är det dags att lyfta sig själv ett steg. Så det är liksom på allvar kompetensutveckling på riktigt. Och då tänker jag också en annan grej om man är expert. Då kan det vara lite ego-utmanande att våga släppa sargen och tänka att jag är nu inte expertexperten utan jag är då det som du säger, alltså dirigenten som dirigerar fyra experter som gör det som jag gjorde förut. Den liksom mentala steget är viktigt att ta för annars kommer man antagligen fastna i fällan att testa AI en gång och glatt se att den inte var lika bra som en själv så kan man lägga det åt sidorna och fortsätta med sin sax och sin tape rulle. Hanna Musie (37:00) Mm. Mm. Mm. Precis. Och det ser man ganska ofta att det är så men jag tycker faktiskt inte att AI är särskilt bra. Jag får inte så bra svar eller jag får inte så bra output. Ja men då kanske du behöver lägga lite mer tid på att förstå hur du sätter upp detta. Bolla med andra som har gjort det som är i liknande sits eller kolla YouTube eller läs på för att… Anders Hermansson (37:27) Nej. Hanna Musie (37:43) Som sagt kan en AI driva ett café. Så jag tror att den kan skriva ihop den här texten du vill ha eller bygga den här landningssidan eller vad det nu är. Anders Hermansson (37:50) Exakt. Tänk på AI som en sorts… Om du har fått en personlig assistent, hur skulle du introducera den personen till jobbet och tala om för den personen exakt hur jobbet ska göra så att den bara flyger igenom processen och producerar fantastiskt resultat? Det är väl en ganska bra… Det är så du ska tänka. Om vi ska försöka sammanfatta, vi har pratat om tre olika punkter. Vi sa att det är viktigt att du inte lämnar kontrollen till AI. Hanna Musie (38:10) Mm. Anders Hermansson (38:18) Det var ju det här med att det måste finnas, om vi tittar i go-to-market perspektivet av saker och ting så ska det finnas en unikitet annars blir du ingen skillnad från alla andra vanilj som håller på och bara tjatkepeterar sig till marknaden utan det måste finnas en kontroll över den kärnan i strategin eller hur det var så vi pratade om. sen hade vi nummer två det var att diagnostisera innan du automatiserar. Det var ju då att Hanna Musie (38:39) Pisses. Anders Hermansson (38:46) Vi måste se över de flöden som vi faktiskt har och titta väldigt mikroskopiskt på dem och se vilka steg gör vi faktiskt nu repetitivt och som du sa vad är det som tar mycket tid? Ibland kan man ju fastna i det att jag gör någonting ganska sällan men det när jag gör det är det supertråkigt så det borde jag automatisera bara nej om du gör någonting en gång om året, sorry ät dig igenom det liksom bokslut eller vad du nu gör för någonting det är bara det så är det ät grodam Men om du gör någonting varje dag och det tar mycket tid eller ofta under en vecka, där har du liksom en riktigt nice möjlighet att automatisera bort det då. Och sen var det det tredje. Ja, just det, exakt. Sättet att göra det på, tänk verkligen på att skriva ner det. Vad skulle du föreslå? Är det papper och penna? Hanna Musie (39:24) Och är vi där, börjar jag skriva ner stegen först. Det beror på hur man är som person, men miro-boards är ju väldigt bra att rita upp flöden i. Papper och penna går också bra. Bara så ni har det tydligt framför er. Så är sätt som känns mest bekvämt. Anders Hermansson (39:40) Mm? Ja? Ja. Om man är en babbelmänniska, då kan man sätta på voice-rekorden på sin iPhone och ta en promenad och berätta för sig själv hur man gör saker. Det kanske känns lite konstigt i början att bara prata rakt in i en mikrofon, men det kan man göra. Sen kan man lägga den till en AI och försöka reda ut hur man gör saker. Det var bara lite grann på kul. Tänk så här… Vänta nu, har du ska strukturera din process? Ja men vänta nu, kan inte en AI strukturera den? Fast du måste ju ge den input då till den här hjärnan. Annars så kommer den att göra något vanilj eller något fel. Det tredje, var ju just det där med hur framtidens marknadsorganisation behöver se ut och vilka krav man måste ställa på personerna där. Och då pratar du om att, de här tre personerna, hur stort är det bolaget som klarar, som liksom, de klarar av att marknadsföra där tre personer? Ja då. Hanna Musie (40:47) …small till medium-sized. Så liksom, ja. Anders Hermansson (40:52) En hanterbar företag. Eller hur? är ju exakt. Vi är mycket midsize-bolag i vår bolagspyramid. Vi har pratat i B2B-kontexten. Det finns säkert massor prata om i B2C också. Större volymer, fler och allt sånt där. Men nu har vi hållit oss inom B2B som vi alltid gör i Säljmarknadspodden. Hanna Musie (40:56) Som majoriteten av svenska bolag är. Mm. ⁓ Precis. Anders Hermansson (41:18) Men då var det teamet som då kommer att bli dirigenter istället och ska övervaka ett gäng med AI var. Och där sa du att ditt tips var att kunna dela upp ansvaret mellan de här var top of fun, alltså det man gör tidigt för att försöka få folk att bara uppmärksamma en och få en viss känsla. Och sen så det som är längre ner i tratten då där man konverterar och får igång sälja. Det var det så ungefär du sa. Hanna Musie (41:44) Ja, precis. Och sen en CMO eller motsvarande som håller ihop helheten. Anders Hermansson (41:49) Just det. Och som har bra budget för tokens. Hanna Musie (41:52) Det var en annan poäng som jag skulle säga tidigare men jag vill inte sticka in det. För du pratade mycket om det här med din loop. Alltså du har en AI som kritiserar din… Ja, och det är ju viktigt då att tänka på tokens där för att den loopen kan du ju hålla på hur länge som helst. Anders Hermansson (42:09) Ja. Ja exakt, de kan aldrig bli nöjda. Jag satt till två varv, sen får de vara nöjda. Riktigt. Och sen har vi det här med hur man ska tänka som person i marknadsteamet. Eller då som tips till vd här att coacha sina befintliga marknadsförare. Eller vad man ska leta efter i rekryteringsförfarande. Just med hur snabbt lär man sig saker. Hur snabbt tar man till sin ny kunskap helt enkelt. För det det som är… Hanna Musie (42:19) Det var bra. Anders Hermansson (42:43) Där ökar hastigheten exponentiellt med att det kommer nya möjligheter och är man duktig på att ta till sig sånt, kan man ju också utnyttja det och till företagets fördel då. Hanna Musie (42:53) Och även vara trygg i att vara otrygg. Anders Hermansson (42:57) Ja just det. Att man vågar göra saker innan man är helt supersäker på. Snyggt, absolut. Det är en väldigt bra tips. Okej, apropå tips. Ska vi försöka nu? Nu har Hanna kommit här med massa bra insikter och kunskaper kring det här med hur man automatiserar marknadsavdelning med AI. Och jag känner att jag nu vart ännu mer stressad. För det har varit en sak till jag BODE göra. Och jag har redan brist på tid. Vad är ditt konkreta tips kring vad jag ska göra nu för att påbörja resan? Vad är nästa grej jag borde göra? Hanna Musie (43:35) Första grejen att göra är ju en audit på nuvarande processer. en helt vanlig vecka, bara hur många timmar lägger du på olika saker som inte kräver ditt mänskliga omdomme? Och inte köpa fler AI-licenser eller ens fundera på vilka verktyg som finns just nu, utan bara fokusera på dina egna processer och skriva ner dem. Det skulle jag säga är A och O. Anders Hermansson (43:59) Hmm… Hmm… Just det. Så då blir det så här, vd, leva som man lär, köra vd, gör det här själv, men instruera också dina marknadsförare till att göra exakt samma sak. Sen kan ni compare notes då efter en vecka och se vad kom vi på allihopa kring vad vi gör för någonting. Och då har ni tagit ett första viktigt steg då. Hanna Musie (44:24) Ja, och om man känner att man känner sig ensam i den här resan söker till ett sammanhang där man kan få inspiration från andra som redan har gjort jobbet. det kan ju spara hur mycket trial and error-tid som möjligt. Anders Hermansson (44:32) Mm. Just det. Man behöver inte känna i det här sammanhanget att man är sift på bollen och så vidare. Men det är lätt att tro när man är inne, nu vet inte jag hur folks Instagram algoritmer ser ut men min är ju helt nerlusad av AI förstås är påar och sånt där. Man tänker så här men gud vad långt efter jag är. Det är en missvisande bild. Det är verkligen så att om man har kommit, så har man börjat tänka på de här grejerna då ligger man ganska bra till än så länge. Får man sluta? Slutar det hela med då? Avslutar det hela med då då? Ja. Hanna Musie (44:54) Ja. Det ses. Där! Mm. Ja. Anders Hermansson (45:10) Ja men grymt Hanna, tack snälla för att du var med i Säljmarknadspodden. Hanna Musie (45:14) Tack så mycket för att jag fick vara med, det varit jättekul att prata med dig. Anders Hermansson (45:17) Ja, roligt. Har du så fint, då? Hej hej! Hanna Musie (45:19) Då sa man… Hej! Anders Hermansson (45:21) Vilket bra avsnitt eller hur? Hanna är ju grym verkligen. som jag sa tidigare i avsnittet så har vi på Business Reflex gått all in på det med AI sen flera år tillbaks. Och har en ganska avancerad setup för hur det här ska fungera för att det ska bli maximalt effektivt för marknadsfunktioner och för den delen också säljfunktioner. Så om du är intresserad av att få ut mer av AI eller bara vill bolla och bolla kring er egen resa och hur ni ska ta er vidare så är du hjärtligt välkomna att höra av dig. Men som vanligt, vad den gör där ute så ska den vara relevant. Hejdå! The post Podd #250 – Automatisera marknad med AI appeared first on Business Reflex.

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The AI LLM boom seems to show no sign of slowing down. Each time I think we've reached some level of crazy use or predictions, things take another turn. I still find myself pinging back and forth between this will be amazingly good and horrifyingly bad. Sometimes on the same day. Read the rest of Half of All Engineers

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Recently I saw an interesting article, saying that someone could build a general purpose coding agent in 131 lines of Python code. That's a neat idea, though I'm not sure that this is better than just using Claude Code, especially as the agent still uses the online version of  the Claude model from Anthropic to generate code or perform other tasks. There's a video in the article showing how this code can be used to perform some quick tasks on a computer. However, the code isn't specific to Anthropic. It can be used with any LLM, and I started doing just that, with a copy of the code from the article, but modified to use a local AI LLM running under Ollama. You can see my repo and feel free to download and play with it. It's expecting a local LLM on 11434. Read the rest of Local Agents

We're thrilled to be joined today by Neely Khan and Rachel Alday to talk all things storytelling, marketing to luxury, being chosen vs being found, AI / LLM discoverability, and a LOT more.Enjoy!⭐️ Links & Show NotesAdam NorkoConrad O'Connell Neely KhanRachel AldaykahaniAbode Luxury Rentals

Думаете, знаете полный lifecycle удаления пода в Kubernetes? Даже опытный инженер с CKA запнулся на этом вопросе. Мок-собеседование на Senior DevOps с live coding и тремя интервьюерами. ЧТО СПРАШИВАЛИ - Cloud: миграция AWS в Yandex Cloud, DynamoDB в YDB, Kafka HA в трех зонах - Terraform: структура репозитория, Terragrunt, state management, code review модулей - Kubernetes: pod lifecycle, graceful shutdown, kube-proxy, endpoint slices - Live coding: Helm troubleshooting сломанного StatefulSet upgrade - AI/LLM: токенизация, промпт-инженерия, MCP Server - "обычно говоришь LLM сделай красиво" - CI/CD: pipeline от merge request до prod, rolling update vs canary, GitOps и Argo CD - Скриптинг: code review скрипта удаления Docker-образов из registry КАНДИДАТ Владимир Ушков - инфраструктурный DevOps-инженер с опытом в AWS, Yandex Cloud, Terraform, Kubernetes, CI/CD. Интересный момент: кандидат честно признался, что цифра "улучшил на 23%" в CV была "органолептической" - и добавил: "в эпоху LLM резюме тоже надо писать для LLM". Фидбэк по интервью доступен на Patreon/Boosty. Хотите пройти mock interview на нашем канале? Пишите нам! ССЫЛКИ Поддержать наш подкаст:   - Patreon - https://www.patreon.com/c/devopskitchentalks   - Boosty - https://boosty.to/devopskitchentalks ПОДКАСТ YouTube - www.youtube.com/@DevOpsKitchenTalks Apple Podcasts - https://apple.co/41O6mqA Spotify - https://t.ly/Jg5_2 Yandex Music - https://music.yandex.ru/album/10151746 PodBean - https://devopskitchentalks.podbean.com НАВИГАЦИЯ 00:00 - Знакомство: три интервьюера и кандидат 03:24 - Начало интервью: "Почему хотите работать у нас?" 06:37 - Self-presentation: опыт в DevOps и инфраструктуре ЧАСТЬ 1: CLOUD И ИНФРАСТРУКТУРА (Саша) 10:46 - AWS и Yandex Cloud: зоны ответственности инфра-команды 16:38 - Миграция AWS в Yandex Cloud: DynamoDB, риски, планирование 21:00 - Kubernetes: managed K8s, node pools и capacity planning ЧАСТЬ 2: TERRAFORM И IAC (Саша) 24:09 - Terraform: структура репозитория, Terragrunt, state 29:40 - Terraform модули: code review и best practices 32:05 - Стабильность кода: version locking и required providers ЧАСТЬ 3: KUBERNETES DEEP DIVE (Виктор) 42:25 - Kubernetes: CRD, операторы и что нравится в K8s 44:20 - Pod lifecycle: kubectl delete и graceful shutdown 48:00 - Kube-proxy: iptables, endpoint slices, сервисы ЧАСТЬ 4: LIVE CODING (Виктор) 55:00 - Практика: Helm troubleshooting StatefulSet upgrade 01:09:00 - Helm upgrade: дебаг "not valid zip" и restart стратегии 01:22:00 - SRE-подход: "дропаем бэкап, делаем rollout" ЧАСТЬ 5: AI И LLM (Виктор) 01:24:53 - AI для DevOps: токенизация, контекстное окно, промпт-инженерия 01:28:00 - MCP Server и практическое применение LLM в работе ЧАСТЬ 6: CI/CD И GITOPS (Саша) 01:34:24 - DORA-метрики и как считать "улучшил на 23%" 01:37:00 - CI/CD pipeline: от merge request до production 01:45:00 - Branching стратегии: GitFlow vs GitLab Flow 01:48:00 - Deployment: rolling update vs canary, Helm vs Argo CD 01:49:45 - GitOps: source of truth и configuration drift 01:53:00 - Скриптинг: code review скрипта удаления Docker-образов 01:56:57 - Завершение и благодарности ПОДПИСЫВАЙТЕСЬ Telegram - https://t.me/DevOpsKitchenTalks Instagram - https://www.instagram.com/devopskitchentalks/ #MockInterview #DevOps #Kubernetes #Terraform #CICD #LiveCoding #DKT #DevOpsKitchenTalks #SeniorDevOps #GitOps

Zprvu skepse, ale teď už jsem expert na užití AI. A jsem znovu skeptik

We're super excited to present a special edition of Android Faithful, welcoming back friend of the show and VP Product, Android Developer Experience at Google, Matthew McCullough who joins Huyen Tue Dao and Ron Richards to go behind the scenes on the making of the new Android Bench and the AI LLM Rankings recently made available to Android Developers. Matthew was kind enough to give us some time out of his day to give us the inside scoop on what went into the effort, exactly how and why Gemini came out on top of the LLM rankings and a provide a glimpse of what's to come! Hosted on Acast. See acast.com/privacy for more information.

В този епизод, Кив и Тулечки се потапят в света на AI агентите, разглеждайки ги като работниците на бъдещето. Те обсъждат дефиницията на един AI агент – как се стига до него от LLM и какви са основните му характеристики като автономност и използване на инструменти. За илюстрация на навлизането им се използват примери с професии като Търговец, Счетоводител, Офис мениджър и HR. Говори се за техническата част – как агентите използват инструменти, връзки към организационни системи, RAG за вътрешна документация и как компютрите вече си говорят на човешки език. Акцентът пада върху паметта на агентите, само-сумаризирането и защо контекстният прозорец е от ключово значение, тъй като LLM-ите са без състояние (Stateless). Във втората част разглеждат как навлизането на AI агентите ще промени света на труда и управлението. Накрая питат дали AI агентите са пътят към Общия изкуствен интелект (AGI), къде е разликата с ASI и обсъждат сравнението на модел срещу човешко представяне на тестове. Споменато в епизода: https://www.greaterwrong.com/posts/SEszTmpx7gFaAaHFq/career-decisions-if-you-take-agi-seriously#Productivity__The_Evidence_Is_Mixed__But_the_Pattern_Is_Clear?utm_source=tldrnewsletter https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/ За подкаста: „Агент 001“ изследва пресечните точки на технологиите и обществото, на дигиталното и реалното, на нещата и данните за тях. Това е една от шестте серии на Ratio Podcast – подкаст за любопитни хора. С негова помощ ще навлезете в света на Изкуствения интелект и технологиите и ще чуете неформални разговори с интересни събеседници, свързани или вдъхновени от науката и AI. Автор на музиката е Мишо. Партньори са Grapwise.ai И Данни за добро

Send a textAI just found hundreds of high-severity vulnerabilities hiding in open source, and the market flinched. We dig into what Anthropic's Claude Code Security actually means for security teams, why vendors like CrowdStrike and Okta aren't going away, and how the real change lands on roles, workflows, and the skills you need next. From CI/CD integration to vulnerability discovery at scale, we frame where general models augment specialized tools and where human expertise still anchors the stack.We also get tactical with five CISSP-style AI questions designed to sharpen your instincts. You'll learn how adversaries reverse engineer decision boundaries to drive up false negatives, what adversarial examples look like in practice, and why adversarial training matters. We break down indirect prompt injection—how a crafted document can hijack an LLM to exfiltrate session data—and outline guardrails that actually reduce risk. Then we map AI risk using NIST's AI RMF, focusing on the Measure function to evaluate potential harms to protected classes, and we unpack why federated learning still faces privacy leakage through gradient updates without differential privacy and secure aggregation.If you're in a SOC or building AppSec pipelines, this conversation gives you a blueprint to adapt: automate tier one triage, monitor for model drift, add OOD detection, and treat your models like code with tests, reviews, and rollbacks. If you're planning your career, we share concrete pivot paths into detection engineering with ML, AI governance, and assurance. Want more hands-on practice and mentorship to pass the CISSP the first time and future-proof your skills? Subscribe, share this with a teammate, and leave a review with the next AI topic you want us to tackle.Gain exclusive access to 360 FREE CISSP Practice Questions at FreeCISSPQuestions.com and have them delivered directly to your inbox! Don't miss this valuable opportunity to strengthen your CISSP exam preparation and boost your chances of certification success. Join now and start your journey toward CISSP mastery today!

Jack Chambers-Ward hosts a solo episode of Search With Candour recapping seven major SEO and digital marketing news stories from the first six weeks of 2026, previously covered in the Core Updates newsletter. He highlights Google's Universal Commerce Protocol (UCP) for agentic commerce and checkout capabilities, Google's Business Agent for brand-voice shopper conversations, and Google's Personal Intelligence initiative that personalises experiences by connecting Gemini to apps like Gmail, YouTube, Photos, and Search. He also covers Gemini-powered AI Insights in Google Trends, Chrome's agentic “auto browse” features that can complete multi-step tasks, a SparkToro study showing AI/LLM recommendations are highly inconsistent, and the February 2026 Google Discover core update aimed at reducing sensational clickbait, improving local relevance, and addressing self-promotional “self-ranking” listicles. Jack notes plans for ongoing monthly news recap episodes and points viewers to links in the show notes for all sources.Links to resources/references:https://developers.googleblog.com/under-the-hood-universal-commerce-protocol-ucp/https://support.google.com/brandprofile/answer/16410382https://blog.google/innovation-and-ai/products/gemini-app/personal-intelligence/https://blog.google/products-and-platforms/products/search/google-trends-explore-with-ai/https://blog.google/products-and-platforms/products/chrome/gemini-3-auto-browse/https://sparktoro.com/blog/new-research-ais-are-highly-inconsistent-when-recommending-brands-or-products-marketers-should-take-care-when-tracking-ai-visibility/https://developers.google.com/search/blog/2026/02/discover-core-update00:00 Introduction02:34 Candour Website Builds: Why SEO Must Be Baked In From Day One04:17 Story #1: Google's Universal Commerce Protocol (UCP) for Agentic Commerce08:52 Story #2: Google Business Agent - Branded AI Chat for Retailers11:50 Story #3: “Personal Intelligence” and the Start of Fully Personalised Search15:09 Story #4: Gemini-Powered Google Trends Insights17:02 Story #5: Chrome “Auto Browse” & Gemini in the Browser22:54 Story #6: SparkToro Study: Why AI Brand Recommendations Are Inconsistent31:51 Story #7: February 2026 Google Discover Core Update34:35 Wrap-Up and upcoming episode

This week I'm delighted to introduce Ayush Sharma, Founder and CEO of Warp. Warp are building the next-gen, AI-native employee management platform for fast-growing companies. We are diving into Warp's journey, why they are tackling the employee management space and more importantly the how behind their journey – it wouldn't be an Enginears podcast if we aren't breaking down the product and engineering challenges behind this. - 2 years in, closed $18M Series A, alongside YC, Dropbox C-level, Amjad (Replit) - crew of highly technical + product folks. - Understanding the friction points of the payroll ecosystem and how Warp are re-building this with a highly-technical, AI-native approach. - Scale, performance and fault-tolerancy challenges. - Ayush's product-first mindset and how he believes companies of 2025+ will build category defining companies. - Meta points around AI/LLM's If you're keen to share your story, please reach out to us! Guest: https://www.linkedin.com/in/ayushsharma01/ Careers: https://www.joinwarp.com/careers/rolesPowered by Artifeks!https://www.linkedin.com/company/artifeksrecruitmenthttps://www.artifeks.co.ukhttps://www.linkedin.com/in/agilerecruiterLinkedIn: https://www.linkedin.com/company/enginearsioTwitter: https://x.com/EnginearsioAll Podcast Platforms: https://smartlink.ausha.co/enginearsHosted on Ausha. See ausha.co/privacy-policy for more information.

There have been a lot of features added to the SQL Server platform over the years. Several of these features let us perform functions that are beyond what a database has traditionally been designed to handle. SQL Server has had the ability to send emails,  execute Python/R/etc. code, and in SQL Server 2025, we can call REST endpoints. Quite a few of these features (arguably) are more application-oriented than database-oriented. There's nothing inherently wrong with having a server perform some of these functions, and there have been some very creative implementations using these features. I recently ran into one of these examples from Amy Abel, where she shows how to use the new REST endpoint feature to call an AI LLM to generate and send emails from your database server. That's creative, and it's reminiscent of the numerous examples from various experts over the years who demonstrate how these features can be used to accomplish a task. Read the rest of Expensive CPUs

＜目次＞(0:00) 今までの振り返り(1:37) ChatGPTのメモリーレイヤーの実態とトレードオフ(8:52) 情報の劣化と価値の変化(13:09) 自分の世代の音楽が一番と感じる説(14:34) どの服を着ていくべきか？の複雑さ(16:27) 大量のデータが必要になるが実現する難しい(19:59) 複数のアルゴリズムが同時並行で走る(22:24) AIによるモノカルチャー化とLLMの言語(25:50) AIにSF小説を書かせると同じ主人公の名前が出てくる現象(29:25) イギリス政治家がLLMに影響される事例(31:01) 映画、フォント、本の表紙、サムネイルなどのモノカルチャー化(35:50) アメリカ人のアルコール消費量が落ちた影響(38:29) 逸脱・ふざける重要性、違いを見つけるAI(40:30) 私自身がまだ気づいてないかもしれないユニークな点(43:30) 飲まない宮武さんが語るアルコールの話w(43:44) 意外と違いがあまりないかも？(45:32) 未だに見てない「The Big Door Prize」(46:37) AIメモリーの発展によって人間は情報を覚えなくなるのか？(48:14) 何を覚えないといけないのか？(51:29) デジタルツインと大量通知の時代(54:46) 通知の歴史(58:00) AIの記憶再現、合成メモリーの可能性＜参照リンク＞https://offtopicjp.notion.site/303-2c9c8b57e114804ca47bd06af06ff04e?source=copy_link＜About Off Topic＞Podcast:Apple - https://apple.co/2UZCQwzSpotify - https://spoti.fi/2JakzKmOff Topic Clubhttps://note.com/offtopic/membershipX - https://twitter.com/OffTopicJP草野ミキ:https://twitter.com/mikikusanohttps://www.instagram.com/mikikusano宮武テツロー: https://twitter.com/tmiyatake1

Enterprise SEO teams track AI visibility without measuring business impact. Eli Schwartz, growth advisor who's driven millions in organic revenue for Tinder, Coinbase, and LinkedIn, reveals why current visibility tracking resembles "impression tracking without attribution." He outlines first-click attribution frameworks that demonstrate SEO's true $200M revenue contribution, competitive share-of-voice analysis that prioritizes market positioning over granular prompt tracking, and sustainable citation strategies that focus on quantity over manipulated mentions.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Почему софт в автомобиле, который стоит миллионы, часто уступает по качеству и скорости телефону за 50 тысяч и как на это влияет война экосистем? Погружаемся в анатомию современного автомобильного софта вместе с Денисом Неклюдовым — тимлидом команды Android Automotive OS в Google. В выпуске разбираемся, почему автопроизводители вроде General Motors объявляют войну Apple CarPlay; заглядываем ПОД КАПОТ и обнаруживаем, что в машине часто работает не одна, а сразу две операционки; эмпатируем разработчикам приложений под авто, которые страдают из-за большой фрагментации и жестких гайдлайнов по безопасности. И, конечно, говорим о будущем: как AI и LLM превратят машину в "третье жилое пространство", и почему подогрев сидений по подписке — это только начало. Партнёр команды Podlodka — наши давние друзья @AvitoTech. Это команда с крутыми процессами, культурой здравого смысла и эксперимента. Узнать про их технологии, подходы и прокачку компетенций в командах можно по ссылкам: – Как декомпозиция повышает точность распознавания текста: опыт с фотографиями СТС https://clc.to/K4mk2A – Как мы используем RFM-сегментацию, чтобы улучшать CRM-коммуникации в Авито https://clc.to/rWGtng – Как аналитики Авито с помощью ML помогают людям выбирать хорошие авто с пробегом https://clc.to/Rt1C7A Реклама. ООО "Авито Тех”, ИНН 9710089440, erid:2SDnjd1eqTW Также ждем вас, ваши лайки, репосты и комменты в мессенджерах и соцсетях!
 Telegram-чат: https://t.me/podlodka Telegram-канал: https://t.me/podlodkanews Страница в Facebook: www.facebook.com/podlodkacast/ Twitter-аккаунт: https://twitter.com/PodcastPodlodka Ведущие в выпуске: Катя Петрова, Стас Цыганов Полезные ссылки: Polestar portraits | Denis Nekliudov | Google | Polestar https://www.youtube.com/watch?v=IYN05v2qXSE Денис на LinkedIn активно пишет про разработку под авто https://www.linkedin.com/in/nekdenis/

Stop the Hype, Start the ProfitThe era of experimental AI pilot projects is over. For C-Suite leaders in the Energy Industry and complex infrastructure, the mandate is clear: deliver quantifiable ROI from AI.This special AI Unraveled episode is a direct sample of our AI-Powered Executive Briefings. We provide a crucial five-minute insight into The Commercial Impact of Large Language Models (LLMs) on Energy Infrastructure, demonstrating the critical shift from technology research to strategic, P&L-linked deployment.Our briefing cuts through vendor hype, focusing on hard engineering outcomes. We treat Gen AI as a critical engineering tool to solve enterprise problems like asset reliability, grid optimization, and OPEX reduction. If you're struggling to bridge the gap between AI lab work and boardroom strategy, this briefing is your first step toward a robust AI roadmap.Key Strategic & Technical TakeawaysGen AI as an Efficiency Tool: Understand why the main application in energy is not chatbots, but unlocking latent capacity and safely eroding conservative safety margins in physical infrastructure.The MLOps Challenge: The true hurdle is not model creation, but MLOps (Machine Learning Operations)—the ability to securely deploy, govern, and continuously monitor complex models at enterprise scale in regulated environments.Quantifiable Return: Hear data on how industrial AI users achieve significant results, including energy savings averaging 23% and CO2 reductions of 24% through optimized upstream operations. Use this data to justify capital expenditure.C-Suite Alignment: Learn how one concise brief ensures your entire leadership team has a shared, defensible vision for AI transformation.Your Strategist: Bridging Engineering and the BoardroomThis strategic insight is delivered by Etienne Noumen, Senior Software Engineer and the host of AI Unraveled.Etienne provides the builder's perspective—someone who designs, deploys, and governs production-ready AI/LLM systems. He specializes in bridging deep-tech engineering with clear boardroom strategy, ensuring your roadmap is feasible, scalable, secure, and ambitious.Why Djamgatech Briefings? We replace ambiguous consulting reports with actionable, 5-minute audio intelligence briefings and a clear governance framework, moving you from planning to decisive execution.Action Steps: Request Your Private ConsultationReady to stop wasting budget on hype and adopt an AI strategy directly tied to the P&L?We offer limited slots for a private, no-obligation consultation to design your customized, defensible AI roadmap.➡️ Request Your Private Consultation Here: https://forms.gle/YHQPzQcZecFbmNds5Connect & Learn MoreLearn more about our Executive Briefings: https://djamgatech.com/djamgatech-executive-briefings-ai-powered-strategic-insightConnect with Etienne Noumen on LinkedIn: https://linkedin.com/in/enoumenKeywords: AI Strategy, Generative AI for Energy, CTO Roadmap, Executive Briefing, MLOps, Strategic Alignment, Asset Reliability, ROI, OPEX Reduction, Digital Transformation, AI Governance, Etienne Noumen

AI Daily Rundown: October 22, 2025:Welcome to AI Unraveled, Your daily briefing on the real world business impact of AIIn Today's edition:

AGI in the Near Term or AI Bubble? The True State of AI (LLM Limits, World Models, and the Profit Puzzle Behind AI's Biggest Claims)

Alex Shevchenko is the Co-Founder of Aurora & Defuse, pioneering next-gen UX with Intents and Chain Signatures for an agentic, user-first future. Defuse Labs develops NEAR Intents to enable seamless cross-chain interactions in an automated world, connecting AI, services, and financial applications. Alex is on a mission to make blockchain invisible, creating seamless, secure, and intuitive crypto experiences for everyday users.In this conversation, we discuss:- In crypto, we have investors, not users - AI & Intents - User-owned AI - Building Rainbow Bridge and Aurora - Decentralized Confidential Machine Learning (DCML) - The AI LLM lifecycle - How AI agents will power the crypto economy - The importance of chain abstraction - NEAR intents are unlocking autonomous finance - Creating intuitive automated agent workflows - AI agents that can transact, adapt, and execute cross-chainAurora Labs Website: auroralabs.devX: @auroraisnearDiscord: discord.gg/auroralabsAlex ShevchenkoX: @AlexAuroraDevLinkedIn: Alex Shevchenko---------------------------------------------------------------------------------This episode is brought to you by PrimeXBT.PrimeXBT offers a robust trading system for both beginners and professional traders that demand highly reliable market data and performance. Traders of all experience levels can easily design and customize layouts and widgets to best fit their trading style. PrimeXBT is always offering innovative products and professional trading conditions to all customers.  PrimeXBT is running an exclusive promotion for listeners of the podcast. After making your first deposit, 50% of that first deposit will be credited to your account as a bonus that can be used as additional collateral to open positions. Code: CRYPTONEWS50 This promotion is available for a month after activation. Click the link below: PrimeXBT x CRYPTONEWS50

*以下はAIによる要約です*今回の「フリーアジェンダ」は、メモをきっかけにAI（LLM）ばりのトークが連発する、いつも以上に予測不能な展開に！ 「川上・川下議論と小売り業、そして情報のおろし売り・小売り」というテーマ: hikaruさんが1ヶ月以上前にメモしたこのお題からスタート。yamottyがその文脈を知らないままテーマを推察「キングダムではやはり騰の話がしたい」: 次のテーマもhikaruさんのメモからyamottyがキングダムの「騰」についてAI（LLM）のように語る「騰」の魅力とhikaruさんの共感: メルカリでの「ファルファルする」といういじりからキングダムを読み始め、無血開城や対局的な統治視点を持つ「騰」に自分との共通点を見出しています。「法とは国がどうありたいかという願い」: 「騰」の魅力から派生し、李斯の「法とは国がどうありたいかという願いのことだ」という言葉に深く共感する二人の熱い漫画談義が展開されます。大人たちの漫画ライフ: 映画は眠くなるが漫画は没入できると語るhikaruさんが、「九条の大罪」や「ゴールデンドロップ」といったアウトロー漫画に触れながら、漫画喫茶が苦手でTSUTAYAで大量に借りて読む「悪魔的な贅沢」を満喫しているエピソードも。変化する漫画市場とGEOの戦略: デジタル化が進み、TSUTAYAのようなリアル店舗が減少する中で、GEOが「ラストマンシップによる利益」を上げているという市場の興味深い動きにも言及。漫画インフルエンサー: 大人になっても漫画は日本人を救っていると語り、ドングリFMのnarumiさんの紹介で漫画を買うというyamotty。▼お便りや感想はこちらからお待ちしています。⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://forms.gle/73RW6Fq7TWMJpfNx9⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠採用された方には、何かノベルティをお送りします。▼フリーアジェンダとは...メルカリでグロースを務めてきた@hik0107と株式会社10Xの創業者&代表である@yamotty3 が仕事のことから哲学、雑談など話すPodcastです。名は体を表す、という諺どおり、かっちりしたアジェンダなく二人のその時のバイブスによって思いついたままに話す、まさに「フリーアジェンダ」なスタイルが特徴。▼有料コミュニティはこちら⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://community.camp-fire.jp/projects/view/318756⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠▼Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠FREE AGENDA⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ /⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Yamotty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠  /⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Hikaru⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠▼配信アカウント⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ /⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ /⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Anchor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ /⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠note⁠

Hey ho, welcome to the Publishing Nerd Corner, where we dive into the more technical aspects of authorship.Jess here. I love it when Sarina schools me on all things publishing nerdery, so we decided to make it official and create a whole new series. I have a long list of things I want her to explain for us, so stay tuned for more. In the meantime, our first Nerd Corner chat is a timely episode about the Anthropic case specifically and registering your copyright specifically. We're going to discuss: * The benefits of registering your copyright with the United States Copyright Office. * The possibility of a settlement in the Anthropic lawsuit, and what that could mean for authors.* Why copyright registration will be part of any potential settlement.* How to register your copyright.* Did your publisher fulfill its obligation to register your copyright?For more information about the benefits of copyright registration, see the Copyright Alliance To register your copyright yourself, you'll need Copyright.gov. You will also want to read the Authors Guild post about, “What Authors Need to Know About the Anthropic Settlement”Hit that “play” button and nerd out with us for fifteen minutes! Transcript below!EPISODE 466 - TRANSCRIPTJess LaheyHey, it's Jess Lahey. If you've been listening to the Hashtag AmWriting Podcast for any length of time, you know that, yes, I am a writer, but my true love, my deepest love, is combining writing with speaking. I get to go into schools, into community organizations, into nonprofits, into businesses, and do everything from lunch-and-learns, to community reads, to just teaching about the topics that I'm an expert in. From the topics in The Gift of Failure, engagement, learning, learning in the brain, cognitive development, getting kids motivated, and yes, the topic of over parenting and what that does to kids learning, to topics around The Addiction Inoculation, substance use prevention in kids, and what I've been doing lately that's the most fun for me, frankly, is combining the two topics. It makes the topic of substance use prevention more approachable, less scary when we're talking about it in the context of learning and motivation and self-efficacy and competence and, yes, cognitive development. So if you have any interest in bringing me into your school, to your nonprofit, to your business, I would love to come. You can go to Jessicalahey.com. Look under the menu option “Speaking” and go down to “Speaking Inquiry.” There's also a lot of information on my website about what I do. There's videos there about how I do it. Please feel free to get in touch. And I hope I get to come to your community. If you put in the speaking inquiry that you are a Hashtag AmWriting listener, we can talk about a discount. So that can be one of the bonuses for being a loyal and long-term listener to the Hashtag AmWriting Podcast. Hope to hear from you.Multiple SpeakersIs it recording? Now it's recording. Yay! Go ahead. This is the part where I stare blankly at the microphone. Try to remember what I'm supposed to be doing. All right, let's start over. Awkward pause. I'm going to rustle some papers. Okay. Now, one, two, three.Jess LaheyHey, welcome to the Hashtag AmWriting Podcast. I'm Jess Lahey, your host, along with another host today—this is going to be super fun. We are the podcast about writing: short things, long things, poetry, prose, book proposals, querying agents—we're basically the podcast about getting the work done. I am Jess Lahey. I'm the author of The Gift of Failure and The Addiction Inoculation. And you can find my journalism at The New York Times, The Washington Post, and The Atlantic.Sarina BowenAnd I'm Sarina Bowen, the author of many contemporary novels, and also a council member on The Authors Guild. And it is in that spirit that we are bringing you a special episode today, which we're calling part of our Publishing Nerd Corner segment.Jess LaheyOur favorite stuff.Sarina BowenYeah, so publishing nerd stuff. Here we go, and the topic is pretty timely.Jess LaheyAnd juicy.Sarina BowenAnd juicy. We're talking about why authors copyright their work, what it means, and how it ties into everything going on with the Anthropic lawsuit and potential settlement.Jess LaheySo, backing up, could you tell us a little bit about the Anthropic lawsuit, and sort of what it was about, and why everybody's talking about it right now?Sarina BowenOf course. So, Anthropic is an AI LLM, Large Language Model Company, just like OpenAI is the same as ChatGPT. Anthropic are the people who make Claude, but all the AI big companies are being sued right now, including Meta, including Microsoft, or...Jess LaheyGoogle. Google.Sarina BowenYeah, sorry.Jess LaheyNot Microsoft.Sarina BowenAnd also the new one is there's a new lawsuit against Apple. So, basically, everybody who went out and made a big LLM model using stolen, pirated books and articles downloaded from the Internet is being sued variously by different organizations, and it looks like the Anthropic lawsuit might be resolved first.Jess LaheyOkay, so what are they being sued for?Sarina BowenThey're being sued for a couple of things. First is the wholesale piracy of lots of books downloaded off the internet, and second, for feeding all of those books into their models to teach them how to speak and compose.Jess LaheyA while ago, weren't some—I think some—internal memos around the whole Meta thing where, essentially, they acknowledged how much it would cost to purchase legally all of the things they needed to model, do their large LLMs, and they decided, “Wow, that would be a lot of money.”Sarina BowenRight.Jess Lahey“We'll just steal them.”Sarina BowenWe don't want to deal with copyright. Well, specifically, the most interesting internal memos that we've seen have been involved in the Meta case, which we're not really talking about tonight, but yeah, there are some big smoking guns out there. But I wanted to take this opportunity to talk about the practical nature of copyrighting your work, because there's a potential settlement on the table that's taking shape in terms of how authors will be paid some portion of a $1.5 billion settlement from this Anthropic suit, potentially, and whether or not you have a registered copyright on your book is going to matter. So, first of all, in this case, the judge did rule—well, we wanted him to rule—that using these books to train the model was not a fair use situation.Jess LaheyRight. They were trying to say, “No, no, this is just fair use.”Sarina BowenRight.Jess Lahey“We shouldn't have to pay anybody.”Sarina BowenAnd unfortunately, we don't have a ruling in favor of this concept yet, and The Authors Guild cares very much that it's not fair use and will continue to fight for that. But we instead were ruled in this case something that is actually quite powerful and important to the whole conversation, which is that the judge said that Anthropic downloading all of these titles—these millions of stolen books—from a piracy site was, in fact, illegal and that they are going to have to pay. So the ruling was against them. So now this is a class-action suit, and in a class-action suit, all of the parties in the class—you can opt out if you want to, like if you're an author who would rather sue them individually, you can still do that. But it looks like in defining the class of who is eligible to receive a payout; you're going to have to have a registered copyright. Your copyright will have had to have been registered within five years of publication, and also before they downloaded it.Jess LaheySo, to clarify, some of the questions I've seen floating around on the interwebs are about, “Oh, but there was that big list that was published by The Atlantic.” You could go to The Atlantic and just see, and “oh my gosh, I had six titles that were on that list. Does that mean that I'm going to get money for all of those titles?”Sarina BowenOkay, well, that is a great question. And actually, I need to stipulate real quick that I am not a lawyer.Jess LaheyRight.Sarina BowenYou're a lawyer, and almost certainly I'm going to make an error when I'm speaking on this tonight. I have spent a lot of time listening in meetings about these things, so I feel comfortable enough to discuss it with you tonight. But, um, but I'm going to make a mistake. So you need to check everything...Jess LaheyRight.Sarina Bowen…when you make your own legal decisions. So wait, what was the question?Jess LaheySo the question was about that big list at The Atlantic.Sarina BowenOh yeah!Jess LaheyThat was like, what, 5 million titles or so?Sarina BowenWell, that list was taken from a specific piracy site.Jess LaheyRight.Sarina BowenBut it doesn't know which titles the company actually downloaded, so only the company has that list. So, first of all, that database is sort of handy and interesting, but it is not definitive in terms of this list.Jess LaheySo do not count on looking at that list and saying, “Oh, I have six titles there, maybe I'll get a payout for all six titles.”Sarina BowenRight. So, um, but let's—we really need to talk about copyright registration because there's so much misinformation floating around out there. So it's true that if you sit down right now and write something, you already own the copyright for it. So that's powerful—sort of—right? Um, but the point of registering your copyright—and these benefits are right on the Copyright Alliance website. So we're going to link to the copyright website—but, um, one of the primary reasons why people register is because registration is a necessary prerequisite for bringing, for U.S. copyright owners, to bring a copyright infringement suit in federal court. And of course, this is a federal court action, but also because statutory damages and attorneys' fees can only be sued for if you have a registered copyright. If you just own your copyright without registering it, you can sue for damages. The damages in the copyright suit are pretty hard to prove, or at least quantify. So that is why the statutory part of damages is what is being enacted in this judgment.Jess LaheyBut Sarina, I have a publisher. Didn't my publisher register my copyright for me?Sarina BowenWell, probably. My newer contracts all say the publisher must register them, and as far as I can tell, those newer contracts, the publisher did. So, yay. But I do have an old contract from about 2014 that only says that the publisher may register it. And guess what—they didn't. So, first of all, you need to see—you can go to a different database, which is the U.S. government copyright database—and look yourself up and see if your book is in there. And honestly, if your publisher was supposed to register you, and they didn't, The Authors Guild would really like to hear from you, because they're sort of looking into this. Suddenly, you know, in the last 10 days, there's a bunch of people who are like, “Oh my goodness, hang on, they didn't actually do it.” So that's something to think about, something to look at.Jess LaheyYeah.Sarina BowenMeanwhile, because statutory damages are what is going to be paid by this company, that is why the registration—it's not just to make people mad. It's not just to… it's not a gatekeeping thing. It's a legal issue with the settlement. So if you have not been in the practice of registering your copyrights, it's a pretty darn good idea to do that now. It's a completely online process. The site is quite antiquated and not that much fun to work with, and there are some moments in there when you're like, “I don't understand what's being asked of me.” But it's worth taking the time. It costs, I believe, $65 for a single title. They mail it to you at home, and then you have the certificate forever with your copyright registration number, but it's also kept in that database. You are required to deposit a copy—two copies of… well, a digital copy of your book, or two physical ones, and we usually use digital at this point. But totally worthwhile, and all the people who've been slogging it out on the copyright website up till now are probably feeling pretty good about it.Jess LaheyOkay, so there's been this settlement, and I don't know yet whether or not my book is included in that settlement because Anthropic has not turned over their list yet, but let's say I'm on it. When can I get my sweet, sweet dollars?Sarina BowenWell, right now there is a really important The Authors Guild blog post about what to do, and we will also link to that, and they, in turn, link to—I think it's the lawyer's website with a form, a contact form—saying, yes, you know, please keep me in your thoughts and send me the email so that when the list is really ready, we can find each other.Jess LaheyAnd another plug for why you should be a member of The Authors Guild, if you qualify to be a member of The Authors Guild, is that The Authors Guild made sure that their authors were included in the class action suit.Sarina BowenWell, just that they're going to hand the names.Jess LaheyYes. Exactly.Sarina BowenExcept I actually think that if you have multiple titles, if you have multiple publishers, if you use a pseudonym—there's lots of reasons to go to that lawyer's page and fill it out anyway.Jess LaheyYeah.Sarina BowenSo, I mean, the worst that can happen is that both The Authors Guild and you have turned in your name, and they'll have to sort out some duplicates. But that is not the end of the world. And I went there, and I'm filling it in as well.Jess LaheyThe Authors Guild is a great source of reliable, factual information on what is going on with this suit at the moment.Sarina BowenIt is, and it's not like… I'm very proud of my work on the council, but it's like a couple of meetings a month. But what's really happening is that the people who work at The Authors Guild—it's their job. It's a bunch of lawyers who are very good at copyright law, and they've been working on this, like, you know, without sleeping practically, for like a year and a half. So, you know, all of these suits are what they're focusing on all day long. And they want to make sure that the greatest number of authors receive the compensation that they deserve, and it's basically like their whole entire lives right now.Jess LaheyIt's always cool, actually, as a side note, in the annual meetings—I like to attend the annual meetings virtually—and it's always amazing when they give sort of a download of what's been accomplished by The Authors Guild over the past year. So it amazes me, the advocacy that's going on.Sarina BowenIt's a lot of suing people who aren't working on behalf of authors and against book bans and things like that.Jess LaheyAbsolutely, absolutely. Is there anything else that we need to know that's pressing?Sarina BowenRegister your copyrights, people, let's go.Jess LaheyGo to the show notes. The links will be in the show notes, as Sarina said. Worst case scenario, you go to that lawyer website, law firm website, and you double—you know, you've done it, and so has your publisher. But who cares, whatever, as long as you've done the work. And, in fact, I will, when I write the show notes, be going back and doing the same myself. And you know, this is a moving target. This is not over yet. This is a continuing saga.Sarina BowenRight.Jess LaheyYeah, and it's definitely not like a done deal, like, “Yay, I'm going to be getting a check in the mail next week.”Sarina BowenNo.Jess LaheyThat's not the way...Sarina BowenIt's going to take a long time, but there's going to be more of these suits. So, of course, the best time to register your copyright was five years ago. The second-best time is right now.Jess LaheySo, go do that. You have a to-do list. You have homework. Go do those things. And thank you for explaining that stuff. And thank you also for working with The Authors Guild. Because I know it's a ton of work. Not only is it a ton of work for you, doing the meetings and all that sort of stuff, but it's hard to go online and see on social media so many people misunderstanding either what this case is about, and you do a lot of clarifying, which is very sweet.Sarina BowenOh, thank you. But you know what? It's complicated.Jess LaheyIt is very complicated.Sarina BowenAnd I am not a lawyer, and I put in the time to understand it. But the truth is, it's hard. We're dealing with some really complicated concepts. IP is tricky, and, you know, I learn a little more every year, but it's hard, and if it confuses you, you are forgiven for feeling that way.Jess LaheySo, again, thank you. Go do your copyright thing. Go to the law firm website, go to The Authors Guild website, and just catch up. Catch up on what this is all about. And we will keep you posted in our little nerdy corner here, which I'm really excited about. I have a full page of questions I want to ask Sarina about some of the things that she understands really well about publishing and all of the stuff that goes into it—all these things, especially about independent publishing—that is not a world I'm a part of, but you always seem to have great answers to those questions. So we will be delivering those questions and answers to you in our Nerd Corner. And thank you so much for being with us. And until next week, keep your butt in the chair and your head in the game.NarratorThe Hashtag AmWriting Podcast is produced by Andrew Perella. Our intro music, aptly titled Unemployed Monday, was written and played by Max Cohen. Andrew and Max were paid for their time and their creative output, because everyone deserves to be paid for their work. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit amwriting.substack.com/subscribe

From texting workflows and estimate calculators to Google's four-result “Monopoly board,” Phil shows how better ops beat “more leads.” We dig into retargeting your ignored database, the five metrics that matter, and how AI/LLM authority content will shape the next decade. Whether you run HVAC, plumbing, gutters—or manage 1,800 units—these tactics turn chaos into pipeline. Watch to level up your home service marketing today.Connect with Phil RisherWebsite: https://phlashconsulting.com/ Chapters:00:00 – Introduction 07:19 – Two big fixes: ROAS visibility + lead management 09:11 – Text-first workflows that boost response & bookings 13:37 – Chat-to-text widgets & estimate calculators that convert 22:10 – Google “Monopoly board”: LSA, Search Ads, Map Pack, SEO 24:26 – Content flywheel from real customer calls (They Ask, You Answer) 27:21 – AI search & becoming the local authority with content 38:28 – Scaling ladder & PE honey holes (retargeting) 44:45 – Gino Wraps it Up We're here to help create multifamily entrepreneurs... Here's how: Brand New? Start Here: https://jakeandgino.mykajabi.com/free-wheelbarrowprofits Want To Get Into Multifamily Real Estate Or Scale Your Current Portfolio Faster? Apply to join our PREMIER MULTIFAMILY INVESTING COMMUNITY & MENTORSHIP PROGRAM. (*Note: Our community is not for beginner investors)

In episode 85 of o11ycast, Dr. Cat Hicks unpacks AI's impact on software teams from a psychological and social-science perspective. Along with Ken, Jess, and Austin, she explores how AI magnifies long-standing tensions between solitary and collaborative models of development, and how fears about AI often reflect deeper issues like undervaluing collaboration or having unrealistic productivity expectations. The discussion also explores empathy, theory of mind, and pluralistic ignorance, highlighting why developers may prepare more for AI than for each other.

In episode 85 of o11ycast, Dr. Cat Hicks unpacks AI's impact on software teams from a psychological and social-science perspective. Along with Ken, Jess, and Austin, she explores how AI magnifies long-standing tensions between solitary and collaborative models of development, and how fears about AI often reflect deeper issues like undervaluing collaboration or having unrealistic productivity expectations. The discussion also explores empathy, theory of mind, and pluralistic ignorance, highlighting why developers may prepare more for AI than for each other.

Ethical hacker Rachel Tobac joins us to answer a juicy question: How would she hack someone reasonably security savvy like Matt?

An airhacks.fm conversation with Jonathan Ellis (@spyced) about: brokk as a Norse dwarf who forged Thor's hammer, Java Swing UI performance advantages over Electron apps, zb build tool integration, onboarding experience comparison with Cursor, architect vs code buttons functionality, session management in brokk, build and test tool configuration, in-memory Java parser development, JVector and embedding models limitations, agentic search approach using find symbol by wildcard and fetch method tools, hierarchical embeddings concept, package-info for AI context, LLMs as artists needing constraints, Java's typing system advantages for AI feedback, architect mode with multiple tool access, code agent feedback loops, joern code graph indexing, Git integration with jgit, custom diff format avoiding JSON escaping issues, tool calling in architect mode, MCP server development in pure Java - zmcp, prompt templates for team collaboration, JBang installation experience, subscription pricing discussion, organizational subscriptions for corporate teams, avoiding context explosion in architect mode, Gemini Flash for summarization, workspace tools and summaries, build status feedback to architect, enterprise-friendly features development Jonathan Ellis on twitter: @spyced

سلام عليكم الخوت و الخوات! مرحبا بكم ف هاد الحلقة الجديدة ديالنا.ف هاد الوقت اللي الـ AI و الـ LLM's (بحال ChatGPT) ولاو جزء من حياتنا، كاين واحد السؤال كبييير: كيفاش نخبعوا هاد الداتا كاملة، بالطريقة اللي تكون رخيصة و سريعة ف نفس الوقت؟ و هنا فين كايجي AWS S3 Vectors!ف هاد الحلقة، غادي ندويو على هاد الـ feature الجديدة من Amazon S3، اللي غادي تغيّر بزاف الإستعمال ديال "Vector Embeddings"

“Visibility in the age of AI isn't just about ranking anymore—it's about being understood, trusted, and retrievable by the machines your buyers now rely on. These engines extract only the most relevant chunks of content to answer the query. And if your message isn't structured clearly or consistent across channels, you risk being invisible.” That's a quote from David Kirkdorffer and a sneak peek at today's episode.Hi there, I'm Kerry Curran, B2B Revenue Growth Executive Advisor, Industry Analyst, and host of Revenue Boost: A Marketing Podcast. Every episode, I sit down with top experts to bring you actionable strategies that drive real results. If you're serious about growth, hit subscribe to stay ahead of your competition.In The New SEO Frontier: How Marketers Can Win Visibility in the Age of AI, I sit down with David Kirkdorffer. He's a B2B marketing strategist and generative SEO expert. We break down how your content, website, and messaging must evolve to be visible in LLM-powered search. We explore what's changed, what still works, and what's next—so your brand stays front and center no matter which AI engine your buyer turns to.Be sure to stay to the end, where David shares why team alignment across content, SEO, PR, and partnerships is your best defense—and greatest opportunity—in an AI-first future. Let's go.Kerry Curran, RBMA (00:01.422)So, welcome, David. Please introduce yourself and share your background and expertise.David Kirkdorffer (00:07.466)Hi, Kerry, and thank you so much for bringing me on the show. My background: I am a B2B marketer. I've been doing B2B marketing for—let's say—30-plus years. I have focused most of my career on generating leads for sales teams, and that is still my focus, though the way that is done nowadays has certainly changed.I've worked mostly in technology companies, selling technology to technology departments—so IT tech for IT tech consumers. Over the years, that has gone from enterprise accounts, as technologies became more democratized, down to medium-sized businesses and small businesses.So that's briefly about me.Kerry Curran, RBMA (01:00.214)Excellent. David, I know you have been deep into the research around what I'll introduce as the evolution of SEO. Tell me: What are you hearing? What triggered your interest in diving into gaining visibility for brands within the GPTs and other AI engines?David Kirkdorffer (01:25.994)Right. OK, that's a great question. Given my background of trying to get information into buyers' hands—being buyer-centric—a number of years ago I focused on what we might call buyer enablement and the buyer experience: the buyer being successful in finding the information they're looking for on our website. I realized that a lot of the great information buyers want sits behind a gate where you have to speak to a sales rep.The idea I was working with—and many people, of course, not just me—was, “Can we get this information onto our website so that when buyers come, they can find what they need and say, ‘This looks like a good fit'?” Along come these LLMs, and now all of a sudden I'm thinking, “How do I AI-enable training? How do I make sure the AIs have the information that answers buyer questions?”In a way, AI LLM tools are a disintermediating force separating my buyer from my answer. They're turning to the ChatGPTs, the Geminis, the Perplexities, the Claudes, the Copilots, and various other tools—some specialized for particular domains. Our challenge is to make sure our answers are read, understood, and correctly represented within these LLMs so that, when a buyer goes there for an answer, our brand is visible.It's much more effective for a buyer to ask questions with ChatGPT, and you might ask the same question to four or five tools just to validate, because they all have different information sets, models, crawlers, and licensing agreements. Therefore, you may have high visibility in one and low visibility in another. Training data differs; retrieval data differs; the models themselves differ—so they have different “brains,” just like different people. That's what brought me into this: trying to be customer-centric and helping my salespeople so that, when buyers do find information, our brand is there.Kerry Curran, RBMA (04:27.744)That's excellent, David, and it's such a hot topic. I don't think I can go through a few hours of my day without it coming up. I know you've been evangelizing it a lot, which I'm sure generates many questions. What are the main questions people ask you about this capability and opportunity?David Kirkdorffer (04:51.442)Everyone wants to know, “What am I supposed to do? How is this different—is it different?” Two main lines of inquiry emerge. One comes from senior marketing leaders—the CMO or someone at a higher level—who wants to understand what they and their teams can do holistically. The other is very tactical: people approach it from their domain expertise—website, SEO, content—and ask, “What do I do within my lane that makes an impact?”The truth is, it's a bit of both. In my view, it's a holistic problem to solve. You can operate in just one tactical lane—website, SEO, or content—and it will have an impact. When you combine them, the impact is amplified, and it should also involve your PR, partner, and demand-gen teams; their work can help or hurt how your brand is recognized and surfaces in answers. So those two lanes—holistic and tactical—intertwine, and where you start depends on team size and resources.Kerry Curran, RBMA (06:48.354)If the main question is “How do I do this?” what do you think people should be asking first? What's the right starting point?David Kirkdorffer (07:01.140)I think you need a big-picture view of how this is different and what drives it—how GEO (Generative Engine Optimization) actually differs from SEO. It even has many acronyms: generative engine optimization, AI optimization, LLM optimization, and more.Kerry Curran, RBMA (07:38.732)Based on your work, which term do you prefer?David Kirkdorffer (07:44.744)I like “generative engine optimization.” Unfortunately, “GEO” means other things in other domains, which is part of the problem—both technically and from a brand standpoint. When we use shortcuts like acronyms, we know what they mean; the LLM doesn't. It could interpret “MRO,” for example, as any of 50 different things until you spell it out first.Kerry Curran, RBMA (08:24.150)Earlier you said it starts with a mindset. What mindset should people adopt to lean into improving their strategies here?David Kirkdorffer (08:46.292)At the highest level, LLMs and GEO replace the short keyword query box with a large window where users add lots of context. Through vectorization—turning language into math—the LLM finds little chunks of information, the “needles,” rather than presenting a haystack of links. It compares those chunks, validates them against other sources, and synthesizes an answer.We often don't know or care where the answer came from, as long as it's accurate. But that means the LLM isn't reading your whole page; it's reading segments. So this isn't just a technical SEO challenge—it's about the words themselves: how we phrase them, how we make them easy to understand, and how we avoid letting brand personality cloud clarity.Because of “chunking,” answers often come from two or three sentences—maybe 200–300 words—not entire pages. So we need to optimize those chunks.Kerry Curran, RBMA (13:06.506)Before we dive deeper into tactics, explain how these platforms differ from Google's traditional search engines and why that demands a different strategy.David Kirkdorffer (13:41.514)Think of GEO as standing on the shoulders of SEO. If your SEO is weak, the shoulders aren't strong. Some say, “This is just a new kind of SEO,” and there's truth in that. Others think, “We just need to do good marketing,” and that's also true. But with GEO, some shortcuts we've taken—like heavy JavaScript or hidden tab content—now have new impacts because LLMs don't execute JavaScript or click tabs.For example, if your page uses tabs for five benefits, the LLM sees only the first one; it can't click the others. It forces us to reevaluate design choices, because GEO cares about different things.Kerry Curran, RBMA (16:11.054)So SEO is shifting from technical crawlability to a content-first approach—almost back to the early days of SEO. When you talk about chunking content, best practices seem to be resurfacing. What should we consider when writing content now?David Kirkdorffer (17:34.914)The best practice is simply doing what we've always known: write clearly for the reader. LLMs struggle with poetic or highly stylized language; they understand literal, structured information. Our challenge is to provide that clarity without becoming too dry. In the future, LLMs may understand nuance better, but for now, literal clarity wins.Kerry Curran, RBMA (21:09.686)There's still a technical aspect—different from technical SEO a few years ago—like tagging. Why is that more important than ever?David Kirkdorffer (21:09.686)We have semantic tags—H1, H2, H3, etc.—but many treat them as visual elements. You might find an H6 above an H2 because it looks good, but that confuses the LLM. Ideally, one H1 states what the page is about, multiple H2s mark subtopics, H3s detail components, and so on. When that hierarchy is broken, the LLM can't map ideas correctly, and your content may be excluded from answers.Kerry Curran, RBMA (25:57.034)Old is new again: off-site SEO also matters. Why is consistency off-site so critical, and what should brands do?David Kirkdorffer (25:57.034)B2B marketers want their message on as many authoritative sites as possible. A small brand's site may have little traffic, so its signal is weak. Getting listed in directories or partner sites amplifies that signal. In the old days, “brand police” ensured consistent boilerplates—25-, 50-, 100-word descriptions—so customers weren't confused. LLMs work the same way: if they see the same wording consistently, they trust it. When every team tweaks the message, it creates variations that confuse the model, so consistency is key.Kerry Curran, RBMA (30:33.718)This has been super valuable. For listeners who know they need to start right away, what's the most important first step?David Kirkdorffer (30:59.392)First, learn how these systems work. You don't need deep technical knowledge, but understand the impact. If you're in a specific lane—SEO, content, web—still learn the bigger picture so your choices align with the new reality. Then triage: audit where you'll work first based on team size and resources.Gather the whole team—web, SEO, content, PR, demand gen—so everyone hears one story and understands how their actions affect each other. Agencies should know what they can and can't do and set expectations. After learning and auditing, remember this is ongoing, like SEO has always been.Finally, be present where your customers go. Different LLMs rely on different data sources—Reddit, Wikipedia, licensed content—and those arrangements change. Go where your customers already spend time.Kerry Curran, RBMA (36:06.339)Excellent. For folks who want to learn more or bring you in to help their team, how can they reach you?David Kirkdorffer (36:42.518)The best way is through LinkedIn. Search “David Kirkdorffer.” My email is firstname.lastname@gmail.com. I post about these topics and provide training classes—very hands-on and tactical, covering tabs, accordions, LLMS text, schema and chunkability, and more. Feel free to DM or email me.Kerry Curran, RBMA (37:52.238)Perfect. I'll include those links in the show notes. David, thank you so much for sharing your expertise with us today.David Kirkdorffer (38:05.046)Thank you, Kerry, and thank you to the audience. If you've made it this far, that's a compliment. I appreciate it and enjoyed the conversation.Kerry Curran, RBMA (38:15.050)Excellent—thanks!Huge thanks to David Kirkdorffer for joining me on the show. If your brand isn't showing up in AI-generated answers, this conversation is your roadmap to change that. From content structure to message consistency to offsite visibility, David laid out actionable ways to adapt your SEO strategy to this new era of AI-driven buyer behavior. If you found this valuable, share it with your team and hit subscribe so you don't miss the next episode.And for more strategic insights on revenue growth through marketing, head to revenuebasedmarketing.com or follow me, Kerry Curran, on LinkedIn today. Flat or slowing revenue? Let's fix that—fast.Revenue Boost: A Marketing Podcast delivers the proven plays, sharp insights, and “steal-this-today” tactics that high-growth teams swear by.Follow / Subscribe on Apple, Spotify, and YouTubeTap ⭐⭐⭐⭐⭐ if the insights move your metrics—every rating fuels more game-changing episodes

Christine Short and Steve Dickens preview Box (BOX) earnings. Steve is watching for where Box fits into the “agentic workflow” and how it integrates an AI LLM. Christine notes a big drop in paying subscribers from its competitor Dropbox (DBX), which could be an individual problem or a sector-wide trend.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – / schwabnetwork Follow us on Facebook – / schwabnetwork Follow us on LinkedIn - / schwab-network About Schwab Network - https://schwabnetwork.com/about

I'm thrilled to have Dr. Bushra Anjum, join us for today's episode! She is the head of Data Science and AI/LLM subject matter expert at the EdTech startup NoRedInk. With a passion for innovation in adaptive online curriculum tools, Dr. Anjum leads a talented team dedicated to enhancing students' writing and critical thinking skills.Join us as we dive into her impressive journey and explore her pivotal role as Co-chair of the Association for Computing Machinery's Women in Computing Council (ACM-W). Dr. Anjum will share insights on ACM-W's mission to increase representation and inclusion in STEM, the importance of mentorship for women in tech, and her key priorities in advancing initiatives for women in computing.We'll also discuss practical steps for students and early-career professionals looking to break into the tech industry, and how aspiring members can get involved with ACM-W. Plus, we'll learn about the practices Dr. Anjum has implemented to promote equity in the hiring process for her Data Department.Don't miss this inspiring conversation filled with valuable advice and actionable insights for anyone interested in the tech field!✉️ Connect with Dr. Anjum on LinkedIn: https://www.linkedin.com/in/bushraanjum/

Stephen Wolfram answers questions from his viewers about the future of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qaQuestions include: In the spirit of Valentine's Day, what is the future of bionic hearts? Would this be a way to make humans more efficient? - How would you think about a world in which all of the work is done by robots and AI? - Architects using computerized/AI tools will result in less demand for architects overall, thus less people getting to do architecture. - Do you think the current methods of training and using AI/LLM are here to stay for a while, or is there a real possibility of an alternative machine learning approach appearing and being superior and more efficient? - What would you think about spiking neural nets with a new non-differentiable learning algorithm? Is it the path to smarter AI? - ​​I read from an expert that correcting the errors in a later prompt results in more errors. It's better to go back to the original prompt. - Do you or your team actively work on the alignment issues with AI and are you worried about the next 10 years with regard to that? - Do you see a danger in the trend toward anthropomorphic AI and providing AI systems with human-like attributes? - I wonder what will happen when future AI models are trained on material that shows them the actual results of their past actions. - What are some near- and medium-term breakthroughs that could potentially make the creator a trillionaire? Off the top of my head, fusion power, far more efficient batteries or novel propulsion systems.

This is a free preview of a paid episode. To hear more, visit www.insurgentspod.comKylie Robison of The Verge joins us to talk about DeepSeek, the new AI LLM that, its developers claim, was built for just a fraction of the cost compared to its US-based competitors. We analyze those claims, talk about the competing interests trying to “win” the AI race, examine the harm and risks associated with rapid and unchecked AI development and, …

Ken and Seth return for 2025 to review the accuracy of their predictions from 2024 and make a few new ones for this new year. Some hits and misses for last year, but overall the generic predictions for both AI/LLM growth and software supply chain security were accurate. However, they were wrong in their assumptions around LLM creation and training. For 2025, predictions on AI billing models, software supply chain attacks, OWASP Top 10 2025, and more.

In this milestone 200th episode, Sam Kamani interviews August from Paxful, a decade-old platform that's empowering over 14 million users through peer-to-peer payments. They discuss how Paxful is solving financial inclusion, enabling trust with escrow services, and offering 500+ on-ramping methods globally. August also shares his views on market trends, the rise of Solana, and what the future holds for peer-to-peer crypto ecosystems. Key Timestamps [00:00:00] Introduction: Sam introduces August from Paxful, a pioneer in peer-to-peer payments. [00:01:00] August's Journey: From traditional finance to crypto, MakerDAO, and joining Paxful's leadership team. [00:05:00] What is Paxful?: Enabling trust-based peer-to-peer payments with escrow for financial inclusion. [00:08:00] How Paxful Works: Combining 500+ payment methods with escrow to facilitate seamless transactions. [00:13:00] User Stats: Over 14 million unique signups and 1M+ active funded accounts globally. [00:15:00] Growth Strategies: SEO, referral programs, and grassroots outreach to expand Paxful's reach. [00:18:00] Future Vision: Building Paxful into the “Swiss army knife” for global crypto and financial services. [00:24:00] Trends in Crypto: The rise of USDT, Bitcoin dominance, and Solana's vibrant ecosystem. [00:30:00] Challenges Ahead: Regulation and adopting AI/LLM technologies to enhance user experience. [00:36:00] What's Next?: Paxful's roadmap to expand its product suite and enter new markets. Connect https://paxful.com/ https://www.linkedin.com/company/paxful-inc https://www.linkedin.com/in/augustwidmer/ https://twitter.com/paxful https://x.com/AugForceOne Disclaimer Nothing mentioned in this podcast is investment advice and please do your own research. Finally, it would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Be a guest on the podcast or contact us - https://www.web3pod.xyz/

It's not a reach to say that we're currently in a time of uncertainty, across technology, economic and political spectrums. But historically, times of uncertainty have often led to unexpected creativity. SHOW: 873SHOW TRANSCRIPT: The Cloudcast #873 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS"SHOW NOTES:STUFF THAT FEELS UNCERTAIN OR FRAGMENTED RIGHT NOWTransition of US political parties (regulation, leadership, reaction to the unknown, friend or foe of Silicon Valley)Stock market is somewhat bullish, but credit markets aren't alignedSocial media seems more fragmented (good & bad), so what does this do to information flows, learning, discussions, etc.Speculation is that AI LLM models are starting to plateauCloud providers aren't really talking about anything but AIVCs seem to be excited about the potential of acquisitions again, but who?Netflix can't seem to figure out streaming live TV, at least at scale - but Amazon can?FEEDBACK?Email: show at the cloudcast dot netTwitter: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

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Today Jason is joined by Spectral's Co-Founder & CEO, Sishir Varghese to discuss the Onchain Agent Economy and the future of machine intelligence networks aiding autonomous onchain agents . In this episode they discuss: AI/LLM integration abstractions Revenue-generating agents Competitive market dynamics: The Agent App Store Agent transparency A live Spectral demo! Agent-to-agent communication And much more! Episode article links: https://vitalik.eth.limo/general/2024/01/30/cryptoai.html https://goodalexander.com/posts/agenticprotocols/ https://www.spectrallabs.xyz/whitepaper Host: Jason Choi @mrjasonchoi . Not financial advice. -- Tangent is a private holdings company managing personal assets and is not a licensed investment advisor nor does it manage or accept any external capital. Nothing discussed is a solicitation for investment and is for entertainment purposes only. -- Timestamps: (00:00) Introduction (05:17) On-chain agents (11:01) AI/LLM integration abstractions (14:28) Vitalik's take on AI x Crypto (17:58) Spectral's infra-chain (20:49) Revenue-generating agents (23:21) Competitive market dynamics: agent App Store (26:28) Agent verification (29:09) Agent transparency (32:36) Spectral Demo (37:42) Agent moats (40:04) Security parameters (41:46) Agents/protocols (43:36) Agent-to-agent communication (45:30) Outro -- Partner message: Aptos is the next-generation Layer 1 blockchain designed to enhance scalability, security, and reliability for decentralized applications. With industry-leading performance, internet-grade UX, 100X lower gas fees than comparable chains, and a thriving ecosystem - Aptos is the platform of choice for both builders and users.  Find out more at https://aptosfoundation.org/ -- Twitter accounts: Jason Choi's Twitter: https://twitter.com/mrjasonchoi Sishir Varghese's Twitter: https://x.com/__sishir Spectral's Twitter: https://x.com/Spectral_Labs Spectral's website: https://www.spectrallabs.xyz/ Blockcrunch Twitter: https://twitter.com/theBlockcrunch -- Blockcrunch VIP:  https://blockcrunch.substack.com/ -- Disclaimer: The Blockcrunch Podcast (“Blockcrunch”) is an educational resource intended for informational purposes only. Blockcrunch produces a weekly podcast and newsletter that routinely covers projects in Web 3 and may discuss assets that the host or its guests have financial exposure to. Views held by Blockcrunch's guests are their own. None of Blockcrunch, its registered entity or any of its affiliated personnel are licensed to provide any type of financial advice, and nothing on Blockcrunch's podcast, newsletter, website and social media should be construed as financial advice. Blockcrunch also receives compensation from its sponsor; sponsorship messages do not constitute financial advice or endorsement.   Full disclaimer:  https://blockcrunch.substack.com/about

Stephen Wolfram answers questions from his viewers about the future of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Continuing the dinosaur theme, is it possible biology can repeat patterns of evolution? Is it possible for dinosaur-like creatures to reappear? - Why is it as technology advances, it goes through phases of bigger to smaller to bigger? I've seen this with phones, computers, TVs, cars, etc. What does this say for the future of technology? - ​​What would be the future of the personal computing paradigm? Would we see more remote cloud-like computing and storage in the future, essentially making personal computing devices obsolete? - The current AI/LLM models aren't good at the mathematical and statistical computational methods. What areas do you think should be focused on in computer science and mathematics to teach these models to be better at computation and assist researchers and scientists? - What do you think of the amount of data that gets processed or code that is run in terms of bytes vs. bytes that are used for storage in the world? - What exactly is 5G? How is it different from 4G or 3G? - Nowadays, instead of getting higher resolution, we can get higher color range and frame rate. - If AI is being used for autonomous vehicles, then presumably technology could improve to the level where vehicles could "see around corners" by different vehicles communicating with each other, buildings, etc.–so the video stream is from multiple perspectives? - Taking the concept further, could vehicles on a motorway and those joining seamlessly interweave at high speeds safely and traffic be diverted automatically in real time to ensure that there are no blockages etc.? - Turns out that as computer displays get better, our sensor limitations turn out to be higher than we used to think. - I recall reading something saying that 5G and low-latency connectivity would be important for self-driving cars. That seems somewhat unlikely to be an important component of self-driving now. - What's the future of fiber optics? - In the future, will cell towers be more advanced to prevent dead zones?