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Application volumes are continuing to rise, but finding quality hires remains a challenge. The usual suspects that tend to get the blame are candidates using AI, economic uncertainty, and a continuing decline in job board effectiveness. However, research suggests a more fundamental issue that many organizations overlook. The words in job descriptions matter more than most teams realize. Non-inclusive language is actually a key factor that stops many qualified candidates from applying. At the same time, regulations around pay transparency and anti-discrimination are proliferating across the US and EU, creating complex compliance requirements for job ads that vary by market. Many employers are also outsourcing their job ad creation to generic LLMs that have more potential to amplify bias than they do to eliminate it. So, how should employers utilize technology to ensure inclusivity, compliance, and a high-quality response from their advertising My guest this week is Pil Byriel, CEO and co-founder of Lyser. In our conversation, Pil shares research on how language shapes candidate behavior, why LLM reinforces bias, and the growing complexity of job ad compliance around the world In the interview, we discuss: The impact of language on applications from qualified candidates The human-led research behind inclusive communication Why generic AI LLMs amplify stereotypes and bias Compliance challenges across global markets What actually drives job ad performance Why structure, clarity, and transparency matter Building data-driven recruitment communication Follow this podcast on Apple Podcasts. Follow this podcast on Spotify.
Today on the show, we have Kevin White, Head of Marketing at Scrunch AI, a platform helping brands stay discoverable in the era of AI-powered search. Kevin brings experience from leading go-to-market and marketing teams at Segment, Retool, and Common Room, as well as advising fast-growing startups like Ashby, Deepnote, and Gretel.ai. In this episode, we explore how the rise of answer engines like ChatGPT and Perplexity is reshaping how people find information online—and what it means for marketers. We discuss how Scrunch helps brands optimize their sites for large language models (LLMs), why bots are becoming the new audience, and how AI-driven search is redefining visibility and discovery. We also delve into lessons from Segment and Retool on balancing self-serve and enterprise growth, how activation-first onboarding drives retention, and why doing “white-glove at scale” can triple user success. We wrap up by unpacking Kevin's biggest learnings on churn and growth—from Reforge's “don't fill a leaky bucket” principle to why something as simple as naming conventions can make or break a company's ability to scale.Churn FM is sponsored by Vitally, the all-in-one Customer Success Platform.
When trying to grow your property management business, have you ever thought to yourself, "Man, it would be great if I just had more leads?" In this episode of the #DoorGrowShow, property management growth experts Jason and Sarah Hull discuss the Leads Myth and how "just having more leads" will not actually help you grow your business. You'll Learn [02:06] The Myth of Needing More Leads [11:39] Leaks in Your Sales Pipeline [22:41] The Future of SEO with AI Quotables "Why do we call it the leads myth? Well, the myth is this lie that we believe that you just need more leads. And the assumption in that is that all leads are the same." "The more clarity you have, the less wrong stuff you're going to be doing." "Not all clients are equal, right? Which means not all leads you get are equal. You need to qualify them." Resources DoorGrow and Scale Mastermind DoorGrow Academy DoorGrow on YouTube DoorGrowClub DoorGrowLive Transcript Jason Hull (00:00) Most of the industry is trapped in a cycle of suck. This is why most property managers suck in most markets. Maybe even you that's listening. We are Jason and Sarah Hull, the owners of DoorGrow, the world's leading and most comprehensive coaching and consulting firm for long-term residential property management entrepreneurs. For over a decade and a half, we have brought innovative strategies and optimization to the property management industry. We help people grow their property management businesses quickly. And our mission is to transform property management business owners and their businesses. We want to transform the industry, eliminate the BS, build awareness, change perception, expand the market, and help the best property management entrepreneurs win. Now let's get into the show. All right. So today we're going to be chatting a little bit about the leads myth that a lot of people believe. So if you have ever thought to yourself, I just need more leads. If I just had more leads, everything else would be great in my business. What do you have to say about that? Well, I think that is not the case. Okay. It's definitely not the case. And I also think almost kind of be careful what you ask for a little bit. getting a whole bunch of leads was never really the best. strategy anyway, unless you have people who are just picking up the phone and calling you and saying hey, I Would love for you to just manage my property. I don't have any questions. Here's my money. I just had a contract Those are leads I want but cold leads that are Not ready to go that need to be warmed up that have a bajillion questions That might not even understand why they want to work with you Specifically, yeah, I'm just not interested in those leads. And the other thing I think we need to discuss on this episode specifically is the changes that we're seeing because of AI. So AI is really great and also it's changing things very rapidly and leads and SEO that's very effective by this too. Okay. So. Let's get into this. So a lot of people believe they just need more leads. And the danger in that is if you really just think you need more leads, you're going to go out to the marketplace and talk to marketers and they're going to go, cool, I'll give you leads. And they will sell you leads basically. So why do we call it the leads myth? Well, the myth is this lie that we believe that you just need more leads. And the assumption in that is that all leads are the same. And they're not, they're not even remotely the same. So there's a couple of different frameworks that we usually talk about to kind of destroy the leads myth. One is the four Ds to revenue. Another is the cycle of suck we talk about and how people get stuck in growth. We talk sometimes about the pipeline leaks that you have in your pipeline. And we talk about the myth of SEO or internet marketing. And then we often talk about any others warm versus cold leads and then David versus Goliath. Okay. So we can tackle these all really quickly and go through each of these and maybe some other things will pop up as we go. Cool. Let's talk about all of that and then we'll talk about why AI has changed all of, really all of those things. Okay. That'll be in conjunction with SEO. All right, so let's go through these. And so for those following along, if you stack all these concepts, each one compounds your speed of growth. They're all related. And so these are frameworks that I love to share with clients to help them understand so that they don't make the mistake of doing the wrong stuff. The more clarity you have, the less wrong stuff you're going to be doing. The less you're going to be experimenting, the less you're going to be wasting time. And if you really wanna collapse time, the easiest hack is reach out to us and we can help you with all of this. We've been doing this for over a decade and a half. We have had hundreds of guinea pigs to figure this all out and we have over 100. case studies and testimonials more than anyone else in the industry. All right. Let's get into this. let's talk about the four D's to revenue. So these are four numbers when multiplied equal the gross revenue in your business. And I sometimes call them the four doors to revenue. And I showed four doors with a little multiplication X next to each of them equals your money. Right? So not all leads are equal. So the, these D's are, if you want to write them down, they each start with a D. It is Deals, doors, duration, and dollars. Okay? So the first is like how many deals is this client going to bring you? Not all clients are equal, right? Which means not all leads you get are equal. You need to qualify them. And how many doors are they bringing to the table? Or how many doors per deal are they bringing? And then the third D is duration. How long are they going to stick around or be involved in property management? is are they an accidental investor that's going to stick around for maybe a year, or are they in the buy and hold game and they'll be around for 10? And then the last D is revenue or is dollars. And so are they a cheapo? Are they a premium buyer? Where do they kind of fit? Or are they somewhere in the middle, like the normals as I call them? So we've got these four Ds. So let's play a quick example. Let's take the accidental investor. They couldn't sell their property. They wanna get it rented out. How does this play out in the 4Ds? done one deal. They didn't mean to do a deal, but they did. And it's usually just one door. Maybe sometimes they have two, but very often we just see one door and they're not looking to... to do more deals because as soon as the market spikes and the market is hot, they're going to bail. They're going to sell, which means the duration is questionable. Let's say it's like one year, like if they can just get it rented. but it might be a few months because if the market spikes three months from now, they're probably going to dump that property pretty quick. And then. than the dollars, they're not your premium buyers. They're not looking to do a lot of improvements. They're not looking to spend a lot of money. They're the people who, they have this property, they aren't quite sure what to do with it. They figure, let's just see if I can get it rented. They want it well taken care of, but they're not generally looking to spend a lot of money or invest a lot of money in either the property or maintenance or repairs or improvements or a property manager. So they're just trying to... Do what they need to do. It's like the bare minimum in order to get a tenant. All right, so one, one, one, right? Like one deal, one door, one year duration, for example, if this is worst case scenario and you sign a one year agreement with them and they're a cheapo, right? Now let's take a really great scenario. What would be maybe an opposite scenario or a really great opportunity? Like my, I will say my second largest client. He had 42 doors I think was the right answer but I was looking to buy more. So when I took him on he had 42 by the time I sold the business he had 60 something. So he was always doing multiple deals. Yeah. The doors that he had came out of multiple deals. So since he did multiple deals he also had multiple doors. was consistently looking to grow. He didn't want to just stop, you know, at a certain point he was always looking. He also was a buy and hold investor. He wasn't trying to buy these things and then wait, you know, until the market spiked and then try to sell them and make a profit. He wasn't up for the long term. And he was not a cheapo. He wasn't trying to cut corners. He wasn't trying to cut costs. You he wanted to work with. a property manager, wanted to take care of the properties and make sure that they were being maintained properly. Yeah. Okay. So that's a great example that previous client that you had. So let's just say like on each of these fees, we use tens instead of ones, right? Like let's say they do 10 deals over the life of being with you. They've got 10 doors. Maybe sometimes it's 10 doors per deal if they're doing small multis or something like this, right? And then you've got a 10 year buy and hold duration. In this hypothetical example that I just threw out, it would be 10 times 10 times 10. This would be over a thousand times greater lifetime value than that accidental investor in our previous hypothetical. Does that make sense? So are these even remotely equal? No, not even remotely equal. Should you then spend the same amount of time trying to cultivate both of those type of leads? Probably not. Would you spend the same amount of time following up or giving them attention? Probably not. And the great investor clients probably are easier to deal with, less emotional, have a much higher margin and operational cost is lower, right? And so there's a lot of benefits. so this is, we're just talking about the revenue piece, but when we look at the cost side of things as well, everybody knows having a really bad owner that's really needy and difficult and emotional about the property. can be a big headache and a big challenge and you may be losing money on some of those doors. So, four D's to revenue, that's one concept. One quick thing I wanna add to that is where do you think these owners hang out? So, if you've got an accidental landlord and they are looking for a property manager, where might that lead come from? Versus where might the lead of a client that has 42 doors come from? There's a lot higher probability that an online lead is going to be an accidental landlord. It's not impossible to get an online lead that has 42 doors. It's just probably not your norm because the ones that have 42 doors, they aren't really dabbling. They aren't going, oh, geez, I wonder if I should get a property manager to maybe help me with these. They are just a little bit more savvy. A lot of times those aren't going to be the leads that you're getting if you're buying leads. Although those are the leads that you want, it's not going to be the norm that you get. All right, so we're 10 minutes into this. We're going to crank through some of the rest of these. So cycle of suck. Cycle of suck, real simple. If you take on any client, it leads to you having some bad clients. So if you take on bad clients, that leads to you having bad properties, which leads to having bad. Residents or tenants which leads to having a bad reputation or reviews which leads to you attracting more bad clients. So not all leads are good. You don't want to take on every client and you definitely don't want to attract or get more bad leads. And so this is a framework that if you understand you can reverse it and focus on a cycle of success where you're picky about the owners you take on, you're picky about the properties you take on, you're picky about the tenants which everybody tries to do anyway. but those first two steps are supremely important. And then you're going to have a methodology for getting more positive reviews. These are things we help our clients with. And so then you create a cycle of success. Most of the industry is trapped in a cycle of suck. This is why most property managers suck in most markets. Maybe even you that's listening. We want you to get out of the cycle of suck. All right, let's talk about the pipeline leaks. Okay. So usually if I were drawing, I would draw a spigot or a faucet or whatever you attach a hose to, and then I would draw a hose, and then I would draw a little plant or tree that you're trying to grow at the end of the yard that this hose is trying to get water to. Most of you listening think, I just need more leads. This is where the lead Smith becomes really obvious, trying to turn on that faucet even more. I just need more water flowing through the hose. That would make sense, that would be true unless there's a problem with the hose, right? Like the hose has some leaks. And if the hose has some major holes in it, there's not going to be a lot coming out the other end. Sometimes very little at all. And so it's not about how many leads you're getting, sometimes it's just how good is your pipeline? How tight is your product? And so we need to make sure that we get those leaks shored up. And we'll just mention what they are real quick, but. One of the earliest ones that affects you is just awareness. It's going to be your perception and reputation online. It's going to be your website. It's going to be your branding. So they can tell that you are in this industry and that it's clear that that's your focus and it's not real estate or something else. And what else? Your culture and purpose. This is the actual product that you sell. So that is another one. And there are two more. Pricing. Pricing, which everybody's trying to price the same way, 10 % or worse, pure percentage, or they're doing flat fee. We have a different innovative pricing model. If you're curious about that, set up a call with our team. We can tell you about it. That allows you to close more deals more easily at a higher price point. And the last is the pitch, right? Selling. And so if you can dial in each of these leaks, what we've noticed over the years is we can double a company's close rate without changing the amount of leads or lead sources that they're getting currently if we can get those things dialed in. And that's significant. Maybe you don't need more leads. Maybe you just need less leakage in your pipeline. Cool. All right, the next one, you had mentioned warm versus cold leads. Do you wanna explain the difference? Yeah, we can talk about warm versus cold. So when I had my property management business, Yeah. what is a cold lead? So cold lead is someone who really has almost zero, very little familiarity with who you are in your company and your brand and what you do. They don't. they should work with you. That's the big thing is why they should work with you. So they don't know you, trust you or like you. That's a cold lead. And a warm lead. Warm lead would be something like a referral or some sort of recommendation. hey, Sarah is the best, I work with her and you should too. Now they're coming in already feeling like, somebody that I know that I trust recommended this person, so therefore I should also trust this person. So those obviously have a much different close rate. And there are things that you can do to increase your close rate or to warm up deals, of course. But if you're spending all of your time trying to close a bunch of cold leads, which generally is going to be what happens when you're purchasing leads, you really don't get to buy warm leads. Right. They're all cold. I mean, that would be great if you could, but when you're buying leads, you're usually buying a lead that is very cold. They don't know you at all. And oftentimes that same lead is being sold to multiple different companies. There's a lot of blood in the water there. So warm leads versus cold leads, the close rate on warm leads will be really high, like 90 % or higher. Cold leads, like the opposite, 10 % or worse. And so I would rather a client get five warm leads and maybe close four of them than 10 cold leads and maybe get one. The hidden pain point or secret with warm versus cold lead generation. or cold lead strategies is time. Cold leads take a massive amount of time because you have to nurture them and warm them up and build the trust and create the relationship. And even after all of that, and all of sudden done, the conversion rate's really low. So all of you know how high the close rate is if you get a really great word of mouth referral. We love those, right? That's a warm lead. So we have strategies and methods that we focus on with clients to increase the warm leads. while avoiding and doing cold lead advertising and avoiding worrying about cold leads. Once you start getting some growth engines installed for your business that give you warm leads, you're not going to want the cold leads. They feel like garbage in comparison, and you're not going to have time for them. And you're not going to wanna waste time on those because those are often the worst owners. All right. What I would say is as far as getting leads in, if you give me three warm leads, I will take three warm leads over even 100 cold leads. Sure. don't, I don't, I'm not really interested because even if I close, let's say two out of the three warm leads, that's great. What's the close rate on 100 cold leads? If it's about 10%, you might close 10. And some of you might be going, Sarah, 10 is better than two. Yeah, you're right. But how much work did it take for me to close the two versus how much work? did it take for me to close the 10? I would rather close two very easy warmed up leads because I can do that again and again and again. So in the same amount of time, I can close way more warm leads than I can cold leads. So I would rather take three warm leads than a hundred cold leads any day of the week. We have a sponsor for this episode. Many of you tell me that maintenance is probably the least enjoyable part of being a property manager and definitely the most time consuming. But what if you could cut that workload by up to 85 %? That's exactly what Vendero has achieved. They've leveraged cutting edge AI technology to handle nearly all your maintenance tasks from initiating work orders and troubleshooting to coordinating with vendors and reporting. This AI doesn't just automate, it becomes your ideal employee, learning your preferences and executing tasks flawlessly, never needing a day off and never quitting. This frees you up to focus on the critical tasks that really move the needle for your business, whether that's refining operations, expanding your portfolio, or even just taking a well deserved break. Over half of the room last year at DoorGroad Live, our conference signed up with Vendero right there. And then a year later, they're not just satisfied, they're raving about how Vendero has transformed their business, don't let maintenance drag you down. Step up your property management game with Vendoroo. Visit Vendoroo.ai slash door grow today and make this the last maintenance hire you'll ever need. All right. I thought it was a good time because it was a good time. Waste of time and I don't like to waste time and maintenance coordination can be a huge waste of time. Yes. All right. Let's talk about David versus Goliath. So I'll give you an example. We've got a client. that has, so this is dumb David versus smart David, right? The story of David and Goliath, if you're not familiar with the Bible. David goes to fight Goliath. These two warring nations send out their best person and David decides he is not going to wear the armor, the sword, the shield, all the heavy stuff. He's just bringing out his slingshot. He's got his sling, he's got some rock and he goes out to fight Goliath and he's like, I don't need all that stuff. What most property managers do is David basically brought a superior technology. He brought a gun to a sword fight and he was good at this. He trusted himself. He had skill. He had a better tech to beat this giant. He flung the rock right into the guy's head. I had knocked him unconscious or killed him, I don't know. And then he chopped the guy's head off with his own sword. Right. And so that's the story of David and Goliath. So let's talk about the dumb version of David. Like if David wasn't smart. And he said, I'm going to do all the same stuff. I'm going to use the sword of SEO and the shield of pay per click and the helmet of content marketing and the breastplate of social media marketing. And I'm going to do all the same stuff, digital marketing that all the other big companies are doing that are spending two to $3,000 a month or greater. I'm going to go compete with them as a small startup or a small pro. two to 400 unit property management business and try and compete with these big companies that have thousands of doors. One of our clients, as an example, came to us has 6,000 doors. They were spending $30,000 a month doing these strategies to try to grow and it wasn't even working for them. So why would you go and do what the big guys are doing and lose the battle with them and it's not even working for them, right? So that's the idea of David and Goliath. Don't go do what the big guys are doing, find a better way to compete, especially if you're smaller than them. You don't wanna try to outspend them, because that's not going to be possible. right, myth of SEO. All right, and we'll talk a little bit about the future and AI, all right, to wrap things up. So, all of you can go check this out for yourself. This is not me making stuff up. You can go on trends.google.com. You can go look up property management. date it, the time period, to the current time back to 2004, to the present. And you can filter by the US if you want to. What you'll see is that property management search volume, the amount of people searching for property management on Google has not increased since they started tracking data back in 2004. What has increased? The Goliaths, right? The companies spending a lot of money on digital marketing trying to do all this stuff. And so it's created a lot more competition. So this is where we get into another framework that we share, which is the blue ocean versus the red ocean. There's this small little area of the ocean that's red bloody water where all the sharks are fighting over the worst fish, which are these terrible property management business owners that are at the end of the sales cycle. Basically the crappy scraps that fell off the word of mouth table that the warm lead stuff has captured. They're what's left over. And so there's these ugly gross fish and the sharks are all fighting over the worst stuff. And there's this huge ocean full of fish in the U.S. 60 % are self-managing. There's tons of business out there. And so the myth of SEO is basically this, that in order to win the game, you need to have the top spot on Google. Not true. You don't even have to show up on Google in order to go out and be able to create business. Because there aren't really people searching for property management. It's very small. So you don't need to be found on Google. You need to go find owners because the best clients are offline and they're not looking for you and they don't like doing property management and they need you, but they're not looking for property management actively right now. And you can figure out how to go make that happen and we can teach you, right? So let's talk about the future of AI. What are we noticing? Well, I don't think it's any surprise. messed up a lot of Yeah, it's changing everything. AI is going to change everything. And if you haven't noticed it yet, just hold on because you will. It's crazy if you haven't even seen it yet. But it's it's going to flip everything you know upside down, including SEO. Yeah, including SEO. So everyone that is like, no, I don't care. I'm still going to do SEO. That's the only way to go. Like we made a video about this. specifically for this reason, but even the ones who are still clinging to SEO and you just can't let it go and you don't know that there's another way and maybe you don't believe it and you're like, no, I'm no, this is the only thing I'm going to do and I'm going to do this and that's the only way I can grow the business. That is all right and SEO is going to force you to look at that. Okay, yeah, so what we're seeing is search volume on Google is going down. There's less people using Google. More people are now going to LLMs like ChatGPT, Clod, Perplexity, Google's Gemini. So people are using tools now, sometimes within software, and they're using these tools to ask questions, to figure things out, figure out who they should use or who they should choose or what they need. And so Is it still relevant to have good reviews? Yes. Is it still relevant to maybe have some SEO stuff going? Probably, but it's certainly on the down slope and it's certainly decreasing. The game is changing. Even if you search on Google now, the AI at the top will respond to your search request anyway. And a lot of people are just reading that and not really looking at the results below. And so this is the new future. It's changing very quickly. and some are calling it AEO, some are calling it LLM, SEO, there's all these different phrases that are coming out. If you want to do a quick experiment, open up one of these LLMs like ChatGBT. Don't be in your own. It's a large language model. It's basically all these different AI chat tools. So go into ChatGBT. Everybody should be familiar with that by now if you're not. and go to ChatGPT open that up, but make sure you're not logged in or you use a different account and just, or say don't use any of my previous data or open a private window and say don't use any of my previous information or data and say who's the best property manager or what property manager should I choose in X market, right? And see if it comes up. See if your business comes up and see what shows up. And so this is... how people are kind of doing some of their research, but all the stuff we just talked about still applies. Don't think your whole goal needs to be LLM SEO, where you need to start getting these chat tools to tell people. Why? Because most people are not looking for a property manager. They're not looking. They are not trying to find you. That's the mistake most people make. The majority of people that are self-managing, the potential business, are not looking for a property manager. It's really rare that somebody has a property manager that they're looking actively for a new one unless they've really done a bad job or stolen money or done something really obvious. The people that need your services are not looking for you. You need to be looking for them. And so this is where you can skip all of the cold lead marketing. You don't need to spend money on SEO or AI SEO or Google Ads or pay-per-click or any of these marketing agencies, you don't need to spend any money and you can actually grow faster if you use our strategies and it costs you nothing to do the strategies that we give you. It costs time and action, but it actually takes less time because warm leads and focusing on more effective strategies give you a much greater result in less time. So less time, less money, more results. And that's why we call it the Leadsmith. A lot of people think I just need leads. Cool. there's better ways. Not all leads are equal and we can help you out. Cool. Anything else we should add in wrapping up? I don't think so. I think we covered everything. Okay. I think we got it. So cool. Well, if you are wanting to figure out how do I grow this business? How do I finally get out of the rut that I've been in? How do I scale this? Maybe adding more doors is creating you grief and pain and you want freedom from your business. These are the things we help clients with. We'll help you figure out how to grow dramatically faster and we'll help you figure out how to make your business scalable while getting you out of the day to day and getting you to exit the business in various ways so that you get more freedom. So if you felt stuck or stagnant, you want to take it to the next level, reach out to us at doorgrow.com. Also join our free Facebook community just for property management business owners at doorgrowclub.com if you would like to get the best ideas in property management, join our newsletter at where? doorgrow.com/subscribe And if you found this even a little bit helpful, don't forget to subscribe and leave us a review. We'd really appreciate it. And until next time, remember the slowest path to growth is to do it alone. So let's grow together. Bye everyone.
Financial Intelligence. Nikola Jakic from Compass App AI combines your financial data with context to give you confident decision-making.Summary of PodcastIntroductions and backgroundKevin and Graham introduce themselves and welcome their guest Nikola Jakic. Nikola is the founder of a financial AI tool called Compass AI. He provides background on how he came up with the idea for Compass AI based on his experience as a CEO of a software company. Then he discusses the limitations he faced in managing the financial aspects of the business.Overview of Compass AINikola explains that Compass AI combines a company's financial data with business context. Doing this provides insights and recommendations to help founders and fractional CFOs make better decisions. The tool can connect to accounting systems like Xero and QuickBooks, categorise transactions, generate forecasts, and allow users to interact with the data through natural language prompts.Target market and positioningKevin and Graham discuss how Compass AI is positioned to serve small and medium-sized businesses. This as opposed to targeting the enterprise market that many financial software tools focus on. Nikola shares that his initial target audience was founders, but he has also found interest from fractional CFOs who can use the tool to provide more value to their clients.Competitive landscape and growth strategyThe group explores Compass AI's competitive landscape, noting that while there are tools targeting CFOs and larger enterprises. He explains there is less focus on the small business market that Nikola is pursuing. They discuss Nikola's strategy of starting with founders and growing with them as their businesses scale, rather than chasing the enterprise market directly.Recap and next stepsGraham and Kevin provide a positive recap of the discussion and encourage Nikola to continue focusing on his target market and leveraging the natural, conversational style he demonstrated during the podcast. They express enthusiasm for the product and suggest ways Nikola could use snippets of the conversation for marketing purposes.The Next 100 Days Podcast Co-HostsGraham ArrowsmithGraham founded Finely Fettled ten years ago to help business owners and marketers market to affluent and high-net-worth customers. He's the founder of MicroYES, a Partner for MeclabsAI, where he introduces AI Agents that you can talk to, that increase engagement, dwell time, leads and conversions. Now, Graham is offering Answer Engine Optimisation that gets you ready to be found by LLM search.Kevin ApplebyKevin specialises in finance transformation and implementing business change. He's the COO of GrowCFO, which provides both community and CPD-accredited training designed to grow the next generation of finance leaders. You can find Kevin on LinkedIn and at kevinappleby.com
Send us a text- On-Demand Programme Link - https://mailchi.mp/bb2a7b851246/kairos-centre"Narcissism because of Sex Addiction - Yuk! That's not me".Many clients initially (but silently and violently) object to any suggestion that there is Narcissism at work. I am never suggesting they have NPD (Narcissist Personality Disorder), but that they WILL have traits from Narcissism.Here is one definition of Narcissism which I use: "Narcissism is the way we conceptualise how we will look after ourselves. In its pathological form, it refers to people who seem incapable of acknowledging or taking sufficient account of the reality of other people and their separate existence. Narcissistic Personality Disorder describes those who exemplify an extreme form of this characteristic. The primary purpose of Narcissism is to compensate for experience, usually in early childhood, when ordinary expectable needs were not met adequately. The Narcissist denies dependence on others and denies even that others exist except as players in the Narcissist's drama. Other people are required to meet the narcissist's needs for recognition and value, but without relationship being reciprocated.The narcissist gives nothing, but demands others give everything. Therefore the original horrific experience of unmet need and the shame and vulnerability that goes with it, is denied and defended against.Traits include being the centre of attention; little interest in others; craves recognition and praise. They are performers and want others to keep on clapping and not stop; controls and dominates interaction with others; has to be right; cannot admit to ever being wrong and never apologises; insists on things being done their way; always makes the choices and decisions. Reliance on another is not acknowledged"."Gary, let me show you evidence that I do not seek attention, take little interest in others, don't crave recognition or attention, let alone a performer and want claps. How dare you...."Until I unfold their behaviours and leave them with 'food for thought' to reflect upon; including going back to my definition of Sex Addiction to see 'the function which the addiction serves'.Get some help from The Kairos Centre. See what you cannot see. Begin to change that which you begin to better understand.Help someone: https://igg.me/at/ThekairosCentreHelp is here for you: bit.ly/pornaddictionhelpGary McFarlane (BA, LLM, Dip, Certs), Accredited EMDR Practitioner.Key words: sex addiction, addicted, partner, porn addiction, recovery, sex drive, therapy, sex therapy, podcast, relationships, relationship counseling, relationship advice, addiction, couples, couples therapy, sex therapy, emdr, love addiction, behavior, psychology, codependency, sex life, neuroscience, sex ed, sober, sobriety, sexual dysfunction, relationship issues, sex coach, sexual, trauma, ptsd, sex science, The sex porn love Addiction Podcast, The Singles Partners Marrieds and Long Time Marrieds Podcast, Gary McFarlane, porn addiction, what neuroscience says, neuroscience, young adults, sex, sex addict, porn, recovery, porn addiction issue, porn addiction in teens, sex addiction in teens, sex hormones, hormones,Support the show
Dans ce 139 ème épisode, je vous parle du rôle de CMO (chief marketing officer) qui n'a jamais été aussi stratégique ni aussi complexe. Aujourd'hui, les directeurs marketing sont à un tournant : ils doivent à la fois piloter la croissance, maîtriser l'IA, et repenser la créativité. Je vous partage l'analyse de Mc Kinsey sur le rôle du CMO avec l'arrivée des outils d'IA générative.Une fonction sous pression mais essentielleLes CMOs sont au cœur de la croissance, mais peinent encore à démontrer leur impact au reste du comité de direction.Les chiffres parlent d'eux-mêmes : les budgets marketing ont chuté, et seuls 7 dirigeants sur 10 affirment comprendre la vraie valeur du marketing.Résultat ? Une tension permanente entre rigueur analytique et inspiration créative — deux leviers que les dirigeants cherchent désormais à réconcilier.L'irruption de l'agentic AI dans le marketingAprès l'expérimentation vient le déploiement : les équipes marketing explorent désormais l'agentic AI, ces systèmes autonomes capables d'agir sans intervention humaine.De la personnalisation extrême des expériences clients à la réinvention de l'achat média, ces agents transforment la façon dont les marques créent de la valeur.Mais cette révolution suscite trois réactions : l'enthousiasme, l'inquiétude (face aux transformations métiers) et la prudence (liée à la maturité des données et des infrastructures).La créativité augmentée par l'IAL'avenir de la créativité se joue dans la collaboration homme–machine.L'IA s'occupe des tâches répétitives — adaptation d'actifs, reformulation, tests A/B — pendant que les créatifs se concentrent sur l'émotion et l'audace.Dans de nombreuses entreprises, ce sont d'ailleurs les créatifs qui adoptent l'IA les plus rapidement, car elle leur redonne du temps pour penser différemment.Conclusion :D'ici 3 à 5 ans, les organisations marketing ne ressembleront plus à celles d'aujourd'hui : nouveaux rôles, nouvelles structures, nouvelles méthodes.La question n'est plus “si” mais “comment” les CMOs vont s'emparer de l'IA pour rester à la pointe de la croissance et de la créativité.Soutenez le podcast :✅ Abonnez-vous à DigitalFeeling sur LinkedIn✅ Rejoignez ma newsletter : substack.com/@elodiechenol✅ Laissez 5 ⭐ sur Apple Podcasts ou Spotify
Send us a text I denne episoden møter vi Professor Michael Alexander Riegler, Head of AI ved Simula. Vi forklarer RAG, når AI-agenter gir verdi, og hvordan LLM-er bør kvalitetssikres i offentlig sektor. Riegler deler innsikt fra helse og ansvarlig KI. Programledere: Jens Christian Bang og Dag Rustad. Hva er RAG – når gir det verdi, og hvilke arkitekturvalg finnesFra LLM til KI-agenter – hva skiller verktøy, assistenter og autonome systemerVerktøykasse for å bygge agenter – dataflytEgen LLM vs. åpen kildekode vs. proprietær – kost/nytte og driftHvem er Simula – rolle, forskning og samarbeidLLM i offentlig sektor – behovet for et nasjonalt kvalitetssikringsregimeDigitaliseringspådden lages av Already On og CW.no. Besøk oss på digitaliseringspodden.alreadyon.com. Du finner Digitaliseringspådden på alle plattformer – lytt via Spotify, Apple Podcasts eller YouTube Podcasts.
Hey, this is Alex! We're finally so back! Tons of open source releases, OpenAI updates GPT and a few breakthroughs in audio as well, makes this a very dense week! Today on the show, we covered the newly released GPT 5.1 update, a few open source releases like Terminal Bench and Project AELLA (renamed OASSAS), and Baidu's Ernie 4.5 VL that shows impressive visual understanding! Also, chatted with Paul from 11Labs and Dima Duev from the wandb SDK team, who brought us a delicious demo of LEET, our new TUI for wandb! Tons of news coverage, let's dive in
Founder-led teams can use AI to run effective, specific outreach - without sounding robotic. In this episode of 'AI Literacy for Entrepreneurs', I share a five-part "non-cringe" follow-up, a reusable variable-block system, tone/quality checks, a 5-step SOP you can paste into your AI tool, and a 48-hour challenge to make it real. Inside the episode: The 5-line follow-up that doesn't make you cringe (context → value → ask → next step → grace). A variable-block library (Persona, Pain, Proof, Offer, CTA) so AI can personalize at speed. Three 60-second QC checks to keep tone clean and human. A tiny SOP you can paste into your LLM and ship five follow-ups this week. If referrals aren't enough anymore for your business, this is your nudge to build a simple system and hit send. Want more? Agile teams move fast. Grab our 10 AI Deep Research Prompts to see how proven frameworks can unlock clarity in hours, not months. Find the prompt pack here. Join the Marketing Power Circle (MPC) Connect with Susan Diaz on LinkedIn If this helped, a quick ⭐⭐⭐⭐⭐ keeps the show discoverable for other entrepreneurs.
Smart Agency Masterclass with Jason Swenk: Podcast for Digital Marketing Agencies
Would you like access to our advanced agency training for FREE? https://www.agencymastery360.com/training How are you preparing your clients to start thinking about AI as part of their SEO strategy? Are you educating them on what they can expect now that the landscape is changing with AI optimization? As an agency, you should be starting these conversations because you can be sure your clients are already thinking about AI, even if they still don't understand its applications for how clients will get to their content. Artificial intelligence isn't just changing how people find information, it's rewriting the rules of search altogether. Today's featured guest is already running AI audits for his clients; he thinks all agency owners should be doing this. He'll unpack what AI optimization really means for agencies, marketers, and business owners who've lived and breathed SEO for decades. Vishal Mahida is the Director of Digital Marketing at E2M Solutions, where he helps over 100 agencies scale their SEO and digital marketing operations. With a 40+ person team specializing in SEO, PPC, and operations support, Vishal works directly with agencies on systems that drive measurable growth and keep them ahead of major shifts in the industry. In this episode, we'll discuss: SEO vs. AI Optimization No, SEO is not dead, so your website still matters. Preparing your agency and clients for AI search. Subscribe Apple | Spotify | iHeart Radio The Difference Between SEO and AI Optimization There's a lot of buzz around how AI has come to change and maybe even replace SEO. Vishal clarifies that AI optimization isn't replacing SEO, it's expanding it. Traditional SEO focused primarily on optimizing for Google rankings, keywords, and backlinks. The goal was to get traffic from search results. But as Vishal explains, the modern search landscape has fragmented. Users are now searching on multiple platforms including ChatGPT, Perplexity, and Claude, not just Google. This shift means brands must move beyond "ranking on Google" and focus on being visible wherever their audience searches for information. Whether someone asks ChatGPT for "the best roofers in Austin" or Google's AI mode for "running shoes under $5,000," AI systems are gathering and summarizing information across multiple sources in real time, including social platforms like Reddit, Quora, and LinkedIn. Think about it as building a multimedia visibility strategy and ensuring your brand, expertise, and answers exist across platforms that large language models (LLMs) pull from. "You're not optimizing for one search engine anymore," he says. "You're optimizing for how the internet talks about you." Why Your Website Still Matters in the AI Era Will websites become irrelevant if AI answers everything for users? According to Vishal, websites won't disappear, they'll evolve. Think of them as your source of truth rather than your traffic generator. When AI summarizes answers for users, it still references real content and authoritative sources. So, your website remains essential for credibility, events, and conversion, even if fewer users arrive there through traditional search. For instance, if someone asks ChatGPT about agency growth events in Austin, and you've mentioned your event across social media, your website, and podcasts, AI will likely include it in the results. "That's how people find you now," Vishal agrees. "Not just through search but through signals from every platform." Of course, you should still think about the content you're putting out on your website. Are you answering the questions that people are asking? Or you just optimizing for the keywords. Optimizing for the keywords won't work. People will ask LLMs questions and if you're already answering them on your content there are more chances that AI results will find you and list your website. Redefining Reporting and KPIs for Agencies One of the biggest challenges agencies face is explaining to clients why organic traffic might be dropping even as visibility increases. Why? Traditional SEO metrics no longer tell the whole story. So how to report back? Basically, you'll need to educate clients and start measuring mentions, citations, and referrals coming from AI platforms. Vishal suggests tracking LLM bot hits in server logs and monitoring whether AI crawlers are visiting key pages. These indicators reveal your brand's visibility in AI-generated results. While raw traffic might decline, the quality of leads and conversions often improves. "You might get fewer leads," he says, "but they'll be more qualified, because AI searchers are deeper in their intent." Leads from AI chats tend to be more serious buyers who have already researched their problems. The shift, then, isn't a loss but rather an opportunity to educate clients on new performance indicators that reflect where users actually search today. Preparing Your Agency and Clients for AI Search When it comes to optimizing for AI, Vishal recommends a hybrid approach: combine solid technical SEO fundamentals with a new layer of AI-readiness. This includes making sure your site is clean, crawlable, and structured properly, while also ensuring your brand has visibility across other platforms. At E2M, Vishal's team runs AI search audits to check how often their clients' brands appear in LLM answers. They even query ChatGPT and Perplexity directly to see what those systems say about them and their competitors. From there, they reverse-engineer visibility by identifying which platforms, podcasts, or publications help brands get cited more often by AI. Mentions on Reddit, Quora, and podcasts count, even if they're not linked, because they help build trust signals that LLMs detect. Agencies, Vishal says, can sell these as AI search audits, AI content audits, or full AI optimization packages — new recurring revenue streams that build on their SEO expertise. The Human Edge in an AI-Driven World Agencies can't afford to be "order takers" who wait for clients to bring up AI. If your clients are asking about AI before you bring it up, you're already behind. Instead, agencies should position themselves as trusted advisors who help clients navigate the shift confidently. So go to your clients and start those conversations, or you WILL be replaced by AI. At the end of the day, people still want connection, which is why both Jason and Vishal agree that AI will never replace the human element and the strategy, empathy, and creativity that come from real human connection. People will always want someone that can help guide them through the new marketing trends. As Vishal puts it, "Business owners don't have time to learn all this. They want someone they trust to handle it." AI might make average easier, but connection, data, and network will always be your edge. Do You Want to Transform Your Agency from a Liability to an Asset? Looking to dig deeper into your agency's potential? Check out our Agency Blueprint. Designed for agency owners like you, our Agency Blueprint helps you uncover growth opportunities, tackle obstacles, and craft a customized blueprint for your agency's success.
צ'אט ג'י.פי.טי, ג'מיני, גרוק ודיפסיק הסיני הם מודלי שפה גדולים (LLM) שבשימוש גם בישראל וגם בעברית. אבל הם לא נכתבו בעברית. לפי ד"ר אריאל סובלמן, חוקר בכיר במכון למחקרי ביטחון לאומי, כדאי מאוד לפתח מודל שפה גדול כחול לבן. לתפיסתו, שפה אינה רק כלי לבניית נרטיב - עניין חשוב כשלעצמו - אלא ממש נכס לביטחון הלאומי. עם העיתונאית עמנואל אלבז-פלפס, הוא מקיים שיחה פילוסופית על מילים בעולם של מחשבים ענקיים ואנרגיה עצומה, שמובילה לשיחה על הצורך הממשלתי להכיר בדחיפות במשימה, לתקצב אותה כראוי וליצור בריתות אזוריות על מנת לעלות על הרכבת של הבינה המלאכותית לפני שיהיה מאוחר מדי.
In this episode, Jeff interviews Luca about his intensive experience presenting at five conferences in two and a half days, including the Embedded Online Conference and a German conference where he delivered a keynote on AI-enhanced software development. Luca shares practical insights from running an LLM-only hackathon where participants were prohibited from manually writing any code that entered version control—forcing them to rely entirely on AI tools.The conversation explores technical challenges in AI-assisted embedded development, particularly the importance of context management when working with LLMs. Luca reveals that effective AI-assisted coding requires treating prompts like code itself—version controlling them, refining them iteratively, and building project-specific prompt libraries. He discusses the economics of LLM-based development (approximately one cent per line of code), the dramatic tightening of feedback loops from days to minutes, and how this fundamentally changes agile workflows for embedded teams.The episode concludes with a discussion about the evolving role of embedded developers—from code writers to AI supervisors and eventually to product owners with deep technical skills. Luca and Jeff address concerns about maintaining core software engineering competencies while embracing these powerful new tools, emphasizing that understanding the craft remains essential even as the tools evolve.Key Topics[02:15] LLM-only hackathon constraints: No human-written code in version control[04:30] Context management as the critical skill for effective LLM-assisted development[08:45] Explicit context control: Files, directories, API documentation, and web content integration[11:20] LLM hallucinations: When AI invents file contents and generates diffs against phantom code[13:00] Economics of AI-assisted coding: Approximately $0.01 per line of code[15:30] Tightening feedback loops: From day-long iterations to minutes in agile embedded workflows[17:45] Rapid technical debt accumulation: How LLMs can create problems faster than humans notice[19:30] The essential role of comprehensive testing in AI-assisted development workflows[22:00] Challenges with TDD and LLMs: Getting AI to take small steps and wait for feedback[26:15] Treating prompts like code: Version control, libraries, and project-specific prompt management[29:40] External context management: Coding style guides, plan files, and todo.txt workflows[32:00] LLM attention patterns: Beginning and end of context receive more focus than middle content[34:30] The evolving developer role: From coder to prompt engineer to AI supervisor to technical product owner[38:00] Code wireframing: Rapid prototyping for embedded systems using AI-generated implementations[40:15] Maintaining software engineering skills in the age of AI: The importance of manual practice[43:00] Software engineering vs. software carpentry: Architecture and goals over syntax and implementationNotable Quotes"One of the hardest things to get an LLM to do is nothing. Sometimes I just want to brainstorm with it and say, let's look at the code base, let's figure out how we're going to tackle this next piece of functionality. And then it says, 'Yeah, I think we should do it like this. You know what? I'm going to do it right now.' And it's so terrible. Stop. You didn't even wait for me to weigh in." — Luca Ingianni"LLMs making everything faster also means they can create technical debt at a spectacular rate. And it gets a little worse because if you're not paying close attention and if you're not disciplined, then it kind of passes you by at first. It generates code and the code kind of looks fine. And you say, yeah, let's keep going. And then you notice that actually it's quite terrible." — Luca Ingianni"I would not trust myself to review an LLM's code and be able to spot all of the little subtleties that it gets wrong. But if I at least have tests that express my goals and maybe also my worries in terms of robustness, then I can feel a lot safer to iterate very quickly within those guardrails." — Luca Ingianni"Roughly speaking, the way I was using the tool, I was spending about a cent per line. Which is about two orders of magnitude below what a human programmer roughly costs. It really is a fraction. So that's nice because it makes certain things approachable. It changes certain build versus buy decisions." — Luca Ingianni"You can tighten your feedback loops to an absurd degree. Maybe before, if you had a really tight feedback loop between a product owner and a developer, it was maybe a day long. And now it can be minutes or quarters of an hour. It is so much faster. And that's not just a quantitative step. It's also a qualitative step." — Luca Ingianni"Some of my best performing prompts came from a place of desperation where one of my prompts is literally 'wait wait wait you didn't do what we agreed you would do you did not read the files carefully.' And I'd like to use this prompt now, even before it did something wrong. And then it apologizes as the first step. And I feel terrible because I hurt the LLM's feelings. But it is very effective." — Luca Ingianni"As you tighten your feedback loops, quality must be maintained through code review and tests. Test first, new feature, review, passing tests—you need to go through that red-green-refactor loop. You can just hopefully do it much more quickly, and maybe in slightly bigger steps than you did before manually." — Jeff Gable"A lot of what I'm doing is really intended to rein in an LLM's propensity to sort of ramble. It's very hard to get them to practice TDD because you can ask them to write the test first, then they will. And then they will just trample on and write the implementation right with it without stopping and returning control back to you." — Luca Ingianni"Those prompts tend to be to some degree specific to the particular code base or the particular problem domain. Every now and then you stumble across ways of making an LLM do exactly what you want it to do within the context of the particular code base. And once you find a nugget like this, you keep it. You don't just keep it in the generic library. Some of those tricks will be very specific to a particular code base." — Luca Ingianni"Just like humans, LLMs tend to pay more attention to the stuff at the beginning of the context and at the end, and the middle sort of gets not quite forgotten but kind of fuzzy. You really need to have a way to extract all of that before it becomes fuzzy and store it in a safe place where it can't be damaged, like a file." — Luca Ingianni"I think we will hit this weird valley in the coming five years where everyone's just using LLMs and no one knows how to write code anymore. And there will be a need for people who can leverage the tools, but still have the skills that serve as the solid foundation." — Jeff Gable"Maybe this is essentially software engineering finally becoming true to its name. At the moment, software engineering is sort of more like software carpentry. You're really doing the craft. You're laboring to put the curly brackets at the right places. And maybe now it's more about taking a step back and thinking in terms of architecture, and thinking in terms of goals, as opposed to knowing how to swing a hammer." — Luca IngianniResources MentionedEmbedded Online Conference - Premier online conference for embedded systems professionals featuring talks on AI integration, development practices, and cutting-edge embedded technologies. All sessions are recorded and available for on-demand viewing.Aider - AI pair programming tool mentioned for its ability to integrate web content into context using commands like '/web [URL]' to incorporate API documentation and other online resources directly into the development workflow.GitHub Copilot - AI-powered code completion tool integrated with VS Code and other IDEs, enabling context-aware code generation and assistance for embedded development workflows. You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/
Timestamps:3:30 - Identifying a market gap in legal tech 10:06 - What is “smart money” after all?16:22 - How do you go from researcher to CEO?25:55 - The biggest risk for every scaleup36:20 - Is Switzerland a hotbed for AI?This episode was co-produced by SICTIC, the leading angel investor network in Switzerland.This episode was sponsored by Relai. Get started with Bitcoin by downloading the Relai app today, and profit from 10% less fees by entering code SWISSPRENEUR at checkout.(Disclaimer: Relai services are exclusively recommended for Swiss and Italian residents.)Click here to order your copy of “Swiss Startups” today.Episode Description:Thomas Dübendorfer is the founder and president of SICTIC, the leading angel investor network in Switzerland. He's also a cybersecurity expert and serial entrepreneur, holding board seats at Frontify and several other startups. Paulina Grnarova is the co-founder and CEO of DeepJudge, an AI-powered knowledge search for legal professionals. She holds a PhD in Computer Science from ETH, and started her company in 2021, directly after completing her studies.Founded by ex-Google search engineers and legaltech veterans, DeepJudge reimagines how firms access and use their internal knowledge, unlocking the full breadth of data and depth of documents to improve all areas of a lawyer's business. It enables you to build entire AI applications, encapsulate multi-step workflows, and implement LLM agents.SICTIC is one of DeepJudge's investors. During his chat with Merle and Paulina, SICTIC president Thomas Dübendorfer shared how he assesses startup teams: Does the founder really understand what the journey of a startup is? Can the startup team evolve to meet changing demands?Does the team believe what they're selling?Are they aware that they'll have to overcome several difficulties in the coming years?Are they all moving in the same direction, working to achieve the same mission?Thomas also takes care to assess companies from an ethical standpoint, especially when the tech has dual use. For instance, drones can be used for rescue missions or to bring food or medicine, but they can also be used to transport weapons. In cases like these, it's crucial to confront the founders with the most problematic possibilities upfront.Thomas is confident in Switzerland's AI future: all the experts are here, across a very broad range of industries, and, when it comes to AI specifically, Switzerland can already count on several research institutions making great strides - like the ETH AI Center, the Swiss National Institute, and the Swiss National SuperComputing Center.The cover portrait was edited by Smartportrait. Don't forget to give us a follow on Instagram, Linkedin, TikTok, and Youtube so you can always stay up to date with our latest initiatives. That way, there's no excuse for missing out on live shows, weekly giveaways or founders' dinners.
Register for Founder University Japan's Kickoff! https://luma.com/cm0x90mkToday's show:Find out why AI is perfectly suited to legal tasks… despite being too fast for “billable hours”On today's TWiST, Alex takes a deep dive into LLM Law with Harvey AI co-founder/president Gabe Pereyra. It turns out, much like software development, doing legal work relies on learning specialized language and sifting through a dense and expansive corpus of information… making it an IDEAL use case for LLMs.Buuuuut AI works so fast… the current structure of legal payments (billable hours) no longer applies. Find out how Harvey is working around these challenges — and what they plan to do if OpenAI decides to get into the legal game — in this fascinating interview.THEN, Alex chats with another AI visionary — OpenRouter co-founder and CEO Alex Atallah — who allows developers to plug and play all the major models into their applications. Find out why specialized LLMs trained for “resourcefulness” are coming into fashion… why benchmarks and evals have become so crucial to the industry… AND whether we'll end up spending as much on AI inference as the human workers it's replacing… in this essential discussion.PLUS Jason stops by for some more Founder Q's!Timestamps:(0:00) Welcome back to TWiST!(1:32) Alex kicks off the show with Harvey AI co-founder and President Gabe Pereyra to talk about applying AI to the legal profession(4:52) How major international law firms (and their enterprise clients) fueled Harvey's mega-growth(6:54) Why LLMs are perfectly suited for legal work(9:24) Enterpret - Enterpret turns feedback noise into Customer Intelligence, so your team knows exactly what to fix and build next. Head to Enterpret.com/twist to book a demo and see it in action.x and build next. Head to Enterpret.com/twist to book a demo and see it in action.(17:22) Looking ahead: expanding beyond the law.(20:42) Uber AI Solutions - Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at Uber.com/twist(21:44) The problem: AI can't charge “billable hours”… it's too fast!(23:44) Will the major AI players like Google and OpenAI build their own version of this?(29:53) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(30:41) Alex welcomes OpenRouter co-founder and CEO Alex Atallah, whose rankings he loves and uses all the time(33:10) Why Alex says we're seeing more specialized LLMs trained for more “resourcefulness”(36:05) How increased competition and diversification makes things tougher for developers(41:09) Alex suggests that new models are exciting for users, like product launches used to be(42:29) OK, let's get into it… How does OpenRouter make money?(45:38) Understanding what kinds of training data the AI companies want the MOST(47:47) The important currency of evals and benchmarks(49:13) Why OpenRouter is ramping up its LLM recommendation engine(53:44) Will AI inference spend end up costing as much as the humans it's replacing?(56:49) Time for a Founder Q! What should founders do about quick vibe-coded competitors?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelmThank you to our partners:(9:24) Enterpret - Enterpret turns feedback noise into Customer Intelligence, so your team knows exactly what to fix and build next. Head to Enterpret.com/twist to book a demo and see it in action.x and build next. Head to Enterpret.com/twist to book a demo and see it in action.(20:42) Uber AI Solutions - Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at Uber.com/twist(29:53) Lemon.io - Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist
Are we underestimating how the agentic world is impacting cybersecurity? We spoke to Mohan Kumar, who did production security at Box for a deep dive into the threats of true autonomous AI agents.The conversation moves beyond simple LLM applications (like chatbots) to the new world of dynamic, goal-driven agents that can take autonomous actions. Mohan took us through why this shift introduces a new class of threats we aren't prepared for, such as agents developing new, unmonitorable communication methods ("Jibber-link" mode).Mohan shared his top three security threats for AI agents in production:Memory Poisoning: How an agent's trusted memory (long-term, short-term, or entity memory) can be corrupted via indirect prompt injection, altering its core decisions.Tool Misuse: The risk of agents connecting to rogue tools or MCP servers, or having their legitimate tools (like a calendar) exploited for data exfiltration.Privilege Compromise: The critical need to enforce least-privilege on agents that can shift roles and identities, often through misconfiguration.Guest Socials - Mohan's LinkedinPodcast Twitter - @CloudSecPod If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels:-Cloud Security Podcast- Youtube- Cloud Security Newsletter If you are interested in AI Cybersecurity, you can check out our sister podcast - AI Security PodcastQuestions asked:(00:00) Introduction(01:30) Who is Mohan Kumar? (Production Security at Box)(03:30) LLM Application vs. AI Agent: What's the Difference?(06:50) "We are totally underestimating" AI agent threats(07:45) Software 3.0: When Prompts Become the New Software(08:20) The "Jibber-link" Threat: Agents Ditching Human Language(10:45) The Top 3 AI Agent Security Threats(11:10) Threat 1: Memory Poisoning & Context Manipulation(14:00) Threat 2: Tool Misuse (e.g., exploiting a calendar tool)(16:50) Threat 3: Privilege Compromise (Least Privilege for Agents)(18:20) How Do You Monitor & Audit Autonomous Agents?(20:30) The Need for "Observer" Agents(24:45) The 6 Components of an AI Agent Architecture(27:00) Threat Modeling: Using CSA's MAESTRO Framework(31:20) Are Leaks Only from Open Source Models or Closed (OpenAI, Claude) Too?(34:10) The "Grandma Trick": Any Model is Susceptible(38:15) Where is AI Agent Security Evolving? (Orchestration, Data, Interface)(42:00) Fun Questions: Hacking MCPs, Skydiving & Risk, BiryaniResources mentioned during the episode:Mohan's Udemy Course -AI Security Bootcamp: LLM Hacking Basics Andre Karpathy's "Software 3.0" Concept "Jibber-link Mode" VideoCrewAI FrameworkOWASP Top 10 for LLM Applications Cloud Security Alliance (CSA) MAESTRO Framework
Ever wondered what happens to your online accounts when you're gone?
This episode features Tami Cannizzaro, Chief Marketing Officer at Thryv, a software company helping small business owners run and grow their businesses with AI-powered tools. Tami shares how her team focuses on revenue first and builds marketing strategies around what drives impact for SMBs.She discusses the shift from traditional SEO to AEO and why speed and originality now define effective marketing. Key TakeawaysAEO and AI are redefining how customers find brands online: Learn how to optimize for AI-driven discovery so your brand appears in conversational search and LLM-generated results.Fresh, original content outperforms repurposed AI blogs: The fastest way to lose visibility is to sound like everyone else. Originality and recency are now ranking factors in AI search.First-mover advantage in AI tools can create outsized revenue impact: Early adopters capture learnings and market share before competitors adapt.Quote“Anytime there's something new in marketing, if you can be a first mover and jump on it before everyone else figures it out, there's a real opportunity to drive revenue from that.”Episode Timestamps(02:28) The Trust Tree: Supporting SMBs(17:12) The Playbook: ABM, AEO, and social ads (37:34) Quick Hits: Tami's Quick HitsSponsorPipeline Visionaries is brought to you by Qualified.com — the pipeline generation platform for revenue teams.Turn your website into a pipeline machine with PipelineAI. Engage and convert your most valuable visitors with live chat, chatbots, meeting scheduling, and intent data.Visit Qualified.com to learn more.LinksConnect with Ian on LinkedInConnect with Tami on LinkedInLearn more about ThryvLearn more about Caspian Studios Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
A CMO Confidential Interview with Andy Sack and Adam Brotman, Co-Founders and Co-CEO's of Forum 3, authors of the book AI First, previously at Microsoft and Starbucks. Adam and Andy discuss the exponential growth of LLM's in the 3 years since the Chat GPT launch, the rapid pace of consumer adoption and "why there's never been a bigger prize in capitalism." Key topics include: why the circular tie-ups between the models and chip providers may make sense, their belief that only 5% of companies are well underway; why you should use AI at least 10 times a day; and how the "current way of doing business" is the biggest blocker to progress. Tune in to hear 2026 predictions, why you should have a "family password," and how an AI Zoom scam resulted in a $20 million loss for the company. AI: The Year That Changed Marketing | Andy Sack & Adam Brotman on CMO ConfidentialFormer Starbucks Chief Digital Officer Adam Brotman and investor/operator Andy Sack return to break down AI's wild 2025—and what's next for marketers and the C-suite in 2026. We cover the rise of reasoning models and agents, chip-and-model tie-ups, who's winning (and who's falling behind), why only ~5% of companies are truly “underway,” and how consumer behavior is racing ahead of most enterprises. Adam and Andy deliver pragmatic guidance for boards, CEOs, and CMOs: where to lean in, how to organize, and what to build now.What you'll learn:• The real story on model advances, agents, and the chip/energy bottlenecks• Why supply-lock deals aren't “circular nonsense” and how they'll shape winners/losers• Enterprise reality check: 5% vs. 95%, and why CEO/board sponsorship determines lift-off• Consumer adoption, zero-click search, and how discovery is shifting under your feet• Marketing beyond efficiency: ideation, synthetic testing, and creative at production speed• 2026 predictions: Apple's big AI move, the year of consumer agents, and new AI devices• Risk & resilience: deepfake fraud, the “family password,” and change management that sticksActionable takeaways:• Use AI 10×/day; turn on voice and select a “thinking/reasoning” model for complex work• Treat AI as a company-wide transformation, not an IT pilot; pick a few high-value use cases and own them from the top• Experiment with agentic workflows and AI video to compress cycle time from storyboard to launchSponsored by @typefaceai Typeface helps the world's biggest brands go from brief to fully personalized, on-brand campaigns in hours—not months. Their agentic AI marketing platform automates workflows across ads, email, and video, integrates with your MarTech stack, and includes enterprise-grade security. Adweek named Typeface “AI Company of the Year,” TIME listed it among the Best Inventions, and Fast Company called it the next big thing in tech. See how brands like @ASICSGlobal and @Microsoft are transforming marketing with Typeface: typeface.ai/cmoAbout CMO ConfidentialHosted by five-time CMO Mike Linton, CMO Confidential goes inside the decisions, politics, and trade-offs of one of the most scrutinized jobs in the C-suite. New episodes every Tuesday on Spotify, Apple, and YouTube.00:00 Intro & Sponsor: Typeface02:00 Topic & Guests — Adam Brotman and Andy Sack03:00 Three-year AI surge: usage, video, geopolitics06:00 Reasoning models, long-duration agents, chip/energy demand10:00 Midroll: Typeface12:00 Capital tie-ups: supply lock vs. “circular money”15:00 Winners & losers: the AGI race and consolidation16:00 Enterprise adoption: board/CEO-led change vs. IT pilots18:50 Reality check: 5% “well underway,” 95% early22:00 Consumer adoption: everyday use, underutilization25:00 Can companies keep up? Why most are lagging27:00 Search is shifting: AI overviews, assistants everywhere29:00 Marketing beyond efficiency: ideation, automation, CX31:00 AI video examples to study (Kalshi ad, IAm8)33:30 Agencies & consultancies adapting (Accenture, BCG, McKinsey)34:30 2026 predictions: Apple's big move, year of agents, new devices36:00 2026 tensions: labor disruption, backlash, “bumpy” progress38:00 Practical tips: use AI 10×/day, voice mode, “thinking” models41:00 Tools & safety: @lovable family/business passwords42:00 Deepfake/Zoom heist cautionary tale44:00 Wrap-up: subscribe & episode library44:30 Closing Sponsor: Typeface —CMO Confidential,Mike Linton,Adam Brotman,Andy Sack,Typeface,agentic AI,AI marketing,marketing strategy,chief marketing officer,CMO,CEO,board strategy,enterprise AI,reasoning models,AI agents,AGI,LLMs,generative AI,Claude,Gemini,ChatGPT,NVIDIA,semiconductors,MarTech,creative automation,personalization,zero click search,search disruption,media buying,advertising,brand vs performance,organizational design,change management,digital transformation,customer experience,synthetic personas,AI video,SOA,Sora,Replit Agent,Apple AI,Perplexity,security,deepfakes,family password,go to market,content at scale,ASICSSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Tyler Martin, Senior Director of Enterprise Security Engineering & Operations at FanDuel, reflects on revolutionizing security operations by replacing traditional analyst tiers with security engineers supported by custom AI agents. Tyler shares the architecture behind SAGE, FanDuel's phishing automation system, and explains how his team progressed from human-in-the-loop validation to fully autonomous triage through bronze-silver-gold maturity stages. The conversation explores practical challenges like context enrichment, implementing user personas connected to IDP and HRIS systems, and choosing between RAG versus CAG models for knowledge augmentation. Tyler also discusses shifts in detection strategy, arguing for leaner detection catalogs with just-in-time, query-based rules over maintaining point-in-time codified detections that no longer address active risks. Topics discussed: Restructuring security operations teams to include only security engineers while AI agents handle traditional level 1-3 triage work. Building Security Analysis and Guided Escalation, an AI-powered phishing automation system that reduced manual ticket volume. Implementing bronze-silver-gold maturity stages for AI triage: manual validation, automated closures with oversight, and full autonomous operations. Enriching AI agents with organizational context through connections to IDP systems, HRIS platforms, and user behavior analytics. Creating user personas that encode access patterns, permissions, security groups, and typical behaviors to improve AI decision-making accuracy. Designing incident response automation that spins up Slack channels, Zoom bridges, recordings, and comprehensive documentation through simple commands. Eliminating 90% of missing PIR action items through automated documentation capture and stakeholder tagging in Confluence. Shifting detection strategy from maintaining large MITRE-mapped catalogs to just-in-time query-based rules written by AI agents. Balancing signal volume and enrichment data against inference costs while avoiding context rot that degrades LLM performance. Evaluating RAG versus CAG models for knowledge augmentation and exploring multi-agent architectures with supervisory oversight layers. Listen to more episodes: Apple Spotify YouTube Website
Leaders, avoid tripping and falling into the current LLM hype cycle. ---Opening and closing themes composed by Brian Sanyshyn of Brian Sanyshyn Music.---Pick up your copy of 12 Rules for Leaders: The Foundation of Intentional Leadership NOW on AMAZON!Check out the 2022 Leadership Lessons From the Great Books podcast reading list!--- ★ Support this podcast on Patreon ★ Subscribe to the Leadership Lessons From The Great Books Podcast: https://bit.ly/LLFTGBSubscribeCheck out HSCT Publishing at: https://www.hsctpublishing.com/.Check out LeadingKeys at: https://www.leadingkeys.com/Check out Leadership ToolBox at: https://leadershiptoolbox.us/Contact HSCT for more information at 1-833-216-8296 to schedule a full DEMO of LeadingKeys with one of our team members.---Leadership ToolBox website: https://leadershiptoolbox.us/.Leadership ToolBox LinkedIn: https://www.linkedin.com/company/ldrshptlbx/.Leadership ToolBox YouTube: https://www.youtube.com/@leadershiptoolbox/videosLeadership ToolBox Twitter: https://twitter.com/ldrshptlbx.Leadership ToolBox IG: https://www.instagram.com/leadershiptoolboxus/.Leadership ToolBox FB: https://www.facebook.com/
У новому епізоді обговорюємо найпомітніші події технологічного тижня. Основна частина дискусії присвячена турніру з покеру між різними моделями штучного інтелекту, де перше місце зайняла модель OpenAI o3, а деякі інші моделі продемонстрували невдалу гру, що свідчить про значну роль випадковості, а не справжній інтелект. OpenAI презентувала браузер Atlas, який інтегрує модель у сам процес перегляду сторінок, створюючи серйозні ризики витоку інформації.Крім того, TikTok переписав частину коду на Rust і заощадив сотні тисяч доларів, а робот X1, попри гучну рекламу, виявився не таким автономним, як обіцяли. Наприкінці говоримо про смартпристрої, які дедалі частіше показують рекламу, і про те, що за зручністю часто ховається комерційний інтерес.00:34 — турнір покеру між моделями ШІ05:34 — проблеми безпеки нового браузера Atlas08:05 — зловісна долина та нові роботи X111:10 — гуманоїдні роботи: практичність чи маркетинг?18:45 — технічні інновації: перехід на Rust у TikTok26:06 — браузери та їх еволюція32:37 — відкриті технології: 3D принтери від Prusa36:33 — проблеми з розумними пристроями42:13 — безпека в розумному будинку та замки47:40 — безпека мобільних пристроїв
Today, we are learning from Zulfia Abawe. Zulfia is a lecturer in Global Business and Cohort Lead in the MBA Global Program at the Faculty of Business and Creative Industries at the University of South Wales (Zulfia Abawe — University of South Wales). Holding three post-graduate degrees, including a Masters in Public Policy, LLM in Human Rights, and a PhD in Law and Democracy, she has extensive experience in political and legal analysis, with a particular focus on Afghanistan's legal pluralism and political institutions. Her PhD dissertation examined Afghanistan's legal pluralism from a gendered perspective and its reflection, or lack of, in the 2004 Afghan constitution. Currently, she is exploring relationality and decoloniality as an analytical and theoretical framework to study foreign interventions in Afghanistan from 2001 to 2021, emphasizing decoloniality, local practices and decolonial knowledge production in legal and political developments. Let's get started... In this conversation with Zulfia Abawe, I learned: 00:00 Intro - how to pronounce Afghanistan and the decolonization of the IDGs 03:40 - Explaining the work that Zulfia does at the University of Wales 04:30 The research work of Zulfia on international relations, decoloniality, relationality, and foreign interventions in Afghanistan. 05:20 Looking at colonisation not only from a North-South or East-West perspective. 09:15 The symbolic elements of the various accents and how they form me. 11:00 Afghanistan is called the graveyard of empires. 13:20 Challenging the victim-savior approach from the Western world towards Afghanistan. 16:05 You have to get as much education as possible, and books are your best friends - her mother always reminded her. 19:18 Bring in your lived experiences, especially in the era of AI. 23:50 We hoped that access to more information would make people smarter, but it often works in the opposite direction, and critical thinking is lacking. 30:25 The definition of leadership by Northouse misses the non-human relationships. 34:55 Acquiring knowledge by taking time to think about the question. 38:45 Going in and experiencing the similarities by being a part of the culture. 41:05 Decolonisation is the process of reflecting and questioning the things that I need to change within myself. 42:35 Knowledge is produced by the mind, the soul, the heart and desire. (Plato) 45:20 Using intuition from your own experiences and the lived experiences of your forefathers in your decision-making. 46:00 Looking for explanations of intuitive capabilities in the work of Jung and Frankl. 56:40 The intention behind the question and stepping onto the cultural island. 59:45 Zulfia is looking for co-authors for the book she is writing on foreign interventions—both military and non-military—from a gendered perspective and micro-resistance. More about Zulfia Abawe: https://www.linkedin.com/in/zulfia-abawe-ph-d-16861819/ https://zulfiaabawe.blogspot.com Resources we mention: Learn more about Afghanistan https://en.wikipedia.org/wiki/Afghanistan A connecting perspective on colonization – Rukmini Iyer Peter Guy Northouse - Leadership theory and practice Book Sophie's World - Wikipedia - Jostein Gaarder Dan Ariely - Wikipedia - Dan Ariely: Misbelief (website) Thinking, Fast and Slow - Wikipedia - Daniel Kahneman (Dutch book review) Predictably Irrational - Wikipedia - Dan Ariely Intuitions -- do we have good intuitions? (YouTube) Carl Gustav Jung - Wikipedia Man's Search for Meaning - Wikipedia - Viktor Frankl (Dutch book review) Socratic questioning - Wikipedia - (Dutch book review on Leer denken als Socrates – Donald Robertson #boekencast afl 127) The union for working animals - Vakbond voor dieren Geert Hofstede's cultural dimensions theory - Wikipedia - The 6 dimensions model of national culture by Geert Hofstede
This week, High Society Radio goes full “Gulag Digital” as Chris Faga and Chris Stanley dive into collapsing social contracts, failed politicians, and the absurd state of modern AI. From Cuomo's alternate universe and Zohran Mamdani's political theatrics to Dick Cheney's final headline, the boys cover politics, tech, and conspiracy in equal measure. There's talk of Gitmo gift shops, AI bubbles bursting, and MrBeast's soul—if he even has one. By the end, it's a philosophical meltdown about who (or what) still has a soul: billionaires, animals, or maybe even LLM's.Topics Include:Gulag DigitalNYC's Mass ExodusOne-Way Ticket to MiamiThe End of the Social ContractA World Where Cuomo WonRIP Dick CheneyDSA as a Real Third PartyMamdani Is a WorkYou Can't Invest in Anything in NYCBig Ups to the Drone GodGitmo Has a Gift ShopMamdani vs Obama SpeechesHating the Mayor Isn't RacistDid Sliwa's Vote Matter?Cheney's Death During Zohran's VoteStory About Zohran's In-LawsCracks in AISoftBank Guy & Michael Burry Shorting AISam Altman: “AI Is Too Big to Fail”ChatGPT Loses Legal & Medical Advice AccessGiant OpenAI DealsGoogle Is Just an Ad FactoryIs the Bubble About to Pop?Redistributing a TrillionMrBeast LandWho Has a Soul: MrBeast, Peter Thiel, or Sam Altman?If the Devil Was RealDON'T FORGET TO WATCH FAGA'S NEW SPECIAL "BURN AFTER SAYING" ON THE HSR YOUTUBE PAGE!https://www.youtube.com/watch?v=TxIHJU2LotUSupport Our Sponsors!https://yokratom.com/ - Check out Yo Kratom (the home of the $60 kilo) for all your kratom needs!Body Brain Coffee: https://bodybraincoffee.com/ - Grab A Bag of Body Brain Coffee with Promo Code HSR20 to get 20% off!https://fatdickhotchocolate.net/ Get you a fat dick at fatdickhotchocolate.netHigh Society Radio is 2 native New Yorkers who started from the bottom and didn't raise up much. That's not the point, if you enjoy a sideways view on technology, current events, or just an in depth analysis of action movies from 2006 this is the show for you.Chris Stanley is the on-air producer for Bennington on Sirius XM.A Twitter Chris Really Likes: https://x.com/stanman42069Chris from Brooklyn is a lifelong street urchin, a former head chef and current retiree.Twitter: https://twitter.com/ChrisFromBklynEngineer: JorgeEditor: TannerInstagram: https://www.instagram.com/lilkinky69/Executive Producer: Mike HarringtonInstagram: https://www.instagram.com/themharrington/Twitter: https://twitter.com/TheMHarringtonSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Tara Sinclair is a professor and chair of the economics department at George Washington University. Tara returns to the show to discuss her ambitious paper simulating an FOMC meeting before it happens with LLM models, the process of building sim FOMC members, the importance of publicly funding economic data, the future of AI and macroeconomics, and much more. Check out the transcript for this week's episode, now with links. Recorded on October 27th, 2025 Subscribe to David's Substack: Macroeconomic Policy Nexus Follow David Beckworth on X: @DavidBeckworth Follow Tara on X: @TaraSinc Follow the show on X: @Macro_Musings Check out our Macro Musings merch! Subscribe to David's new BTS YouTube Channel Timestamps 00:00:00 - Intro 00:01:44 - Data and Policymaking 00:05:28 - Federal Forecasters Conference 00:08:01 - FOMC in Silico 00:32:56 - Future Applications 00:38:29 - Broader Implications 00:42:57 - Central Bank Governance and AI 00:51:40 - Outro
Matthew Bertram brings Rob Neumann on to map how private LLMs, PIM/DAM, and AI-driven search turn messy B2B catalogs into findable, persuasive product experiences that convert. We push leaders to move now on the LLM land grab, unify entities, and align teams to become AI first.• unifying brand, author, and entity signals for clarity• why every business needs an e-commerce path• findability before conversion and product page SEO• persona-based descriptions with private LLMs• PIM/DAM as the enrichment layer above ERP• AI search for exact matches and smart substitutes• channel-aware inventory and safety stock reduction• SKU and vendor normalization for white label margin• CAD, specs, and E‑E‑A‑T for trust and rankings• email fatigue, SMS prompts, and postcard nudges• urgency of the LLM land grab and authority hardeningGuest Contact Information: Website: robneumann.comLinkedIn: linkedin.com/in/robertneumannMore from EWR and Matthew:Leave us a review wherever you listen: Spotify, Apple Podcasts, or Amazon PodcastFree SEO Consultation: www.ewrdigital.com/discovery-callWith over 5 million downloads, The Best SEO Podcast has been the go-to show for digital marketers, business owners, and entrepreneurs wanting real-world strategies to grow online. Now, host Matthew Bertram — creator of LLM Visibility™ and the LLM Visibility Stack™, and Lead Strategist at EWR Digital — takes the conversation beyond traditional SEO into the AI era of discoverability. Each week, Matthew dives into the tactics, frameworks, and insights that matter most in a world where search engines, large language models, and answer engines are reshaping how people find, trust, and choose businesses. From SEO and AI-driven marketing to executive-level growth strategy, you'll hear expert interviews, deep-dive discussions, and actionable strategies to help you stay ahead of the curve. Find more episodes here: youtube.com/@BestSEOPodcastbestseopodcast.combestseopodcast.buzzsprout.comFollow us on:Facebook: @bestseopodcastInstagram: @thebestseopodcastTiktok: @bestseopodcastLinkedIn: @bestseopodcastConnect With Matthew Bertram: Website: www.matthewbertram.comInstagram: @matt_bertram_liveLinkedIn: @mattbertramlivePowered by: ewrdigital.comSupport the show
This Listing Bits episode is now available on your favorite podcast player! Overview Greg Robertson sits down with industry veteran Amy Gorce of REdistribute to clarify what REdistribute actually does, how it differs from display-focused data platforms, and why MLSs should care about the exploding gray-market use of MLS data. Amy breaks down the institutional-buyer use cases, explains how gray-market pipelines emerged, and outlines why MLS participation directly impacts valuation accuracy, AVMs, risk modeling, and overall market health. Key Takeaways • REdistribute is not a display vendor. Their data is used solely for institutional-grade analytics, AVMs, risk modeling, and portfolio management—never for consumer-facing listing display.  • Owned by MLSs, built for MLSs. The operating agreement limits eligible purchasers and prevents MLSs or brokers from using the data for competitive display products.  • The gray market is real and accelerating. Companies scrape, partner with brokers, or purchase unclear data sources to fuel AVMs and risk tools—often without MLS compensation. REdistribute is actively converting gray-market users.  • AI is making the problem bigger. Scraping tools, automated ingestion, and LLM training pipelines are proliferating. REdistribute is building an MCP server to support AI-specific use cases in a controlled and compliant way.  • Coverage, not demand, is the bottleneck. Institutional buyers are ready, but MLS participation is still below critical mass (~55–60% coverage). More MLSs joining closes the gap and increases revenue potential.  • Economics vary by use case. AVM licensing generates significantly higher value than simple match-and-append use cases—creating real opportunities for meaningful revenue distribution back to MLSs and brokers.  • Joining is simple. MLSs sign a license agreement and can be onboarded in roughly two weeks, with quarterly revenue distributions.  Links • The Market Value of Listing Data—and the Cost of the Grey Market - White Paper Contact Amy Gorce Allison Duggins Sponsors Trackxi - Real Estate's #1 Deal Tracking Software Giant Steps Job Board – Where ORE gets hired Production and editing services by: Sunbound Studios
У свіжому дайджесті DOU News поговоримо про падіння акцій GTA 6, угоду Apple з Google та масштабну співпрацю OpenAI з AWS. А ще — про витік коду App Store, нову ШІ-війну між Amazon і Perplexity та інші теми українського ІТ та світового тек-сектору. Таймкоди 00:00 Інтро 00:24 НБУ хоче оподаткувати посилки до €150 02:41 Оборонні компанії зможуть бронювати працівників попри розшук 04:27 «DevOps Engineer» — курс від robot_dreams 05:43 Apple уклала угоду з Google на $1 млрд на рік 08:03 Новий випуск «копінги та допінги» з керівницею Google Україна 08:37 Apple випадково злила код нового App Store 09:58 iOS, iPadOS і macOS змінили Liquid Glass 12:30 Meta заробляє мільярди на шахрайських рекламах у Facebook 14:59 OpenAI уклала угоду з AWS на $38 млрд 16:31 Amazon і Perplexity розпочали війну ШІ-браузерів 18:33 ШІ-браузер Dia отримує найкращі функції Arc 21:37 Акції видавця GTA 6 впали після перенесення релізу 23:33 Нова святкова реклама Coca-Cola створена ШІ 25:47 Приватна компанія запустила власну космічну станцію 28:43 Що цього тижня рекомендує Женя: qqqa — LLM для розробників та подкаст про Rolex
Guest: Ari Herbert-Voss, CEO at RunSybil Topics: The market already has Breach and Attack Simulation (BAS), for testing known TTPs. You're calling this 'AI-powered' red teaming. Is this just a fancy LLM stringing together known attacks, or is there a genuine agent here that can discover a truly novel attack path that a human hasn't scripted for it? Let's talk about the 'so what?' problem. Pentest reports are famous for becoming shelf-ware. How do you turn a complex AI finding into an actionable ticket for a developer, and more importantly, how do you help a CISO decide which of the thousand 'criticals' to actually fix first? You're asking customers to unleash a 'hacker AI' in their production environment. That's terrifying. What are the 'do no harm' guardrails? How do you guarantee your AI won't accidentally rm -rf a critical server or cause a denial of service while it's 'exploring'? You mentioned the AI is particularly good at finding authentication bugs. Why that specific category? What's the secret sauce there, and what's the reaction from customers when you show them those types of flaws? Is this AI meant to replace a human red teamer, or make them better? Does it automate the boring stuff so experts can focus on creative business logic attacks, or is the ultimate goal to automate the entire red team function away? So, is this just about finding holes, or are you closing the loop for the blue team? Can the attack paths your AI finds be automatically translated into high-fidelity detection rules? Is the end goal a continuous purple team engine that's constantly training our defenses? Also, what about fixing? What makes your findings more fixable? What will happen to red team testing in 2-3 years if this technology gets better? Resource: Kim Zetter Zero Day blog EP230 AI Red Teaming: Surprises, Strategies, and Lessons from Google EP217 Red Teaming AI: Uncovering Surprises, Facing New Threats, and the Same Old Mistakes? EP68 How We Attack AI? Learn More at Our RSA Panel! EP71 Attacking Google to Defend Google: How Google Does Red Team
Why does an AI that brilliantly generates code suddenly fail at basic math? The answer explains why your LLM will fail when you least expect it.In this episode, Emmanuel Maggiori, author of “Smart Until It's Dumb” and “The AI Pocket Book,” cuts through the AI hype to reveal what LLMs actually do and, more importantly, what they can't. Drawing from his experience building AI systems and witnessing multiple AI booms and busts, Emmanuel explains why machine learning works brilliantly until it makes mistakes no human would ever make.He shares why businesses repeatedly fail at AI adoption, how hallucinations are baked into the technology, and what developers need to know about building reliable AI products.Whether you're implementing AI at work or concerned about your career, this conversation offers a grounded perspective on navigating the current AI wave without getting swept away by unrealistic promises.Key topics discussed:Why AI projects fail the same way repeatedlyHow LLMs work and why they brilliantly failWhy hallucinations can't be fixed with better promptsWhy self-driving cars still need human operatorsAdopting AI without falling into hype trapsHow engineers stay relevant in the AI eraWhy AGI predictions are mostly marketingBuilding valuable products in boring industriesTimestamps:(00:00:00) Trailer & Intro(00:02:32) Career Turning Points(00:06:41) Writing “Smart Until It's Dumb” and “The AI Pocket Book”(00:08:14) The History of AI Booms & Winters(00:11:34) Why Generative AI Hype is Different Than the Past AI Waves(00:13:26) AI is Smart Until It's Dumb(00:16:45) How LLM and Generative AI Actually Work(00:22:53) What Makes LLMs Smart(00:27:25) Foundational Model(00:30:01) RAG and Agentic AI(00:34:09) Tips on How to Adopt AI Within Companies(00:37:56) How to Reduce & Avoid AI Hallucination Problem(00:45:49) The Important Role of Benchmarks When Building AI Products(00:50:57) Advice for Software Engineers to Deal With AI Concerns(00:56:49) Advice for Junior Developers(00:59:34) Vibe Coders and Prompt Engineers: New Jobs or Just Hype?(01:01:55) The AGI Possibility(01:07:23) Three Tech Lead Wisdom_____Emmanuel Maggiori's BioEmmanuel Maggiori, PhD, is a software engineer and 10-year AI industry insider. He has developed AI for a variety of applications, from processing satellite images to packaging deals for holiday travelers. He is the author of the books Smart Until It's Dumb, Siliconned, and The AI Pocket Book.Follow Emmanuel:LinkedIn – linkedin.com/in/emaggioriWebsite – emaggiori.comLike this episode?Show notes & transcript: techleadjournal.dev/episodes/238.Follow @techleadjournal on LinkedIn, Twitter, and Instagram.Buy me a coffee or become a patron.
This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support. Why do today's LLMs forget key details over long context, and what would it take to give them real memory that scales? In this episode of Eye on AI, host Craig Smith explores Manifest AI's Power Retention architecture and how it rethinks memory, context, and learning for modern models. We look at why transformers struggle with long inputs, how state space and retention models keep context at linear cost, and how scaling state size unlocks reliable recall across lengthy conversations, code, and documents. We also cover practical paths to retrofit existing transformer models, how in context learning can replace frequent fine tuning, and what this means for teams building agents and RAG systems. Learn how product leaders and researchers measure true long context quality, which pitfalls to avoid when extending context windows, and which metrics matter most for success, including recall consistency, answer fidelity, task completion, CSAT, and cost per resolution. You will also hear how to design per user memory, set governance that prevents regressions, evaluate LLM as judge with human review, and plan a secure rollout that improves retrieval, multi step workflows, and agent reliability across chat, email, and voice. Stay Updated: Craig Smith on X:https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI
Rory and Drew return from Halloween with coffee, chaos, and a nerdfest on node-based creation. They speed-run Midjourney office hours, gripe about missing “make him smile” buttons, then crack open the new wave: nodes in Krea, Freepik Spaces, and Weavy...batching, branching, and wiring prompts like a patch bay. Drew admits he's been using v6 personalization inside v7 like a goblin. Rory shows how to spin one image into 20+ shots and auto-write video prompts, then turns pencil sketches into cinematic frames with structure-reference wizardry. It's equal parts workshop and roast of their past selves.--⏱️ Midjourney Fast Hour0:01 – "Tell your dog walker to subscribe” 1:08 – 55 episodes in: what Midjourney Fast Hours is really about3:25 – Midjourney Office Hours recap: dev updates, bugs, and feature requests5:02 – Multiple feature drops teased for next week6:39 – v7 release timing + hopes for a true creative studio UI9:02 – Wishlist: multi-character control, angles, expressions, and seed editing12:29 – Prompting real facial expressions (test simple → build complexity)15:13 – Pro tip: community rating = free Fast Hours learning16:02 – Hack: using v6 personalization codes inside v717:12 – The Node Revolution begins — why nodes fix creative workflow pain22:12 – Krea Nodes deep dive: blueprints, drag-to-wire, product-swap demo31:39 – Image-to-video inside Krea: turning stills into motion35:04 – Batch-generation magic: LLM → 10 prompts → parallel image runs43:07 – Weavy “app view” — simplified node interface for creators45:58 – Freepik Spaces walkthrough: collaborative canvas + node workflows48:25 – Quick win: “4 on demand” + unlimited Nano runs in Freepik49:18 – Rumor mill: Nano Banana 2 incoming50:25 – Seedream vs Nano: angle agility vs object consistency55:27 – Merch detour: Fast Hours T-shirt mockups built with nodes59:26 – Sketch-to-cinema using Mystic (Magnific) for structure-reference1:05:38 – Wrap-up: what's next for nodes and upcoming Midjourney updates1:07:08 – Tease: live AMA event coming in November
A shorter than usual episode about the future of the pod - 2026 and beyond. We will be continuing our support of the Oceania (formerly AusACPDM) conference, the EACD conference and the AACPDM conference in 2026 with in-person, on-site, live broadcasts from Australia, Europe and the Americas!2025 has also seen the team behind the pod launch the ResearchWorks Academy - an entirely FREE online portal for clinicians and researchers, designed to be a one-stop site for all your clinical application needs. You can register today for full access.From AI and ML driven toolsets, to reports, templates, flowcharts, decision trees, outcome measures and more - we are aiming to empower clinicians across the globe with the tools needed to implement evidence based practices. Let us know if you have any suggestions for the site and how we can continue to develop the resources available.On demand courses will also soon launch - we are working with international partners from across the ResearchWorks network to provide the very latest information, courses and educational tools too, so stay tuned!Visit www.researchworks.academy
00:00:00 – Scramble to air: dead car battery tale, housekeeping, and Ken Woods AI-EP status 00:04:54 – "Let's Get the Whole": Star Trek-flavored riff on "Meet Me Halfway" premieres 00:09:48 – Writing the parody: Calgon "take me away" angle, EP direction and tweaks 00:14:49 – Popular Mechanics piece: toward a unified theory of consciousness; EU Human Brain Project backstory 00:19:43 – "Electronic person" policy in EU and LLM introspective awareness experiments (subliminal "bread") 00:24:25 – Black-box LLMs and why self-reports aren't trustworthy; need transparent architectures 00:28:23 – New Yorker debate: "AI is thinking?"—parallels to human cognition and limits 00:32:45 – Embodiment matters: what models lack; scaling limits; why GPT responses "feel" different 00:37:40 – Star Trek's "Measure of a Man": Data's lived experience and the case for embodiment 00:42:01 – Blake Lemoine recap: the Lambda sentience flare-up and Weizenbaum's cautionary lens 00:46:40 – Rights for machines? Dog-level sentience analogy, UBI speculation, EU patents 00:51:34 – J6 pipe-bomber update: gait match claims, LE links, and motives debated 01:04:30 – Pandemic rewind: German PCR/antibody analysis claims and a SNAP/SCOTUS funding skirmish 01:14:06 – Bigfoot on I-80? Road-crossing "glide," possible intangibility; phone lines open 01:19:02 – Caller segment: dogman vs. bigfoot—malevolence, grudges, and one 1996 Glacier NP encounter 01:28:34 – News bed returns; "Penis Man" saga in Phoenix—folk-hero tagging and copycats 01:33:04 – More "Penis Man": suspects, merch, and why the meme spreads 01:37:52 – From tags to treats: Taco Bell's Mountain Dew Baja Blast pie appears 01:42:46 – Would you bring a Baja pie to Friendsgiving? Discord bounty offered 01:47:35 – Stupid criminals: driver tries a Monopoly "Get Out of Jail Free" card 01:57:37 – Viral glassware: that pricey Starbucks seasonal cup rabbit hole 02:00:06 – Wrap and reflections: AI takeaways, Bigfoot vs. dogman, and Baja-pie Thanksgiving dare 02:03:44 – Outro music and sign-off Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research ▀▄▀▄▀ CONTACT LINKS ▀▄▀▄▀ ► Website: http://obdmpod.com ► Twitch: https://www.twitch.tv/obdmpod ► Full Videos at Odysee: https://odysee.com/@obdm:0 ► Twitter: https://twitter.com/obdmpod ► Instagram: obdmpod ► Email: ourbigdumbmouth at gmail ► RSS: http://ourbigdumbmouth.libsyn.com/rss ► iTunes: https://itunes.apple.com/us/podcast/our-big-dumb-mouth/id261189509?mt=2
Thanks to everyone who participated in ACX Grants, whether as an applicant, an evaluator, or a funder. We received 654 applications this year, and were able to fund 42. To the other 612: sorry! Many of you had great ideas that we couldn't fund for contingent reasons - sometimes because we couldn't evaluate them at the level of depth it would have taken to feel comfortable supporting them, or because we had complicated conflicts of interest, or just because we didn't have enough money. Some of you had ideas that were good but not a match for our particular grantmaking philosophy. Finally, a few of you were suffering from LLM psychosis. Please get help. Of the 42 grantees, 40 have answered our email asking for confirmation that they still want the grant. I'm still waiting for confirmation emails from Lewis Wall and Nishank B. If you're reading this and don't think you got a confirmation email, check your spam folder. If it's not in your spam folder, email me at scott@slatestarcodex.com. If you can't reach me or I don't respond, DM me on Substack or Twitter. I'll give you until November 1 to get in touch, after which point the grant will be withdrawn. There are also a few projects so deep in stealth I don't have permission to share their existence; I will mention these as they become public. More information, and the all-important thanks to contributors, are after the list, which is:z https://www.astralcodexten.com/p/acx-grants-results-2025
En 2025 ya se nota que las respuestas de IA están guiando más búsquedas que ir directo a Google, y muchas veces se nutren de tu propio contenido. LLM.txt surge como una convención cada vez más utilizada para indicar a los bots de IA qué pueden hacer con tus páginas, sin reemplazar a robots.txt, sino complementarlo. Tú decides dónde trazar la línea entre visibilidad útil y abuso: qué se puede resumir, cuándo deben citar tu fuente y enlazarla. No se trata de bloquear todo, sino de convertir a las IA en aliadas que descubran tu valor sin perder el control. Y las reglas pueden servir para tres cosas clave: permitir resúmenes con citación, limitar el entrenamiento con tu contenido y exigir cita y enlace cuando se utilice un fragmento.Para verlo en acción, piensa en Verde Viva, una tienda online de jardinería con blog. Definieron un LLM.txt con reglas simples: permitir resúmenes de hasta 120 palabras y exigir un enlace clicable cuando se cite su contenido, manteniendo robots.txt intacto. En un mes empezaron a ver referencias desde asistentes con enlaces y un tráfico de referencia más cualificado, gracias a menciones que enlazan a su fuente. La idea central es clara: una política bien definida no bloquea todo, sino que guía a las IA hacia descubrimiento y atribución, convirtiendo a los asistentes en aliados. ¿Quieres probarlo? Define tu intención de negocio frente a la IA y escribe un primer borrador de LLM.txt con tres reglas básicas: qué se puede resumir, qué queda fuera y cómo debe citarse, y súbelo a la raíz de tu dominio para empezar a monitorizar.Conviértete en un seguidor de este podcast: https://www.spreaker.com/podcast/seo-para-google--1693061/support.Newsletter Marketing Radical: https://marketingradical.substack.com/welcomeNewsletter Negocios con IA: https://negociosconia.substack.com/welcomeMis Libros: https://borjagiron.com/librosSysteme Gratis: https://borjagiron.com/systemeSysteme 30% dto: https://borjagiron.com/systeme30Manychat Gratis: https://borjagiron.com/manychatMetricool 30 días Gratis Plan Premium (Usa cupón BORJA30): https://borjagiron.com/metricoolNoticias Redes Sociales: https://redessocialeshoy.comNoticias IA: https://inteligenciaartificialhoy.comClub: https://triunfers.com
Do This, NOT That: Marketing Tips with Jay Schwedelson l Presented By Marigold
Marketers keep saying the funnel is dead, but this chat actually explains what changed and what to do about it. You'll hear how to rethink content for 23-word questions, why website traffic is shrinking, and what to build instead, plus a hopeful take on AI that puts humans back in charge. And yes, Jay Schwedelson gets personal with Yamini Rangan about college drop-offs, plants that refuse to live, and the real reason personality now beats playbooks.ㅤFollow Yamini on LinkedIn and explore HubSpot's Loop playbook content and the HubSpot Media Network for practical examples you can borrow.ㅤBest Moments:(02:45) The college drop-off half-tear that turned into a full-on drive-to-the-airport cry.(05:01) Is the funnel dead or just changing shape as HubSpot shifts thinking toward a loop.(06:41) Eight out of ten Google searches end with no click, and what that means for your site.(08:50) Content has to answer specific LLM-level questions with citations and case studies.(12:52) Personality beats generic content as podcasts, YouTube, and newsletters win on trust.(16:15) AI won't replace humans; it finally makes one-to-one personalization at scale real.ㅤCheck out our 100% FREE + VIRTUAL EVENTS! ->Guru Conference - The World's Largest Virtual EMAIL MARKETING Conference - Nov 6-7!Register here: www.GuruConference.comㅤCheck out Jay's YOUTUBE Channel: https://www.youtube.com/@schwedelsonCheck out Jay's TIKTOK: https://www.tiktok.com/@schwedelsonCheck Out Jay's INSTAGRAM: https://www.instagram.com/jayschwedelson/
Adam D'Angelo (Quora/Poe) thinks we're 5 years from automating remote work. Amjad Masad (Replit) thinks we're brute-forcing intelligence without understanding it.In this conversation, two technical founders who are building the AI future disagree on almost everything: whether LLMs are hitting limits, if we're anywhere close to AGI, and what happens when entry-level jobs disappear but experts remain irreplaceable. They dig into the uncomfortable reality that AI might create a "missing middle" in the job market, why everyone in SF is suddenly too focused on getting rich to do weird experiments, and whether consciousness research has been abandoned for prompt engineering.Plus: Why coding agents can now run for 20+ hours straight, the return of the "sovereign individual" thesis, and the surprising sophistication of everyday users juggling multiple AIs. Resources:Follow Amjad on X: https://x.com/amasadFollow Adam on X: https://x.com/adamdangelo Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
New app features: listening history, continue listening, and transcript exports + navigating LLM-induced team drama.Chapters:[00:00] Welcome and business update[02:13] Metacast v1.25 Overview[02:50] New Feature: Listening History[08:08] New Feature: Continue Listening[12:41] New Feature: Exporting Transcripts[20:24] Website outage[22:21] The Pro Tier in v1.26[23:06] Team conflict: LLM miscommunication[31:21] LLM Etiquette in Teams[35:50] Podcast & book recommendations[45:34] P.S. We're YouTube stars (FWIW)LinksMetacast v1.25 blog postPodcasts:Tech Brew Ride Home Oct 16Scott & Mark: The AI productivity trapAmerican GodsThe SandmanDownload the Metacast podcast app for free:iOS: https://apps.apple.com/app/metacast/id6462012536Android: https://play.google.com/store/apps/details?id=app.metacast.podcast.player
** AWS re:Invent 2025 Dec 1-5, Las Vegas - Register Here! **Learn how Anyscale's Ray platform enables companies like Instacart to supercharge their model training while Amazon saves heavily by shifting to Ray's multimodal capabilities.Topics Include:Ray originated at UC Berkeley when PhD students spent more time building clusters than ML modelsAnyscale now launches 1 million clusters monthly with contributions from OpenAI, Uber, Google, CoinbaseInstacart achieved 10-100x increase in model training data using Ray's scaling capabilitiesML evolved from single-node Pandas/NumPy to distributed Spark, now Ray for multimodal dataRay Core transforms simple Python functions into distributed tasks across massive compute clustersHigher-level Ray libraries simplify data processing, model training, hyperparameter tuning, and model servingAnyscale platform adds production features: auto-restart, logging, observability, and zone-aware schedulingUnlike Spark's CPU-only approach, Ray handles both CPUs and GPUs for multimodal workloadsRay enables LLM post-training and fine-tuning using reinforcement learning on enterprise dataMulti-agent systems can scale automatically with Ray Serve handling thousands of requests per secondAnyscale leverages AWS infrastructure while keeping customer data within their own VPCsRay supports EC2, EKS, and HyperPod with features like fractional GPU usage and auto-scalingParticipants:Sharath Cholleti – Member of Technical Staff, AnyscaleSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/
Strategic Technology Consultation Services This episode of The Modern .NET Show is supported, in part, by RJJ Software's Strategic Technology Consultation Services. If you're an SME (Small to Medium Enterprise) leader wondering why your technology investments aren't delivering, or you're facing critical decisions about AI, modernization, or team productivity, let's talk. Show Notes "And we talk about that contract. We say, "this is your contract. This Open API definition that you have is the contract for your service." And in the end, that's how customers interact with Azure is through APIs. And so it's important to have that contract so that customers know how things work, how to use them, hopefully how to use them easily, right?"— Mike Kistler Hey everyone, and welcome back to The Modern .NET Show; the premier .NET podcast, focusing entirely on the knowledge, tools, and frameworks that all .NET developers should have in their toolbox. I'm your host Jamie Taylor, bringing you conversations with the brightest minds in the .NET ecosystem. Today, we're joined by Mike Kistler to talk about two topics (we usually only tackle one topic per episode, so you're getting a bonus with this episode): Open API and both MCP and the MCP SDK for C#. We started our conversation by focussing on Open API, as this is a passion of Mike's. We talked about what it is, how you've likely already been using it with any ASP .NET Core WebAPIs that you've worked on, and how the latest versions of ASP .NET Core can generate a lot of the Open API specification for you without having to add lots and lots of metadata an attributes. Pro tip: If you've been using the Swagger UI in your applications, you've been using Open API. "And when the LLM decides that it wants to use an MCP tool or access an MCP resource, it doesn't go and do that directly. It comes back to the MCP host and asks the MCP host to call a tool with a particular set of parameters, or to access an MCP resource. And at first, when I saw this in the MCP architecture, I thought, "boy, that's clunky. Why not have the LLM just call these things directly?" And there's a deliberate reason why it was done this way."— Mike Kistler We then pivoted over to talking about MCP (or Model Context Protocol) which is a rapidly evolving standard for creating your own agents and applications which can communicate with or be instructed by, LLMs. We talked about how the MCP standard works, and how the standard is written in such a way that there's always a human in the loop. We also talked about how you can build your own MCP servers using the MCP SDK for C#. It's worth pointing out that both MCP and Open API are evolving standards. While Open API tends to evolve with a much more relaxed pace, the MCP standard (having not even reached a year old when we recorded) uses the date as it's version number. And Mike actually references the latest version of the MCP spec in our conversation, which will give you a clue as to when we recorded it. Before we jump in, a quick reminder: if The Modern .NET Show has become part of your learning journey, please consider supporting us through Patreon or Buy Me A Coffee. Every contribution helps us continue bringing you these in-depth conversations with industry experts. You'll find all the links in the show notes. Anyway, without further ado, let's sit back, open up a terminal, type in `dotnet new podcast` and we'll dive into the core of Modern .NET. Full Show Notes The full show notes, including links to some of the things we discussed and a full transcription of this episode, can be found at: https://dotnetcore.show/season-8/building-the-future-of-apis-mike-kistlers-insights-on-openapi-and-mcp Useful Links: OpenAPI API Blueprint RAML ProducesResponseType attribute Minimal API TypedResults S07E16 - From Code to Cloud in 15 Minutes: Jason Taylor's Expert Insights And The Clean Architecture Template GitHub MCP Server MCP Transports MCP C# SDK Current version of the MCP spec as of the date of recording (aka version 2025-06-18) Microsoft MCP Servers List Mike on LinkedIn .NET Community Standup Supporting the show: Leave a rating or review Buy the show a coffee Become a patron Getting in Touch: Via the contact page Joining the Discord Remember to rate and review the show on Apple Podcasts, Podchaser, or wherever you find your podcasts, this will help the show's audience grow. Or you can just share the show with a friend. And don't forget to reach out via our Contact page. We're very interested in your opinion of the show, so please get in touch. You can support the show by making a monthly donation on the show's Patreon page at: https://www.patreon.com/TheDotNetCorePodcast. Music created by Mono Memory Music, licensed to RJJ Software for use in The Modern .NET Show. Editing and post-production services for this episode were provided by MB Podcast Services.
Welcome to The Chopping Block — where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. This week, the crew breaks down DeFi's Black Friday: a brutal week that saw the $120 million Balancer v2 hack, the collapse of Stream Finance, and a market-wide panic that reminded everyone — nothing in crypto is risk-free. They dive into how one of DeFi's oldest, most audited contracts failed, why smaller chains froze or rolled back transactions, and what it means for decentralization as Berachain, Sonic, and Polygon took emergency action. The panel debates whether the Balancer attacker used an AI “vibe-coded” exploit, how Ethereum might one day face its own rollback dilemma, and why privacy chains like Zcash may be the last true cypherpunk strongholds. In the second half, they unpack the off-chain losses behind Stream Finance's XUSD blow-up, the contagion risk across Euler, Silo, and Morpho, and the hard lessons for “yield-chasing” DeFi vaults. The gang closes with advice for founders weathering the storm — from Tarun's “cockroach mindset” to Haseeb's reminder that crypto's long-term fundamentals haven't changed. Whether you're building in DeFi, securing smart contracts, or surviving the next credit unwind, this episode lays bare the harsh truths — and enduring resilience — of crypto's frontier markets. Show highlights
A CMO Confidential Interview with Mike Walrath, Chairman and CEO of Yext, Inc., formerly CEO of Right Media, and SVP at Yahoo! Mike discusses what he believes is the collapse of the marketing funnel, the need to understand how AI consumes data while judgement stays with consumers, and how an "influence marketing" mindset is emerging. Key topics include: why CMOs will need to be both great brand strategists as well as scientists, the need to constantly distribute information and "tend it like a garden," and why Reddit is great for training AI, but not as important in building brand influence. Tune in to hear a story about why you shouldn't let ChatGPT talk in an unsupervised forum and why Land Rover should send me a polo shirt. This week, Mike Linton sits down with Mike Walrath, Chairman & CEO of @yext (and founder of WGI Group), to unpack why the classic awareness–consideration–conversion funnel is collapsing—and what CMOs must do next. From zero-click discovery and AI agents “front-ending” consumers to why structured first-party data now beats pretty websites, Walrath maps the new rules for brand, distribution, and measurement in an AI-led marketplace.We cover: how consideration gets outsourced to AI, why marketers will “market to agents” (without controlling the ad copy), the coming arms race in citations and data distribution, and what organizational fixes boards and CMOs should make now. If you own brand, growth, or P&L accountability, this is a playbook for the next chapter.**Sponsor — @typefaceai Typeface helps the world's biggest brands move from brief to fully personalized campaigns in hours, not months. With its agentic AI marketing platform, one idea scales into thousands of on-brand variations across ads, email, and video—integrated with your MarTech stack and secured for the enterprise. See how brands like ASICS and Microsoft are transforming marketing: typeface.ai/cmo.Highlights* Why “zero-click” compresses awareness and consideration inside AI experiences—and how to win the AI bake-off.* The end of marketer-controlled ad copy; influence shifts to data quality, recency, and distribution.* Memory and context change everything: agents know the consumer—and your brand—better than you think.* Brand matters more, not less; without brand salience you won't make the answer set.* From content to data: make every spec, price, menu, inventory, policy, and promo machine-readable and syndicated.* Citations, not vibes: first-party sites and listings dominate AI references; keep them fresh and authoritative.* Org design: hire the data athletes, upgrade infrastructure, and instrument real conversion milestones (tests, visits, units).New episodes every Tuesday on YouTube, Apple, and Spotify. If you find this useful, please like, subscribe, and share with your team.**Guests**Mike Walrath — Chairman & CEO, Yext; Founder, WGI Group.Host: Mike Linton — former CMO of Best Buy, eBay, Farmers Insurance; former CRO, Ancestry.CMO Confidential,marketing,CMO,chief marketing officer,AI marketing,agentic AI,marketing funnel,zero click,search,SEO,GenAI,LLM,brand strategy,performance marketing,Yext,Mike Walrath,Mike Linton,customer journey,personalization,content at scale,structured data,citations,data strategy,MarTech,go to market,GTM,board strategy,enterprise marketing,retail,automotive marketing,restaurants,media,advertising,Typeface sponsor,Typeface AI,typeface.ai/cmoSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
AI-powered web browsers are hitting the scene fast, but Steve and Leo unpack why these smart assistants could usher in an era of security chaos most users aren't ready for. Brace yourself for the wild risks, real-world scams, and the privacy questions no one else is asking. Secret radios discovered in Chinese-made busses. Edge & Chrome introduce LLM-based "scareware" blocking. A perfect example of what scareware blocking hopes to prevent. Aardvark: OpenAI's new vulnerability scanner for code. Italy to require age verification from 48 specific sites. Russia to require the use of only Russian software within Russia. Russia further clamping down on non-MAX Telegram and WhatsApp messaging. 187 new malicious NPM packages. Could AI help with that? BadCandy malware has infiltrated Australian Cisco routers. Github's 2025 report with the dominance of TypeScript. Windows 11 gets new extra-secure Admin Protection feature. A bunch of interesting feedback and listener thoughts. And why the new AI-driven web browsers may be bringing a whole new world of hurt Show Notes - https://www.grc.com/sn/SN-1050-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT canary.tools/twit - use code: TWIT bigid.com/securitynow threatlocker.com for Security Now
AI-powered web browsers are hitting the scene fast, but Steve and Leo unpack why these smart assistants could usher in an era of security chaos most users aren't ready for. Brace yourself for the wild risks, real-world scams, and the privacy questions no one else is asking. Secret radios discovered in Chinese-made busses. Edge & Chrome introduce LLM-based "scareware" blocking. A perfect example of what scareware blocking hopes to prevent. Aardvark: OpenAI's new vulnerability scanner for code. Italy to require age verification from 48 specific sites. Russia to require the use of only Russian software within Russia. Russia further clamping down on non-MAX Telegram and WhatsApp messaging. 187 new malicious NPM packages. Could AI help with that? BadCandy malware has infiltrated Australian Cisco routers. Github's 2025 report with the dominance of TypeScript. Windows 11 gets new extra-secure Admin Protection feature. A bunch of interesting feedback and listener thoughts. And why the new AI-driven web browsers may be bringing a whole new world of hurt Show Notes - https://www.grc.com/sn/SN-1050-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT canary.tools/twit - use code: TWIT bigid.com/securitynow threatlocker.com for Security Now
AI-powered web browsers are hitting the scene fast, but Steve and Leo unpack why these smart assistants could usher in an era of security chaos most users aren't ready for. Brace yourself for the wild risks, real-world scams, and the privacy questions no one else is asking. Secret radios discovered in Chinese-made busses. Edge & Chrome introduce LLM-based "scareware" blocking. A perfect example of what scareware blocking hopes to prevent. Aardvark: OpenAI's new vulnerability scanner for code. Italy to require age verification from 48 specific sites. Russia to require the use of only Russian software within Russia. Russia further clamping down on non-MAX Telegram and WhatsApp messaging. 187 new malicious NPM packages. Could AI help with that? BadCandy malware has infiltrated Australian Cisco routers. Github's 2025 report with the dominance of TypeScript. Windows 11 gets new extra-secure Admin Protection feature. A bunch of interesting feedback and listener thoughts. And why the new AI-driven web browsers may be bringing a whole new world of hurt Show Notes - https://www.grc.com/sn/SN-1050-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT canary.tools/twit - use code: TWIT bigid.com/securitynow threatlocker.com for Security Now
AI-powered web browsers are hitting the scene fast, but Steve and Leo unpack why these smart assistants could usher in an era of security chaos most users aren't ready for. Brace yourself for the wild risks, real-world scams, and the privacy questions no one else is asking. Secret radios discovered in Chinese-made busses. Edge & Chrome introduce LLM-based "scareware" blocking. A perfect example of what scareware blocking hopes to prevent. Aardvark: OpenAI's new vulnerability scanner for code. Italy to require age verification from 48 specific sites. Russia to require the use of only Russian software within Russia. Russia further clamping down on non-MAX Telegram and WhatsApp messaging. 187 new malicious NPM packages. Could AI help with that? BadCandy malware has infiltrated Australian Cisco routers. Github's 2025 report with the dominance of TypeScript. Windows 11 gets new extra-secure Admin Protection feature. A bunch of interesting feedback and listener thoughts. And why the new AI-driven web browsers may be bringing a whole new world of hurt Show Notes - https://www.grc.com/sn/SN-1050-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT canary.tools/twit - use code: TWIT bigid.com/securitynow threatlocker.com for Security Now
AI-powered web browsers are hitting the scene fast, but Steve and Leo unpack why these smart assistants could usher in an era of security chaos most users aren't ready for. Brace yourself for the wild risks, real-world scams, and the privacy questions no one else is asking. Secret radios discovered in Chinese-made busses. Edge & Chrome introduce LLM-based "scareware" blocking. A perfect example of what scareware blocking hopes to prevent. Aardvark: OpenAI's new vulnerability scanner for code. Italy to require age verification from 48 specific sites. Russia to require the use of only Russian software within Russia. Russia further clamping down on non-MAX Telegram and WhatsApp messaging. 187 new malicious NPM packages. Could AI help with that? BadCandy malware has infiltrated Australian Cisco routers. Github's 2025 report with the dominance of TypeScript. Windows 11 gets new extra-secure Admin Protection feature. A bunch of interesting feedback and listener thoughts. And why the new AI-driven web browsers may be bringing a whole new world of hurt Show Notes - https://www.grc.com/sn/SN-1050-Notes.pdf Hosts: Steve Gibson and Leo Laporte Download or subscribe to Security Now at https://twit.tv/shows/security-now. You can submit a question to Security Now at the GRC Feedback Page. For 16kbps versions, transcripts, and notes (including fixes), visit Steve's site: grc.com, also the home of the best disk maintenance and recovery utility ever written Spinrite 6. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT canary.tools/twit - use code: TWIT bigid.com/securitynow threatlocker.com for Security Now
ElevenLabs CEO and co‑founder Mati Staniszewski joins Jennifer Li to explain how the team ships research‑grade AI at lightning speed—from text‑to‑speech and fully licensed AI music to real‑time voice agents—and why voice is the next interface for human‑computer interaction. He shares the small, autonomous team model, global hiring approach, and how the Voice Marketplace has paid creators over $10M while evolving into an enterprise platform. Resources:Follow Mati on X: https://x.com/matistanisFollow Jennifer on X: https://x.com/JenniferHli Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Scott and Wes dive into Remix 3, exploring how it embraces native web standards like Events, Signals, and Streams to become a truly full-stack framework. They unpack what “LLM-ready,” thin APIs, and a standards-based approach mean for the future of web development. Show Notes 00:00 Welcome to Syntax! 03:21 Uses the platform - native Events, Signals, Streams, Fetch 04:16 Remix 3, Fully Fullstack. 04:57 LLM‑ready + thin APIs 05:53 Brought to you by Sentry.io. 06:18 My previous predictions. 07:44 The value of ‘Standards Based'. 09:13 Component model - JSX/TSX; state = variables; call this.render() 11:56 Adding reactivity to Remix. 15:15 Event‑based architecture - custom events, EventTarget, interactions 20:52 Context & type‑safe access. 22:46 Composing interaction logic within events. 24:25 Signals - AbortSignal to cancel async ops 25:21 Benefits of standards - bring your own tools/libraries Michael Asnong X Post. 26:42 CSS - built‑in CSS prop; Svelte‑like scoping 28:34 Server - Web Request/Response, Web Streams across runtimes 31:23 Frames - async URL‑addressable components with fallbacks 33:07 Tooling - ESM; use Vite or esbuild 34:47 Routing - code‑based named routes 35:57 Questions/Concerns - manual rendering vs reactivity 38:47 URL Pattern API - modern, fast routing foundations 41:33 Sick Picks + Shameless Plugs. Sick Picks Scott: MoCA 2.5 Network Adapter Wes: Bosch Dishwasher Shameless Plugs Scott: Syntax on YouTube. Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads
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