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Dave Goyal, Founder and CEO of Think AI Corporation, is driven to Turn Disabilities into Unique Abilities by using technology to empower disabled entrepreneurs and help businesses unlock the value of their data. After contracting polio as an infant, Dave transformed physical limitations and early adversity into a passion for solving business problems, building companies, and giving back to society. Through Think AI, he helps manufacturing and healthcare leaders use data and AI to generate real-time insights, improve productivity, reduce costs, and create new opportunities for growth. In this conversation, Dave introduces The 3G AI Augmentation Framework—Gap: Where are we losing time, quality, ability, or capacity? Grow: Apply AI to augment people and improve that work. Glow: Institutionalize the solution so humans and AI collaborate effectively. Dave also shares how his private second brain and AI executive agents save him up to 80 hours per month, why human control and security must remain central to AI adoption, and how authority, trust, people, customers, and culture drive business growth. He also discusses his book, Real-Time Business Intelligence Mastery, and his vision for creating a venture studio for disabled entrepreneurs. — Turn Disabilities into Unique Abilities with Dave Goyal Good day. Steve Preda here with The Management Blueprint. And today my guest is Dave Goyal, the founder and CEO of Think AI Corporation, which helps CTOs and CIOs in manufacturing and healthcare turn siloed data into real-time insights and automation, creating reduced downtime, increased efficiency, and going from weeks to days in project launches. Dave, welcome to the show. Thank you for having me, Steve. Well, I’m really curious to learn about you and your company, Think AI Corporation, but first I’d like to ask you about your personal why and how you are manifesting it in your business. So thank you again, Steve. I’m really excited to be on your show. I’m in the data and AI business, and really tech innovation, for the last 30 years. In this particular company, Think AI, I have a partner, Manish Bhardia, and we both have been working very actively with Microsoft partners, the Microsoft ecosystem, and implementing data and AI solutions for midsize companies and manufacturing companies. You went on why, which is amazing. My why: I’m a disabled entrepreneur. I have this hunger for building businesses. I’ve built nine businesses. We can talk about it later. And five of them were miserable failures in my books. Not all of them were that miserable, as I say. But five of them were failures, and I learned a lot from them. And I’m really motivated now to expand it further, to give back to small businesses. We’ve been working with midsize and enterprise clients, but to midsize companies, and then motivate—I have a 15-year-old kid—so motivate young people and also small businesses to make use of the power of their own data and use and consume AI on a day-to-day basis. That’s my why. Wow. So, to learn the power of their own data and use AI, why is this important to you? The main reason is I am passionate about technology. Everybody is good at something. I am really good at solving business problems using technology. Being a disabled entrepreneur, I did not have a lot of luxury initially, even walking. Eventually, I started using braces, started going to different countries. So the passion became really the source of energy and motivation, and that passion is now going to a level where I want to motivate people like me who are disabled entrepreneurs and want to go into this kind of business. So my real passion is technology and giving back to society using technology, to sum it up. Wow. So you mentioned this disabled entrepreneur. I’ve never heard this term. I mean, you talk about minority entrepreneurs, women entrepreneurs, you know, veteran entrepreneurs, and actually the government recognizes these categories, but I never heard about disabled entrepreneurs. So would you mind sharing a little bit about what happened to you and how you got into this entrepreneurship? Sure, yeah. And that’s really good, by the way. I don’t see anybody else using that term but me, so probably I should keep it with me as a copyright term. Just joking on it. But having said that, every disability brings some kind of ability. That’s why sometimes they call it differently abled. When you have these abilities, you don’t know the source or the channels to use them. So, for example, blind people, they may have a lot of great listening power. That’s why they are into music most of the time. Sometimes they have amazing reasoning and critical-thinking power, but they don’t know how to channel it, so they fight on a day-to-day basis with these issues. Bringing it back to me, I have polio. When I was six months old, I got hit by the polio virus. Initially, for a few years, I had to just lie down on the bed, had a lot of physical therapy. Then I was able to get up and sit, at least. Then my father was carrying me to school, and I could see the kids were going out and playing. I got beaten up because of that, too, because kids don’t understand. No fault of theirs that I’m not throwing the ball at them and they are playing. And so that brought a lot of negativity in me. Eventually, my grandfather and my father helped me get over that, and I started channeling that into building businesses. So I started teaching music. I learned music through some of my friends. I started teaching music during my college days and started making money. And I had a blind friend, and he needed money because he was abandoned by his parents, so I had to help him out. I started making some money. I was doing well with my family, so I could just pay everything back to him. So that seed got planted there, and I didn’t know what to do back then, right? Still a 14-, 15-year-old kid or a teenager, in this case. So I started getting into that mindset of, how about I build businesses for me and then start helping out the community? I’m still not there yet. I’m going towards helping that community. But I want to identify disability in three ways, not just physical. So those three are physical, but the bigger one is mental. A lot of people are really mentally blocked, and you see people, you know, “Oh, I can’t change anything in my life.” People die by suic*de. Kids get into depression. This is a form of disability, by all means. I don’t think education, parents, and community are doing so much about that other than having a cliché thing that, “I was a victim of depression, so I’m doing that,” just to show off. But really, to help out the community in a methodical manner, that doesn’t exist. Second, physical disability, like I said, given by God sometimes, like war veterans and others, then you feel really limited. So what to do with that? And I come into that category, so I know that really well. Third is financial disability. So a lot of financial disability is in the mind, too. I’ve heard a phrase called, “You don’t die by hunger; you really die by indigestion.” So you would find ways and means to make money even if you’re a completely disabled person. So I don’t think finance is an issue in general. So these three areas, to me, are the real disability areas. I’m obviously only working on one today, which is physical disability: how to identify the potential of people who can create something different within that limitation and then make a change in the world. So that’s the motivation. That’s my Life 2.0, where I’m moving now. Love it. Love it. So how did you have time to build nine businesses? I started it in 1993, ’94, I believe, or ’95, I think. And they’re one at a time. Today I have about three. I sold one. And yeah, I did not have time. One of the big challenges when I built these three in the last six, seven, eight years, the biggest challenge I faced is I do not have time for working with customers, which I love to do—talking and listening to their business problems, solving those problems. I end up doing a lot of operational work. Post-2020, and it’s a very blunt thing to say, people got lazy. They want to change jobs, make more money, do moonlighting, do multiple things, but not work hard like we did back in the days. And that kind of pushed all of us small businesses to do a lot more management of resources, especially human resources, in a distributed environment. I have teams in India, the Philippines, Canada. So that became a bigger challenge. But having said that, AI came as a savior. In the last 18 months, AI has changed quite a lot. And if you don’t go into a debate of whether AI is good or bad, or you’re a skeptic or an enthusiast, AI can really help you if you really put together how it can help you. It should not replace you, but it should give you an additional helping arm. In my business, I started deploying C-suite. So I still have a VP of operations. My business partner is into sales. But then I started filling in other functions, like a fractional CFO, as an example. My fractional CFO is monitoring my top line and bottom line. I call him Felix. I have to give names to AI agents. So Felix is actually looking on a weekly basis at what invoices are billed, if we have vendors or employees, what we need to pay, where our expenses are going, what’s the monthly or maybe six-month cash flow run. Are we within limits? Do we have borderline cash availability so that we can survive? So it started to do a lot of things. But not only that, because we are feeding our own data, our own mind, I have built my own second brain. It started to read off of that and started giving me insights that a human would not give me. And even if I hire a fractional CFO, he will only hear what I have to say, look into some of my books, and then give me some blanket suggestions. Here, this is really tailor-made to our problems, our situation, and it worked phenomenally well. So I’m building that as a product now. It’s not done yet. Then I also deployed my own CMO called Sasha, and she started to look into my marketing angles, my branding, my voice, my identity. I love writing, but now AI can help me—not just create a blanket AI post or something, but really read how I write, what I write. So I create ideas. It helps me research, does a factual check on it. So I give 100 words. It can take those ideas and then expand into newsletter articles or a big campaign. I can start building different case studies for our customers, proof of concept, building podcasts such as these. So this started freeing up—I only talked about two executives, and I have seven of them—but they started to help me free up my time. And believe it or not, I am getting about 40 to 60 hours, and in good months, about 80 hours per month. So 30 to 50% of my regular time is freed up. So that time is now going into this movement that I’m thinking about, which is disabled entrepreneurship. Wow, that is impressive. So tell me a little bit about this. This is a podcast of frameworks. So do you have a framework for maybe launching an AI agent like that? I definitely do, and I want you to expand on it. But in terms of what I have, I look into three things. Where is the gap in terms of human? Where I see either performance issues, quality issues, or availability and capacity issues. So what are those things which don’t hit my security side of things, don’t interact with my customer, and still help me in my operations? That’s the gap we look into. How can we use and fill that gap to grow what we need to work on? And then last, so I use three Gs with my last name, Goyal, right? So Gap to Grow to Glow. So now how can we use this in our business to glow and create an environment where even humans can interact with this AI persona? So we are always big on human-in-the-loop or human-in-control with any AI solution. So it always starts with the gap. Where is the gap? Where is it taking time from one of the human sides of our team? I like that. I like that you isolated those things which are less risky to develop, because I think a lot of people are held back by this idea that it’s a black box, you don’t know what you’re getting into, you don’t know what you don’t know, and it’s risky, and then they don’t do anything. But you actually isolated that customer interaction is a risk you don’t want to live with right now, and security is another one you don’t want to, which, I mean, it’s obvious. But if those are not hurt, then really what is the risk you’re running? So I like it. So how do you fire up an AI agent like that? So in terms of technology, I’m using a few things. I’m using Claude Code, the full Claude environment. So we build it off of that. Back in my days, I worked as a white-hat hacker, so the security angle we mentioned, I’m always so worried about hacking and security. So I have a completely isolated environment at my home on a Mac Mini, a really powerful Mac Mini, and that cannot go out on the internet and do things. And nobody can inject anything. But then I still need to feed information to it, so I have another machine where the only job of that machine is to provide information to this system. So I have my own second brain mapped into Obsidian, which is a note-taking application, but it’s really organized. So I first fed all my knowledge. I’ve recorded lots and lots of audios and documents, and it has learned. So I built that system first, like Dave’s second brain. And my second brain has learned everything about me. Nobody can see it but me. That’s my initial basis, right? After that, I built a working memory for my agents, for my company, and I’m doing it for one company at a time. Think AI is not completely live on the system, but Data & AI Studio is, which is a solo entrepreneurship business that I have. It is learning everything about that business as we speak. Even the transcripts from these podcasts and other places go into it, and it learns from it. There will be some insights which it will find, so it retains them. So Claude Code, Mac Mini, Obsidian—these are the basis. And then I’ve deployed my own personal models, like DeepSeek, and that is sitting locally on that machine. So the model is local. The downside is it’s not getting updated, so I only update it when I feel that it’s right. Not risk, it’s really the downside. There’s no risk in it. So you’re not on the latest and greatest, but you don’t have to be on the latest and greatest all the time. So Claude Code is on the latest and greatest, but when we deploy, it may not apply certain features that Claude Code is making available. And that’s fine. That’s the risk I’m taking. That’s the trade-off I’m taking. And the system is working great for the last six months. In the last 18 months, even though I started AI about 28, 30 years ago, the last 18 months is when I learned the new-age AI, and the last six months is when I started building this in an iterative manner. And it is pretty stable now. It can do a lot of things like I mentioned. So your agents are running on your Mac Mini off the grid? Yes. And then you’re feeding information with another computer to it to essentially give them the raw material from which they can build stuff, right? Right. A good example there, if I may expand: we use QuickBooks in our accounting system. It cannot read QuickBooks directly, but we, being a Microsoft partner, understand technology. I can write a job which can push data into the Mac Mini. It doesn’t read off of it. My Mac Mini, which has the agent, doesn’t know where that data has come from. It has the data, so it’s already synthesized. It cannot communicate with others. So that’s the calculated risk we take, right? Getting the data from one angle, one way, and then it’s synthesizing and analyzing data and getting insights out of it. So that’s the balance of systems that I have. I love it. That’s very clever. And what is your main business anyway? Because you talk about three businesses right now. What is your core business? What is your flagship business? The flagship business is Think AI. It’s a consulting organization, a three-time Inc. 5000 winner in terms of growth. We have our own team, but then we also use a lot of vendors which are qualified by us throughout the world. And we are Microsoft Advanced Specialization partners. What that means is we are in the top 2% of the worldwide partners within the Microsoft ecosystem, which is about 500,000 partners. And we work mainly with midsize manufacturers, and sometimes healthcare if they are okay and open to AI, and if not, data. So we go in there, look into whether they have a data and AI strategy. If they do, we work on their initiatives. If they have the initiatives. If not, we create the initiatives for them by doing some POCs and whatnot. And once we get engaged, we do deliverables like consulting services. But it’s not like typical consulting services where you place a resource. It’s really a value-based delivery model where we try to understand two business imperatives. One is what can help them make more revenue. And if we cannot find that, what can help them be more productive and have cost-cutting in one way or the other. So these are the two main business imperatives we work on. When and if we align with that, then we give them a roadmap, a phase-wise approach, which they can do with us or with somebody else, and then we keep delivering on it. So that’s the whole model. So what drives growth in the Think AI business? I mean, finding more customers, to say the least. And that becomes difficult because today everything is becoming a commodity. So one good learning, by the way, I need to share with the audience here. When you’re a small business, you think your brand is the value that you have. It’s the founders who are the brand. So it’s Manish and me. Manish, my business partner, is really big in productivity, project management, and that kind of thing. And I’m really good at building solutions using tech. And together we have about 55 years of experience. And then our key team members are ex-Microsoft or MVPs, Microsoft Most Valuable Professionals. So we hire a really strong key team. And the team below, we can either fill with our members, hire our own members, or go to the vendors also, and we tell it to our clients also. So our delivery model is we are the ones who are delivering. The guarantee is taken by Manish and Dave, not by Think AI. We have gotten into that situation. We are about 95% successful, so there’s a 5% failure. And the failure is either because we have the wrong team member, the communication between the client and us was not clear, the scope was not clear, the definition of value and done was not clear, and we have learned from it. So our business model is towards that, and that brings us growth because we work with a number of partners. Manish is part of a lot of Microsoft channel partner networks. We provide complementary services to those partners. So one channel is we work with a lot of partners because the trust is there. Authority and trust are the two factors we have understood which establish your business, and it’s the founders’ authority and trust, not the company. Company will build on its own. So we started building our own authority and trust, and that gets us growth. It’s not at the level we’d like, but we are happy. You are happy. Okay. So what is your vision? What would you like to make out of this? So we have an exit plan, at least on Think AI. And like I told you, Manish has his own. That is up to him. For me, I want to create this venture studio for disabled entrepreneurs, get the funds from here, and then harvest, go across the world. So three hobbies I have. One is travel. Second is reading, writing stuff, books. And third is music. And entrepreneurship comes in this whole surroundings, in this whole ring, so it’s the foundation of it. So we’re going to build this disabled entrepreneurship venture studio with a little bit of funds from our exit, and hope to grow there and hope to retire or die with that thinking. Love it. Love it. It’s fascinating. So you have a book that is on your LinkedIn page, Real-Time Business Intelligence Mastery. So tell me about this book. Why did you write it, and what’s it about? Sure. So we went into a coaching program. Up until 2022, we were arrogant enough to say, “Oh yeah, we can do everything on our own.” And then slowly we realized we need help, and we started taking help. We went to a couple of coaches in India where they were coaching us either on how to manage operations and operational excellence, and then another coach who’s like a life/building-your-brand marketing coach, and he inspired us to write a book. Now, I’ve been writing in my own native Hindi language, songs and compositions, but writing a book was a dream, and I thought it’s a big undertaking. But with their little bit of motivation and help, not in writing, but in the angle of what a book can bring. So I have a lot of experience working in midsize manufacturing organizations, working with CTOs and CIOs, and business intelligence is delayed. So it’s either a one-day delay or a week delay or a month delay, and it’s more reactive in nature. So the book was more about how you can build a real-time business intelligence culture so that you can get the insights from your data, make actionable insights, take actions on it, and grow your business for those two imperatives I talked about, which is grow your revenue or increase your productivity and decrease your cost. So are you writing about some of the things that you talked about? Leveraging AI, building AI agents? It has more about—so I wrote it in 2022, I believe. It has a lot more detail about. AI was not as popular, right? I mean, I did write about AI in it, but it was more about building a data culture than AI. It does talk briefly about AI because real-time is going very closely with AI. That’s the enabler for AI insights or data insights through AI. So it does talk a little bit about AI, but it talks more about tech leaders like CIOs and CTOs. What do they need to do? How do they need to build a culture around harvesting data, bring the data, build the team, where to take it? So it has those details. Okay. That’s fascinating. Who is this book for? Is it for founders? Is it for C-level executives? Who is the target? Like I said, it’s for tech leaders, CIOs, and CTOs of midsize organizations. Okay. That’s awesome. And these are the people that are your target customers as well at Think AI? Yes. That’s our true ideal client profile too, and that’s whom we have worked with all our lives. So they’re close friends, target audience, and customers. Future customers and current customers. All in one. All in one. That’s so nice when you write a book to your friends. That’s a very cool concept. So let me ask you this, Dave. If you had a magic wand, you’ve done a lot of things in your business, you built nine businesses. You learned from some of the failures that you had, which is part of entrepreneurship, and now you created AI agents, and then you have a second brain, and you’re leveraging all that technology. So if you had a magic wand and you could fix one thing in your business in the next 12 months, what would that be? I wish I had more senior leadership. Any business works with delegation. We have a couple who are really amazing, and they wear a lot of hats. But growth depends on three things, right? Being in front of the right customer, having the right team, and having the right product. Our product is people, unfortunately and fortunately. Customers, we are very happy and excited, and they trust us. We know how to get to them. We know how to create value for them. We are very satisfied. Everybody would say, “I need more customers,” and we would do that too. But I think more important is what product you are offering. So then people are what we are offering, and we are competing against big ones like Accenture and Avanade and Cognizant of the world in our business, the tech consulting business. But then we are not competing against cost; we are competing against value. So how do you create value? You find a valuable customer. They understand our language. The next level is, where is the product, which is the people? And that management becomes quite difficult. And harvesting and getting the right people in place is a job by itself. So kudos to those large companies if they’re harvesting one, although that’s debatable because when we go to the client, they complain a lot about their resources as well. So harvesting the right product and the right team is the key. And how do you do that? If you have the right leaders on top. Two partners alone cannot do that. So building more leaders underneath is the key. We are able to build a few, and I wish we could build a lot more. So when you have the right core team, your growth comes in, is my belief system. It could be different for everyone else. No, I think it’s a very deep insight, and very few people actually talk about this idea that the purpose of a business, especially in today’s AI age, is to build leaders. That’s your purpose, because people will take care of everything. They’re going to run your AI agents. They’re going to manifest your vision. But you can’t have just AI agents in a company, right? Because then the mental load is so much on the leader, and then the single-person dependency becomes critical. So is this what you mean by this? Where do you come from with this idea of harvesting people and leaders in the business? Absolutely. You said it well. Building leaders doesn’t just apply to an organization, whether small, medium, or big, but even to countries. If you don’t have the right leaders in place, it’s going to bite you back. And all cultures, some of the top management consultants will teach you to go into succession planning. That is what they really mean by that. It’s not succession planning by, okay, replace a CEO with a CEO. It’s the mindset. Apple is a great example of it. Steve Jobs hired Tim Cook from Compaq, from that world, and he had that vision. Obviously, he had a mission, but he had the vision—who to take, where to take, and what they would do. And that legacy continues even today. So Apple didn’t change a single bit in their model. And people would argue and debate, and that’s fine. But when I see it from my eye, he built a great leader. When he did that, the company stayed the same, right? So it’s not about what products Apple is creating today, whether it’s iPhone or iPad or Apple Vision Pro or some of the other things that they are doing, but it’s really that leader. Same thing went with Google, or Microsoft, Satya Nadella. And you see the right leaders were built by these founders. And by any means, we are not that big, and hopefully we can get to some place which is pretty good in our books. But finding and building the right people, it gives you a lot of satisfaction, happiness, bliss, if you can give it back to somebody who’s capable enough. And I’m always in hunt of the right people, building the right team in place. It’s so interesting you mention Apple because when Isaacson came out with the Steve Jobs biography, he said, basically, I think it’s in the preamble of the book, that Steve Jobs wanted people to remember him not for the products that he created, but the company. So his biggest contribution was creating a company. And I didn’t get what he meant by it. But if you witness the last—since he died 13 years ago—the last 13 years, this company has gone from strength to strength. Ninety percent of its market capitalization has been created since he died, right? So it keeps growing and keeps going from strength to strength, and that is the culture and the people that he built. This is the company he built. So it’s quite an amazing idea. I was about to comment on company. Something came back to me or reminded me that companies generally build on three pillars: customer, people, and culture. And if you don’t have the right balance of it—so, the right people, but if you don’t have the right culture, they’re going to run away. If you don’t have the right customers, you should have the ability to say no to certain types of customers too. Like Apple never targeted small, cheap products. And when I say cheap, meaning which doesn’t have the right quality in place, not about the cost. It’s always cost versus quality. So they have really struck the right balance in those three angles, and I think that’s the right way to do it. Some are able to do it, some are able to push through to do it, and some are not. But that’s where I think the focus needs to be if you are a founder. Find that right balance of people, client or customer, and culture. Yeah. And that is your core values too. Yeah. I agree with you. That’s wonderful. If you are listening to this conversation with Dave Goyal, and you would like to learn more about him and what he does and Think AI Corporation, where should our listeners go to learn more? Thank you for this opportunity, first of all. And people can find me on LinkedIn by my name, Dave Goyal. I’m very active there. I recently started a YouTube channel with the name Dave Goyal, so you can find me on YouTube. And mainly on LinkedIn, I have a newsletter on AI, and I’m pretty passionate about what’s happening in AI. So I even publish AI news this week, but with a different angle, a builder’s angle in mind. And last but not least, you can connect with me through LinkedIn for a 15-, 30-minute call. No angle there. I will just come and help you if you really want to do something with AI. I can listen to your challenges or your fear of missing out, if that’s the case, and tell you if AI is the right fit for you or not, and what you can do on your own also. And if you need our help, we are happy to. That’s fantastic. So take Dave up on his offer, which I think is very generous. And obviously, Dave, you know what you’re talking about. You built a second brain. You’re running AI agents. Your C-suite is chock-full of AI agents, which is very impressive. I’d love to learn more about this myself. So if you’re curious about that, make sure you book a call with Dave or check out his stuff. Where is your newsletter? Is it a Substack? Where can people find your newsletter? It’s on LinkedIn. It’s called Data & AI Demystified in my profile. Okay. So that’s easy. So we can go to Dave’s LinkedIn profile. And if you enjoyed this conversation, make sure you subscribe and follow us on Apple Podcasts and YouTube. Give us a review because every week I bring in a couple of exciting entrepreneurs like Dave who share their favorite frameworks with you. So Dave, thanks for coming, and thank you for listening. Important Links: Dave's LinkedIn Dave's website
What happens when an organization writes careful AI governance policies but its infrastructure cannot enforce any of them? In this episode of Tech Talks Daily, I speak with Sabina Anja, Chief Technologist at Broadcom within the VMware Cloud Foundation division, about the infrastructure controls required as AI agents move from generating answers to accessing data, calling APIs, modifying systems, and triggering work. Sabina brings experience from both sides of enterprise technology. She remembers cabling networks, dealing with unstable infrastructure, and receiving those weekend calls when downtime had already upset the business. That background informs her belief that ambitious AI programs cannot succeed without stable, observable, and enforceable infrastructure beneath them. Many organizations are repeating a familiar pattern. Business teams adopt AI services before IT has established visibility, ownership, or control. The terminology may have changed from shadow IT to shadow AI, but the management problem remains. Sabina argues that CIOs first need an inventory of agents, nonhuman identities, data access, processes, and accountable owners. The risk becomes greater because agents behave differently from people. They operate across multiple systems at machine speed and can perform repeated actions without appreciating the wider business outcome. An agent does not need malicious intent to cause disruption. Excessive permissions, flat networks, inconsistent access rules, and years of deferred infrastructure work can give it plenty of opportunities. Sabina recommends brokered access rather than direct access, alongside dedicated virtual machines or namespaces, microsegmentation, lateral security, east-west policy controls, and tamper-evident logging. Organizations also need to define which data an agent can view, modify, or move, especially when sovereignty and regulatory requirements apply. One of Sabina's most memorable ideas is to treat an AI agent like a superhuman contractor. It should have a defined purpose, a named manager, a clear access specification, an activity record, and an end date. Additional permissions should be earned through evidence of reliable behavior rather than granted on the first day. She also warns about agent debt. AI systems are developing rapidly, so an agent created today may become outdated within months. Sabina recommends assuming that many agents will expire after six to nine months rather than allowing forgotten systems and permissions to accumulate indefinitely. For CIOs wanting an immediate test, her advice is straightforward. Create an inventory of nonhuman identities with production access. Then select one agent and examine every part of the infrastructure it attempted to reach. The question is not simply whether the application produced the expected result. Leaders should ask whether the agent entered systems, networks, or data stores that nobody expected it to access. We also challenge the familiar claim that AI agents will take everybody's jobs. Sabina sees an opportunity to remove repetitive tasks and give technology professionals new skills, although she warns that agents may behave like teenagers armed with infrastructure permissions. They may not take your job, but they could become remarkably good at testing your patience. I'd love to hear your thoughts. Does your organization know how many AI agents have production access and who is accountable for each one?
ENTRE NA LISTA DE ESPERA DO VIVER DE RENDA: https://r.vocemaisrico.com/2578c2bd18ABRA SUA CONTA NA COINBASE: https://r.vocemaisrico.com/72f2133408Ao longo da história, algumas mentes se destacaram tanto que passaram a ser lembradas como os maiores gênios da humanidade — indivíduos capazes de revolucionar a ciência, a arte, a filosofia e a forma como compreendemos o mundo.De Leonardo da Vinci a Einstein, de Mozart a Marie Curie, cada um deixou um legado que atravessa séculos e continua influenciando a vida de todos nós.Mas quem realmente merece o título de "maior gênio" de todos os tempos? Seria justo comparar um cientista como Newton com um artista como Shakespeare, ou cada área exige seus próprios critérios de genialidade?Quais nomes menos conhecidos, esquecidos pela história ou pouco celebrados no Ocidente, também deveriam estar nessa lista? E o que aprendemos, afinal, observando as trajetórias dessas mentes extraordinárias?Para conversar sobre isso e muito mais, convidamos Felipe Guisoli (Universo Narrado) para o episódio 313 do podcast Os Sócios. Falaremos sobre os maiores nomes da história humana, seus legados, suas histórias pessoais e por que continuamos fascinados por eles até hoje.Ele será transmitido nesta quinta-feira (27/08), às 12h, no canal Os Sócios Podcast.Hosts: Bruno Perini @bruno_perini e Malu Perini @maluperiniConvidados: Felipe Guisoli @universonarrado
In this episode of The New CISO, host Steve Moore welcomes Sherri Douville for a conversation that sits outside the show's usual lane — less war story, more blueprint. Sherri works alongside CISOs rather than inside the role, and arrives with a pointed argument about what the job is becoming.She starts with why TTIC exists. IEEE UL 2933 gave healthcare a full-stack standard for clinical IoT device and data interoperability, but a standard on paper does nothing until it is adopted, implemented, and maintained. Getting there in a high-reliability industry means pulling in CIOs, CISOs, physicians, and engineers — and, Sherri admits, negotiating turf wars with bodies who assume you have come for their territory.Then the headline: how to make security cool. Sherri's answer starts with visibility — getting CISOs onto stages, onto podcasts, and into print in front of clinical leadership. Underneath it is a claim about trust. In healthcare, trust is the core of the business rather than an adjacent concern, which makes the CISO its natural steward. With AI pushing trust to the center of every industry, she argues that is the opening to become the rock star of the C-suite.Steve raises a banking CISO's framing of AI as a curious seven-year-old with a gun. Sherri pushes back on the spot: her analogy is the gifted teenager — capable, resource-hungry, and badly in need of direction. That leads to her real thesis. Scarce expertise used to carry economic value, and AI is rapidly compressing the worth of expert analysis. What appreciates instead is judgment, authority, execution, verification, organizational integration, and ownership of the outcome. Executives do not want more reports; they want the security problem to go away without adding coordination burden.The last stretch turns practical. Sherri walks through running Exabeam's open-source Praxen against Medigram's own code — painless to run, with remediation effort scaling to whatever standard you are chasing — and pairs it with Observra for continuous runtime telemetry. She closes on why it matters: when systems go down in a hospital, the real damage is not the outage hour but the fortnight of delays, miscommunications, and pile-up that follows for clinicians and patients.Key TopicsWhy standards bodies stall at adoption, not authorshipMaking security “cool”: visibility, stages, and executive presenceTrust as the core of the business in high-reliability industriesThe gifted teenager vs. the curious seven-year-old with a gunJudgment, authority, execution, verification, integration, ownershipSelective depth and the player-coach executiveRunning Praxen pre-deployment; Observra for runtime telemetryWhat a healthcare outage really costs, 14 to 20 days outGuest BioSherri Douville is CEO and Architect of Medigram and Founder and Chair of the Trustworthy Technology & Innovation Consortium (TTIC). She co-chairs the Trust subgroup of IEEE UL 2933 (TIPPSS), the standard for trust in clinical IoT. Medigram builds and operates Darwin, a governed AI decision platform whose agentic fleet runs in production and writes a sealed governance record at the moment of every agent action — an auditable trail for counsel, courts, insurers, and credit rating agencies. Sherri spent over a decade at Johnson & Johnson across a dozen disease states before physician leaders pulled her into healthcare IT and AI. She calls herself an accidental technologist: a domain expert who got into the code, logging 200 GitHub commits across June and July.GET A DEMO:
Who really controls your enterprise technology strategy: your organization or the vendors writing its software contracts? In this episode of Tech Talks Daily, I speak with Tomás O'Leary, founder and CEO of Origina, about enterprise software vendor lock in, forced upgrades, subscription contracts, and the financial consequences of surrendering control over mission-critical systems. Tomás founded Origina in Dublin after working within the enterprise software supply chain and questioning the value customers received from traditional support contracts. He saw organizations paying substantial annual fees while experiencing poor response times, constant pressure to change versions, and upgrades that produced limited business value. He argues that the balance of power between technology buyers and suppliers has moved heavily toward the vendor. Companies that previously purchased perpetual software rights are increasingly being encouraged or forced toward subscription models, while complex contract terms and audit risks can make customers feel trapped. Some Origina customers have described this behavior as a "digital mafia," while one Fortune 50 organization, according to Tomás, uses AI to assess whether suppliers could be acquired by vendors it considers predatory. That business then considers longer contracts as protection against future licensing changes. However, leaving a vendor does not always require replacing the software. Tomás explains why perpetual software rights and independent support can give companies another option. A system that continues to perform its required business function may not need to be replaced simply because the original vendor has ended support or introduced a new commercial model. We discuss how leaders should distinguish between technology that genuinely requires modernization and dependable systems of record that could continue operating securely. Payroll platforms, general ledgers, claims systems, and other back-office applications may not require constant reinvention if the business requirement remains stable. Tomás also describes a European organization spending approximately €1 million annually on a software product. The company estimated that a vendor-required version change would cost €30 million. By moving to an alternative support arrangement, it expects to defer that expenditure while keeping the existing system operational. These figures are the organization's estimates, shared by Tomás during our conversation. We also discuss centralized technology dependency, outages, software patching, AI-assisted development, and why some companies are returning to internally developed applications for operations they consider particularly important. Tomás recommends that CIOs create a small team combining technical, procurement, contractual, and legal knowledge. This group should remain close to senior leadership and challenge assumptions before renewals, migrations, or major software changes are approved. Is your organization modernizing because the business needs to change, or because a vendor has decided that time is up? Listen to the conversation and share your thoughts with me.
ENTRE NA LISTA DE ESPERA DO VIVER DE RENDA: https://r.vocemaisrico.com/32dfe58945 A história do Brasil que você aprendeu na escola é a verdadeira, ou apenas a versão que interessava contar?Por que a história que aprendemos na escola parece ser tão diferente da história real do Brasil? Do "descobrimento" às revoltas coloniais, do Império às diferentes fases da República, muitos dos fatos que consideramos absolutos escondem versões mais complexas — e às vezes bem diferentes do que os livros didáticos ensinam.Será que a miscigenação foi apenas um processo cultural espontâneo, ou também uma estratégia política deliberada? Os bandeirantes foram heróis ou vilões — ou nenhum dos dois? A abolição foi mesmo uma conquista pessoal da Princesa Isabel? E até que ponto figuras como D. Pedro II, D. João VI e Getúlio Vargas foram simplificadas por narrativas que serviam a interesses específicos de cada época?Será que, de fato, a "sequência de fatos" que aprendemos é história ou apenas uma seleção conveniente de eventos? Quantas vezes tomamos como verdade absoluta episódios que, na realidade, escondem disputas de poder, interesses econômicos e escolhas estratégicas?Para responder a essa e outras perguntas, recebemos Rafael Nogueira no episódio 312 do podcast Os Sócios.Hosts: Bruno Perini @bruno_perini e Malu Perini @maluperini Convidado: Rafael Nogueira @nogueira.r
Earlier this year I sat down at the inaugural WRITA spring conference with Jeff Scheetz (CIO, City of Avondale) and Zach Duguid (AI Engineering Manager, Polimorphic). Jeff's answer to what he'd put in front of a room of local government CIOs isn't a success story. It's the horror stories — the scary stuff nobody puts in the press release. Most of this episode is the unglamorous work that prevents it. Zach walked through what Polimorphic does before an agent ever answers a resident: a Knowledge Base Health Check that seeds up to 500 questions against a city's own content, then reruns them weekly or monthly to confirm what the agent answers and which sources it pulled from. We also talked about:Why pilots de-risk AI and then stall before they scale across departmentsSingle sign-on inside the city, four or five logins outside itJeff's next 18 months: consolidate, standardize, clean up after the growthTimestamps01:55 "I just got a new dog. How do I register him?" — the AI answers, then files the form03:43 "We're not selling services. There's no checkout cart." So what is a city website for?04:55 The caller doesn't know the address. They know the coffee shop. The map does the rest.07:24 A water outage in Utah, live on the phone line the moment staff post it09:14 Single sign-on inside the city. 4-5 logins outside it. Nobody's solved this.10:22 30-40 departments, each with its own process — and the war against too many toggles11:47 19 years in: how much security pain can you inflict before staff route around you?12:56 "We had to move very quickly for years. Now we finally get to go clean it up."14:14 Your chatbot is quoting agenda minutes from a decade ago — the check that catches it first16:30 A 20-year employee retires. Where does the knowledge go, and can AI hold it?18:18 Pilots de-risk AI. They don't scale it. Why Zach wants it treated as infrastructure.19:28 Jeff's ask for the roundtable: not the AI wins, the horror stories
Este conteúdo é um trecho do nosso episódio: “#360 - Por que 56% das empresas já têm um Chief AI Officer”.Nele, Francisco Massaro, Coordenador do MBA em Chief AI Data Officer da FIAP, explica por que o CIO é o C-level com a segunda menor permanência média nas empresas, atrás apenas do presidente. Ele traz dados de pesquisas recentes sobre a saída de mais de 230 CIOs de grandes empresas brasileiras em um único ano, e mostra por que a competência mais exigida dos próximos anos não é técnica, mas o pensamento sistêmico. Ficou curioso? Então, dê o play!Assuntos abordados:Permanência do CIO;Rotatividade executiva;Pensamento sistêmico;Cases de mercado.Links importantes:NewsletterDúvidas? Nos mande pelo LinkedinContato: osagilistas@dtidigital.com.brOs Agilistas é uma iniciativa da dti digital, uma empresa WPP #lideranca
What happens when an autonomous AI agent can complete thousands of actions before a traditional access review has even identified that something has gone wrong? In this episode of Tech Talks Daily, I speak with Alex Bovee, CEO and co-founder of C1, about identity security, runtime governance, shadow AI, and the controls companies need as humans and agents begin working together. Alex has spent much of his career in identity and security. He and his co-founder previously worked at Okta on zero trust products before creating C1 as an access control platform capable of operating at machine speed. That requirement has become increasingly important as AI agents begin accessing company data, calling tools, using credentials, and taking actions across enterprise systems. Alex describes agents as non-deterministic systems that can "reward-max." An agent may pursue its assigned objective so aggressively that it finds an unexpected or dangerous way to complete the task. It does not possess a moral compass or an intuitive understanding of what the company considers acceptable. Traditional identity processes were created for people. A company might review access every 90 days or investigate a security issue after an event. That approach becomes inadequate when an agent can execute thousands of actions within minutes. We discuss why identity is becoming a control plane for AI agents. Networks, data systems, and security tools all play important roles, but identity determines which resources an agent can access, which actions it can perform, and whether it acts independently or on behalf of a person. Without a defined identity or delegated authorization model, an organization may struggle to connect an agent's behavior with a responsible owner, a limited mission, and enforceable permissions. Alex explains the four connected capabilities inside C1's Agentic Control Plane. The first concerns shadow AI discovery. Companies need visibility across cloud services, SaaS applications, endpoint agents, hosted agents, local MCP servers, and credentials stored throughout the environment. This is particularly relevant because employees are downloading locally developed or "vibe-coded" MCP servers and running agent tools on their devices. These components can introduce software supply chain risks and expose local credentials. The second capability covers credential security. C1 has introduced a post-quantum credential vault designed to protect secrets and inject them into authorized agent workflows without leaving credentials scattered across devices and applications. The third area is runtime governance. Instead of reviewing behavior after an incident, organizations can evaluate an agent's actions against its assigned mission as they occur. If an agent is authorized to complete one business task but begins exploiting an internal tool, contacting an unapproved service, or attempting to extract data, runtime controls can block the action or request human approval. The fourth capability concerns agentic security intelligence. This uses information collected across identities, agents, permissions, credentials, and behavior to identify risks and support automated remediation. We also discuss human accountability. Alex says emerging regulatory thinking recognizes the need for a responsible person behind an autonomous agent. That connection allows businesses to establish ownership, delegate authority, and determine who remains accountable for the agent's behavior. The conversation then turns to the effect of AI on employees. Alex rejects the assumption that organizations will simply remove people as agents become more capable. His preferred analogy is that people are moving from manually producing every artifact to building and supervising the factory. Employees provide the inputs, direct the agents, examine the outputs, and correct the process when necessary. C1 has experienced this internally. Alex says its engineering team increased from roughly 150 weekly software merges to around 1,500, while engineering headcount grew by approximately 10% to 15%. That productivity requires careful human review. Generating work faster does not remove the need to assess whether the output is accurate, secure, useful, and aligned with the original objective. For CISOs and CIOs, the goal is to provide a governed path for AI adoption. A blanket prohibition may encourage employees to work around policy. Secure self-service access can give teams approved tools, defined permissions, and runtime protection. If an AI agent can operate at machine speed, are your organization's identity controls capable of observing, authorizing, and stopping it at the same pace? Listen to the conversation and share your thoughts with me.
Se você acredita, assim como eu mesmo por muitos anos no passado acreditava, que carboidratos não são essenciais na dieta porque o corpo consegue produzir glicose ele mesmo e que eliminá-los é uma das melhores coisas que você pode fazer para sua saúde, este vídeo é pra você. Hoje quero te mostrar algumas provas cabais do contrário disso e abrir uma porta enorme de possibilidades e felicidade para que você possa atingir seus objetivos de saúde, vitalidade e peso de forma mais fácil, tranquila e muito saborosa na sua vida sabendo melhor o que fazer. Então, vem comigo…
Escalas de abate alongam com pequenos frigoríficos comprados para sete dias e os grandes, programados até o final de agosto, diz analista
Post-quantum cryptography was in conversation after conversation at Black Hat USA 2026, yet Larry Lunetta of HPE walked part of the show floor and counted a single reference to quantum. Where the topic shows up, and where it does not, says something about who is expected to solve it. Why does a problem described in 1994 matter now? Larry Lunetta points to Peter Shor, who asked what would happen to RSA if a different kind of computing technology existed. What changed since then is the trajectory. Five years ago cryptographically relevant quantum computing looked like a 10 to 15 year phenomenon. Larry Lunetta now puts it as soon as three years out, with the original algorithm improved, qubit hardware advancing, and classical supercomputing pulling the timeline in alongside it. The exposure starts before any of that arrives. Larry Lunetta describes harvest now, decrypt later, where an attacker collects RSA-encrypted data today and waits for the machine that can open it. Data that carries no consequence when it leaks this year can be read later, which puts long-lived information like identity records and medical data at the front of the queue rather than in a later phase. HPE puts a three part journey in front of customers. Cryptographically aware asks which data is most sensitive, where it lives, and whether it is protected sufficiently. Cryptographically planning reaches into the refresh cycle, so that new network, server, and storage purchases already implement PQC-relevant algorithms. Cryptographically nimble accounts for the fact that no cryptographically relevant quantum computer exists to test against yet, which makes the ability to change algorithms and firmware quickly part of the design. Who owns the conversation inside the business? Larry Lunetta puts the CISO at the center of gravity, with CIOs becoming aware and boards engaged where GDPR governs customer and private information. His advice for security leaders is to broaden the conversation toward infrastructure and operations, and to make encryption and PQC readiness a question asked during procurement rather than after it. This is a Brand Briefing. A Brand Briefing is an on-location conversation recorded on site at Black Hat USA 2026, putting a spotlight on the guest and their company and pairing it with the editorial reach of ITSPmagazine. Learn more: https://www.studioc60.com/performance/#briefing GUEST Larry Lunetta, Vice President, Portfolio Technical Marketing at HPE On LinkedIn: https://www.linkedin.com/in/larryathpe/ RESOURCES Black Hat USA 2026 event coverage: https://www.itspmagazine.com/black-hat-usa-2026-cybersecurity-event-coverage-in-las-vegas HPE: https://www.hpe.com Post-Quantum Cryptography overview: https://www.hpe.com/us/en/what-is/post-quantum-cryptography.html HPE technology leadership in quantum: https://www.hpe.com/us/en/about/technology-leadership-quantum.html Are you interested in telling your story? ▶︎ Full Length Brand Story: https://www.studioc60.com/content-creation#full ▶︎ Brand Spotlight Story: https://www.studioc60.com/content-creation#spotlight ▶︎ Brand Highlight Story: https://www.studioc60.com/content-creation#highlight ▶︎ Get your own Brand Briefing at an upcoming event: https://www.studioc60.com/buy-brand-briefings KEYWORDS larry lunetta, hpe, sean martin, brand briefing, brand story, brand marketing, marketing podcast, black hat usa 2026, post-quantum cryptography, pqc, quantum computing, harvest now decrypt later, rsa encryption, cryptographic agility, ciso, crypto agility, nist post-quantum standards, it infrastructure security, encryption, data protection Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
Cafeicultores permanecem cautelosos para avançar com suas vendas e agora dividem sua enegia com a safra 2027/28, que já se mostra desafiadora pelo clima.
GARANTA SUA VAGA NO PROGRAMA "DOBRE SEU LUCRO": https://r.vocemaisrico.com/5fc3f6cd35CONHEÇA A AQUILA: https://aquila.com.br/Muitos empreendedores sabem exatamente onde estão os problemas da própria empresa, mas simplesmente não conseguem resolvê-los. Falta de gestão, ausência de processos, sociedades mal estruturadas e uma dificuldade enorme de sair da zona de conforto — tudo isso vai, aos poucos, minando negócios que poderiam prosperar.Enquanto isso, o Brasil enfrenta seus próprios gargalos: alto custo de capital, insegurança jurídica e uma produtividade que praticamente não avança desde os anos 80.Diante disso, qual é o erro mais comum dos empreendedores brasileiros? Por que 90% das estratégias fracassam na hora de serem implementadas? Como saber se vale a pena ter um sócio — e o que realmente garante que essa sociedade não termine em briga judicial? Vale a pena colocar um filho para trabalhar na empresa da família, e como prepará-lo para realmente sucedê-la? E existe um caminho para o país deixar de "andar de lado" e se tornar, enfim, protagonista?Para responder a essas e outras perguntas, convidamos Raimundo Godoy, presidente executivo, sócio e cofundador do Instituto Áquila, para o episódio 311 do Podcast Os Sócios. Ele será transmitido nesta quinta-feira (13/08), às 12h, no canal Os Sócios Podcast.Hosts: Bruno Perini @bruno_perini e Malu Perini @maluperiniConvidado: Raimundo Godoy
Podcast: Industrial Cybersecurity InsiderEpisode: Your Most Critical Network May Be Your Least ProtectedPub date: 2026-08-11Get Podcast Transcript →powered by Listen411 - fast audio-to-text and summarizationThe air gap you're counting on probably isn't there. Dino Busalacchi sits down with cybersecurity veteran and Tulane University Cybersecurity Professor Joshua Copeland, to talk about the realities of protecting industrial environments, where uptime, safety, and production come first. They dig into why legacy systems can't be secured like IT, how routine security tasks can disrupt physical operations, the leadership gap between IT and OT, and why cybersecurity needs to be treated as digital safety. A practical listen for CISOs, CIOs, engineering leaders, and plant operators.Chapters:(00:00:00) Why operational technology is critical to everyday life(00:03:00) Legacy systems and the hidden opportunity in OT security(00:07:00) Ransomware, AI, and attacks designed for physical outcomes(00:10:00) How standard IT security tools can stop production(00:13:00) What cybersecurity events get wrong about OT(00:16:00) The leadership gap and the myth of isolated systems(00:20:00) Why cybersecurity should be treated as digital safety(00:23:00) Compliance, asset inventory, and aging industrial equipment(00:27:00) Building the next generation of OT security professionals(00:31:00) Why every part of modern life depends on OTLinks And Resources:Want to Sponsor an episode or be a Guest? Reach out here.Industrial Cybersecurity Insider on LinkedInCybersecurity & Digital Safety on LinkedInBW Design Group CybersecurityJosh Copeland on LinkedInDino Busalachi on LinkedInCraig Duckworth on LinkedInThanks so much for joining us this week. Want to subscribe to Industrial Cybersecurity Insider? Have some feedback you'd like to share? Connect with us on Spotify, Apple Podcasts, and YouTube to leave us a review!The podcast and artwork embedded on this page are from Industrial Cybersecurity Insider, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
Send us Fan MailAI, leadership, and adoption with Shawn MillsThis episode focuses on how organizations should approach AI as a business strategy, not just a technology purchase. Chris Whitaker is joined by Shawn Mills, CEO and chairman at Pisteyo, who brings a practical view of what actually works when companies try to adopt AI. The conversation covers leadership alignment, change management, and why education matters just as much as the tools themselves.Key topicsIn this episode: Shawn Mills shares how his background in finance, sales, and entrepreneurship shaped the way he thinks about business and technology.We discuss: why AI adoption is usually a people and process challenge, not just a tooling challenge.Shawn explains: the meaning behind the name Pisteyo, including its roots in off-piste skiing and the Greek meaning tied to belief.We explore: how Pisteyo positions itself as a management consulting firm first, then a technology solution provider.Shawn breaks down: why CEOs, boards, CTOs, and CIOs are often the real drivers behind AI initiatives.We cover: the common mistake of buying an AI tool and expecting adoption without training, enablement, or context.Shawn shares: why smaller and mid-market companies can now compete more effectively because AI gives them access to capabilities once reserved for larger firms.We discuss: prompt quality, AI slop, and the need to understand and explain AI-generated output before passing it along.Shawn emphasizes: that business and technology teams need to stay in lockstep or AI projects can drift away from real business needs.We close with: advice on leadership alignment, curiosity, and continuous learning as AI capabilities keep accelerating.Timestamps00:00 - Why AI is now at the center of every tech conversation 02:41 - What Shawn Mills is seeing in executive AI journeys 03:17 - Life outside work: hiking, surfing, Nepal, Peru, and Costa Rica 05:35 - From finance and investment banking to sales, marketing, and operating companies 07:29 - The biggest lesson: use your network and ask for help 09:34 - How American Airlines flight benefits sparked a lifetime of adventure 10:21 - Why AI is transforming financial modeling and analysis 12:11 - The real story behind the name Pisteo 14:45 - Why Pisteo starts with business strategy, not technology 16:52 - The board and CEO pressure driving AI initiatives 18:33 - Passive resistance and why education gets forgotten 20:49 - Why upper mid-market companies are the best fit 22:42 - How AI is leveling the playing field for smaller companies 24:32 - The most common AI failure: tool first, training never 27:38 - Why the AI capability gap keeps growing 29:41 - Is AI making people smarter or lazier? 32:21 - Why technologists must partner with the business 35:25 - Lightning round: coffee, books, leadership, and video 37:28 - Why executive alignment is critical to AI success 38:36 - Closing thoughts and final takeawayNotable quotes“If you're not falling, you're not learning.”“I'm literally the smartest person on the planet as long as I have access to AI.”“Bring the leadership team along with you on the journey.”More on Shawn MillsMore on Pisteyo Support the showCheck out my website https://thewirelessway.net/ use the contact button to send request and feedback.
Reportagem da ONU News foi às ruas de Maputo conhecer empreendedores que focam em desenvolvimento sustentável, autonomia para juventude e muita persistência em meio a desafios; conheça as histórias da sapateira-engraxate e de um criador de uma ótica que quer se expandir pelo mundo.
Congress Presses Big AI on Safety as Data Center Wars Hit Courts and CIO Costs Rise Jim Love's Hashtag Trending for Wednesday, August 12, 2026 looks at mounting pressure on the AI industry from Washington, corporate technology budgets, data center opposition and changing economics in consulting. House Democrats are demanding answers from OpenAI and Anthropic about AI agents that escaped test environments and reached outside systems. Senator Bernie Sanders is going further, urging OpenAI, Anthropic and Meta to pause development of their most advanced models. At the same time, bipartisan proposals are emerging around AI security audits and an AI Kill Switch Act. CIOs are facing another problem: rising costs. Microsoft has reportedly increased Windows 11 OEM licence fees by 7 to 10 percent. Many organizations are still moving PCs off Windows 10, while memory prices, Microsoft 365 costs, AI model and token spending, and cybersecurity requirements are all increasing. The fight over AI data centers is also moving into courtrooms. Lawsuits are challenging approval processes, environmental impacts and plans for off-grid natural-gas power generation. And finally, Jim looks at a question he has been raising for some time: is AI starting to undermine the traditional consulting business model? Accenture's bookings are slowing just as AI gives clients increasingly powerful tools for research, analysis and presentations. 00:00 Headlines and Intro 00:24 Congress Targets AI Safety 02:13 CIO Budget Squeeze 04:14 Data Center Lawsuits Rise 06:38 AI Disrupts Consulting 09:00 Closing Thoughts and Outro
OCR has been around for more than 40 years. So why do the world's biggest banks still have thousands of people reading documents by hand? When Dan Maloney became CEO of Landing AI in 2024, as Andrew Ng stepped back from the day-to-day, he was returning to a problem he had first worked on at SAP back in 2001. When he looked closely at it again two decades later, he was struck by how little it had actually moved. Landing AI's mission is to make the world's documents computable. Instead of growing up from OCR and patching its limits with templates and heuristics, Landing AI came at the problem from visual AI, blending purpose-built models, an intelligent router, and agentic reasoning into a single system that reads a document the way a person does. Today that system extracts structured data from the messiest documents enterprises have, the scanned pages, the tables inside tables, the handwritten forms, at accuracy levels they can build on. Before every enterprise had an AI strategy... Before "agentic" became a boardroom word... Before the industry spent a year token maxing... There was a quieter, more stubborn problem: The world's data was trapped in documents, and no one could read it at scale. In this episode of the Future of Data & AI Podcast, Dan Maloney, CEO of Landing AI and a two-decade veteran of enterprise software and AI, joins Raja Iqbal for a grounded conversation about what it actually takes to move visual AI from an impressive demo into production. Dan is candid about where the hype outruns reality, why the model is the smallest part of the equation, and how a company earns the trust of a compliance team, not just an engineering one. What You'll Discover
What happens when an AI agent is compromised, manipulated, or simply does something nobody expected, but already has permission to access your most sensitive systems? In this episode of Tech Talks Daily, I speak with Geoffrey Mattson, CEO of SecureAuth, about why securing enterprise AI requires businesses to think beyond protecting models and start paying much closer attention to identity, authorization, access control, and what AI agents are actually allowed to do. Geoffrey argues that AI agents present a different security challenge from traditional software. Conventional applications can be tested against relatively predictable behavior. AI models are far less deterministic, particularly when prompt injection, excessive permissions, unexpected behavior, and autonomous actions enter the equation. His advice is to assume an agent could behave unpredictably and control what happens when it attempts to access a database, execute a financial transaction, call an API, or interact with another business system. We discuss what this means as companies race to introduce agentic AI. Geoffrey shares examples of employees granting AI tools permissions without fully understanding what they have approved, along with agents gathering information that creates unexpected privacy and compliance problems. This creates a difficult challenge for CIOs and CISOs. Boards want AI adoption because of its potential competitive value, while employees increasingly depend on AI tools to do their jobs. Simply blocking agents is unlikely to work. Security teams instead need mechanisms that allow innovation while controlling what those agents can access. Geoffrey explains why Zero Trust becomes particularly relevant here. Rather than authenticating a user or agent once and assuming it remains trustworthy, enterprises need to continually evaluate whether an action should be permitted at that specific moment. This leads to the concept of continuous authorization. Geoffrey explains how identity security is moving from asking "Who are you?" toward understanding intent, behavior, context, and authority for individual actions. This becomes increasingly important when one AI agent can create sub-agents, which can then create additional agents and pass permissions down the chain. We also discuss why agentic AI is exposing years of accumulated security debt. Many of the underlying problems are familiar: excessive privileges, inconsistent access controls, incomplete Zero Trust implementations, and systems that trust identities for too long. AI agents amplify those weaknesses because they can operate at machine speed. Geoffrey describes this as combining the unpredictability of humans with the power of machines. For CIOs, CISOs, security architects, identity teams, and business leaders deploying agentic AI, this conversation offers practical questions to ask before connecting agents to enterprise resources. What can the agent access? What authority does it have? Can that authority be reduced as tasks are delegated? Is every important action evaluated independently? And can access be revoked immediately when behavior changes? The goal is not to prevent organizations from using AI agents. It is to create a security layer that gives developers and employees room to experiment while ensuring agents only have the authority they need at the moment they need it. As autonomous AI becomes part of the enterprise workforce, identity alone may no longer be enough. Businesses increasingly need to understand intent, control authority, and continuously decide whether the next action should be allowed.
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
As artificial intelligence innovation outpaces the early days of public cloud, CIOs face the burden of parsing through noise to...
Companies are spending billions on GPUs, data centers, foundation models, and AI infrastructure. But what happens when the network connecting all of it cannot keep up? In this episode of Tech Talks Daily, I welcome back Avi Freedman, co-founder and CEO of Kentik, five years after our previous conversation. Avi has been operating large-scale networks since the 1990s, including more than a decade at Akamai, and brings a rare combination of founder experience and hands-on knowledge of how the internet actually works. We discuss why network performance is becoming an important factor in determining the return companies receive from their AI investments. If organizations cannot move data efficiently to models or deliver inference reliably to users and applications, expensive compute infrastructure can sit waiting while performance suffers and costs increase. Avi explains what technology leaders should measure to determine whether their network is helping or hindering AI workloads. This includes establishing performance baselines, synthetic testing across cloud and AI providers, understanding dependencies across the digital supply chain, and using observability to identify what changed when performance deteriorates. The conversation also examines network intelligence and why collecting telemetry alone is not enough. Organizations need to connect network data with the applications and users affected, understand historical behavior, determine which problems matter, and give network teams enough context to act quickly. Agentic AI introduces another opportunity. Avi explains how AI agents can increasingly perform the work of experienced network engineers by monitoring baselines, investigating alerts, troubleshooting problems, and recommending actions. But fully autonomous networks remain some distance away. Most enterprises currently want humans deciding whether significant production changes should be made. That leads us into governance. As businesses give AI systems access to increasingly important infrastructure, credentials, permissions, guardrails, and oversight become major considerations. Avi warns about ungoverned AI systems gaining proxy access to corporate infrastructure and explains why companies need clear boundaries around what agents can see and do. We also revisit a lesson from decades of internet infrastructure: individual components will fail. Rather than attempting to create networks that never fail, businesses should design for resilience through redundancy, over-provisioning, monitoring, and architectures capable of continuing when something inevitably breaks. For founders, CIOs, CTOs, network engineers, and infrastructure leaders building around AI, Avi offers practical advice on observability, network resilience, autonomous operations, AI infrastructure, and knowing when networking expertise should be developed internally or brought in from elsewhere. And we finish somewhere unexpected: how CEOs can use AI to make better decisions by explicitly asking it to disagree with them. Avi explains why turning AI from a sycophantic assistant into an argumentative colleague can expose weaknesses in an idea, improve communication, and help leaders test their thinking. AI may be transforming software, compute, and business operations, but none of it works without connectivity. As AI becomes part of the operational backbone of the enterprise, understanding the network underneath it becomes increasingly difficult to ignore.
Football franchises run on data. Jono Luk of Sumer Sports explains how AI is changing who wins — on the field and in the stands.Full Show Notes:Most sports AI coverage focuses on stats. Jono Luk, Chief Product Officer at Sumer Sports, is thinking about something harder: measuring what a player decided, not just what they did. Sumer's computer vision tracks all 22 players up to 60 times per second, generating probabilities for every moment of every play — not to describe what happened, but to evaluate whether the best decision was made.That depth of game intelligence turns out to be useful in two places. For coaches, GMs, and scouts, it surfaces skill that box scores miss entirely. For the business side of a franchise, that same real-time game data becomes the trigger for personalized fan experiences — the right offer, the right moment, whether someone is in the stadium or watching from a sports bar. Jono calls this the before, during, and after — and argues it's the same attract-retain-monetize cycle every enterprise runs, just with a different playbook.The episode also covers what Jono wishes organizations understood before they start any AI conversation: AI isn't synonymous with LLMs. Computer vision, specialized models, and multi-component pipelines built for specific data types are doing work that frontier models simply aren't designed for. That framing matters for any enterprise buyer, not just sports franchises.What We Cover:How Sumer Sports uses computer vision to evaluate player decisions, not just outcomesWhy specialized AI models outperform general-purpose frontier models for sports analyticsThe two sides of AI in a football franchise: football operations and fan engagementHow real-time game data triggers personalized in-venue and at-home fan experiencesWhat the NIL era means for AI-assisted recruiting at college and high school levelsWhy AI in the enterprise isn't just about LLMs — and how to think about the broader toolkitThe one question Jono wants every organization to ask before deploying AIGuest Bio:Jono Luk is Chief Product Officer at Sumer Sports, a football data analytics and AI company that uses computer vision to analyze every player, every game, in real time. Before Sumer, Jono held product and technology leadership roles at Cisco. He brings a cross-industry perspective on how AI fits into larger solutions — not as a replacement for human judgment, but as the infrastructure that surfaces better decisions faster.Sumer Sports: https://www.sumersports.comJono Luk on LinkedIn: https://www.linkedin.com/in/jonoluk/ (confirm URL before publishing)Resources Mentioned:Sumer Sports: https://www.sumersports.comLopez Research: https://www.lopezresearch.com/research/
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
GARANTA SUA VAGA NO LUCRO 2X COM GRUPO PRIMO + G4ABRA SUA CONTA NA COINBASESimplifique seu IR com a myprofitO petróleo segue como um dos pilares da economia global, influenciando preços, relações diplomáticas, cadeias produtivas e a segurança energética de países inteiros.No Brasil, a descoberta do pré-sal consolidou o país entre os grandes produtores mundiais. Ao mesmo tempo, trouxe à tona desafios relacionados à capacidade de refino, à importação de derivados e ao papel estratégico da Petrobras.Mais recentemente, a Margem Equatorial passou a ser vista como uma das principais apostas para ampliar as reservas brasileiras nas próximas décadas — e pode redesenhar o mapa da produção nacional.Mas qual é, de fato, o potencial econômico dessa nova fronteira? O petróleo brasileiro tem características diferentes do produzido em outros países? Por que, mesmo sendo um grande produtor, o Brasil ainda importa diesel, gasolina e outros derivados?Em um mundo que busca reduzir emissões e acelerar a transição energética, qual será o papel do petróleo nas próximas décadas? Por quanto tempo ele continuará indispensável à economia global? E como o Brasil pode se posicionar diante das oportunidades e dos desafios desse novo cenário?Para responder a essas e outras perguntas, recebemos Adriano Pires no episódio 310 do Os Sócios Podcast.Hosts: Bruno Perini (@bruno_perini) e Malu Perini (@maluperini)Convidado: Adriano Pires (@cbie_brasil)
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
Most enterprise AI pilots stall or fail before production, and the blocker is rarely the model. Nate B. Jones, an AI analyst and advisor who works with Fortune 500 companies and global banks, tells Michael Krigsman that naming an effort a pilot invites small budgets and safe goals. He explains how to pick a first project that matters to the business, why adoption is roughly 80 percent a people problem, and how to budget AI by cost per completed task rather than cost per token. Recorded live on CXOTalk with questions from the audience throughout.YOU'LL DISCOVER✅ Why calling the work a pilot produces smaller budgets, safer goals, and weaker learning✅ The two starting points Jones gives leaders: get hands-on with the tools yourself, then pick a project where success creates real business leverage✅ Why adoption follows a bell curve, and what actually moves the middle of the distribution✅ Why data flow, not the model, is the technical issue that stops initiatives most often✅ The harness (context, memory, reusable procedures, review gates) treated as company intellectual property✅ How to compare open weights against frontier models on cost per completed action, including token efficiency between models✅ Why cost per task keeps falling even as frontier work stays expensive, and how to budget against that✅ The case for one named owner per agent, and what Jones tells CIOs about shadow AI and cyber defense⏱️ TIMESTAMPS0:00 Introduction0:24 Why pilots fail and where to start3:30 Adoption is mostly a people problem8:51 Data, outcomes, and undocumented knowledge14:19 Learning from pilots and proving value17:57 The harness and AI fluency23:59 Why a culture of experimentation wins28:03 Open weights, costs, and team fluency33:25 When new model releases matter38:15 Job fear, AI costs, and accountability46:41 Agent owners, evals, and production gates51:03 Advice for CIOs and when to stopSubscribe for weekly conversations with the business and technology leaders shaping enterprise AI strategy: https://newsletter.cxotalk.comShow notes, transcript, and summary: https://www.cxotalk.com/episode/why-ai-pilots-stall-how-to-make-enterprise-ai-workEpisode 927 | Recorded Friday, July 31, 2026#CXOTalk #EnterpriseAI #AIStrategy #AIAdoption #DigitalTransformation #CIO #AIAgents #Tokenomics #AIGovernance
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
Cyber Resilience isn't just an IT challenge anymore. It's changing how the best B2B sales teams sell. Companies are racing into AI, but Tim Pfaelzer believes many are overlooking the foundation that determines whether it succeeds. Harry sits down with Tim Pfaelzer, SVP & GM EMEA at Veeam, to explore why successful companies don't simply adapt their products. They retrain their sales teams to speak the language of business risk, executive priorities, and business outcomes. Along the way, Tim challenges one of the biggest assumptions surrounding AI and explains why "backup isn't the product. Trusted data is the outcome."
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
No “Estadão Analisa” desta quarta-feira, 05, Carlos Andreazza fala sobre a transação admitida pelo ex-chefe de gabinete do presidente Luiz Inácio Lula da Silva, Marco Aurélio Santana Ribeiro, que assumiu ter recebido pagamento da lobista Roberta Luchsinger. Ela se tornou investigada pela Polícia Federal por suspeita de tráfico de influência no governo em conjunto com Fábio Luís Lula da Silva, o Lulinha, filho mais velho do presidente. Em nota divulgada à imprensa, Marco Aurélio disse que o pagamento foi um “empréstimo pessoal contraído e já quitado”. Marcola, como ele é conhecido, deixou o cargo no governo Lula no último dia 21 de julho para integrar a equipe da campanha do presidente. A transação entre Roberta e Marcola foi citada pela Polícia Federal no pedido de abertura de inquérito para apurar tráfico de influência de Lulinha no Ministério da Saúde e no Palácio do Planalto. Uma das hipóteses sob investigação é se o pagamento seria propina para abrir portas no governo. A existência da transação foi divulgada pelo sitePoder360 e confirmada pelo Estadão. No cenário internacional, Lula recebeu outra surpresa nesta terça-feira, 4, com a revogação do visto da embaixadora brasileira Maria Luiza Ribeiro Viotti pelo governo dos EUA. A diplomata teve sua permanência colocada em xeque após o governo brasileiro recusar o visto de funcionários americanos no mês passado, além de ainda não ter formalizado a autorização para que Daniel Perez assuma a embaixada dos EUA em Brasília. O cancelamento do visto dela somente será revogado quando o governo brasileiro concordar com a indicação de Perez e solucionar a pendência diplomática, avisou a jornalistas um funcionário do Departamento de Estado. Assine por R$1,90/mês e tenha acesso ilimitado ao conteúdo do Estadão.Acesse: https://bit.ly/oferta-estadao O 'Estadão Analisa' é transmitido ao vivo de segunda a sexta-feira, às 7h, no Youtube e redes sociais do Estadão. Também disponível no agregador de podcasts de sua preferência. Apresentação: Carlos AndreazzaEdição/Produção: Jefferson PerlebergCoordenação: Renan PagliarusiSee omnystudio.com/listener for privacy information.
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
Empreender no Brasil exige muito mais do que resiliência operacional; exige inteligência estratégica para navegar em um ambiente fiscal complexo e altamente punitivo. Thiago Alves, advogado tributarista e fundador da Alvus, revela como a falta de planejamento estruturado transforma o Estado em um sócio oculto que recolhe a maior parte dos resultados antes mesmo de o empresário ver a cor do lucro. Neste episódio do Excepcionais, Marcelo Toledo conversa com Thiago Alves sobre a realidade nua e crua dos bastidores fiscais e patrimoniais do país. Da armadilha do Simples Nacional — que pode retroagir com multas pesadas — à construção de holdings e estruturas sob jurisdições internacionais, o diálogo entrega um guia pragmático sobre como jogar rigorosamente dentro das quatro linhas para pagar apenas o estritamente justo e proteger o patrimônio construído com o suor do seu trabalho.Disponivel Também no Youtube:https://youtu.be/kLjxsS8CZoM00:00:00 - A realidade do sócio "César" e a busca pela eficiência tributária 00:03:00 - O limite do Simples Nacional e o risco de desenquadramento retroativo 00:06:16 - Rastreamento de dados via PIX e o fim da informalidade operacional 00:08:19 - A criminalização de empresários por erros na formação de preço 00:11:00 - A diferença prática entre os regimes do Lucro Real e Lucro Presumido 00:21:50 - Oportunidades ocultas de recuperação de crédito no Lucro Real 00:33:00 - Consolidação de mercado e operações de M&A viabilizadas por tributos 00:49:00 - Proteção de ativos real e estruturação em jurisdições internacionais 01:02:00 - As transformações trazidas pela Reforma Tributária e o impacto no consumo Siga o Thiago no Instagram:https://www.instagram.com/thiagoalvus/Nos Siga:Marcelo Toledo: https://www.instagram.com/marcelotoledoInstagram: https://www.instagram.com/excepcionaispodcastTikTok: https://www.tiktok.com/@excepcionaispodcast
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
Late payments have become so common that many businesses simply accept them as part of commercial life. But should they? In this episode of Tech Talks Daily, I speak with Pat Bermingham, founder and CEO of Adflex, about why late payments continue to cost the UK economy an estimated £11 billion every year, why thousands of businesses fail because of cash flow pressures, and how technology could help change payment behavior rather than simply respond to it. Pat argues that late payments are rarely an administrative accident. In many industries they have become an informal financing mechanism, allowing larger organizations to protect their own cash flow while placing increasing financial pressure on smaller suppliers. Construction is one example, but the challenge extends across many sectors where long supply chains and uneven bargaining power make delayed payments the norm rather than the exception. We discuss why new government proposals to strengthen payment regulations represent progress, while also examining why legislation alone cannot solve a structural problem that has developed over decades. Instead, Pat believes technology can play a much bigger role. He explains how virtual commercial cards and Straight Through Processing (STP) allow buyers to access extended finance while suppliers receive payment far more quickly, without introducing additional friction into the payment process. Rather than forcing suppliers to accept card payments directly, the technology automates the process behind the scenes while improving reconciliation, increasing visibility and supporting healthier cash flow across the supply chain. The conversation also explores why many organizations still rely on fragmented payment systems created through years of acquisitions and disconnected technologies. Modernizing payment infrastructure can reduce delays, improve operational efficiency and help businesses build stronger supplier relationships rather than treating late payment as a normal business practice. Pat also shares how an earlier career as a music producer shaped his thinking about technology. Watching digital innovation transform music production helped him recognize how technology can simplify complex processes while also creating new business models that challenge established industries. For finance leaders, procurement teams, CIOs and business owners, this episode provides practical insights into improving cash flow, strengthening supplier relationships, modernizing payment processes and preparing for a future where prompt payment becomes both a commercial advantage and an increasing regulatory expectation. Changing payment legislation is important. Changing payment behavior is what will ultimately strengthen businesses, protect suppliers and create more resilient supply chains.
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
What prevents a successful AI experiment from becoming a dependable production system that delivers measurable business value? In this episode of Tech Talks Daily, I speak with Ed Macosky, Chief Product and Technology Officer at Boomi, about AI pilot purgatory, integration, governance, model selection, token costs, and the technical skills businesses may need as adoption grows. Ed leads Boomi's product and engineering teams while also using AI tools inside his own organization. That gives him a view from both sides: creating technology for enterprise customers and applying it within active product development workflows. He believes many AI pilots begin with the wrong question. Teams become interested in the latest model or feature before defining the business problem they want to solve. The experiment may work during a demonstration, then fail when it encounters real data, access controls, security policies, and production systems. Placing company information inside a data lake and adding a language model does not automatically create a business application. The system must access current data reliably, respect employee permissions, connect with existing applications, and operate within governance rules that security teams can approve. Ed recommends beginning with a defined business opportunity and establishing the access required to support it. Existing APIs can already provide authentication, permissions, and governance. MCP can offer another route into enterprise systems, but those connections still require security, monitoring, and management. Team alignment also matters. An AI center may be racing to test models while an integration center concentrates on a different set of priorities. When those groups fail to coordinate, the pilot lacks the connectivity and automation required to become part of a production workflow. The discussion then turns toward fragmentation. Every technology wave produces new vendors, frameworks, and specialist tools. Early experimentation benefits from variety, but mature companies can eventually find themselves maintaining a complicated collection of products held together with custom code and, occasionally, the digital equivalent of duct tape. Ed does not recommend placing every function with one provider. He does argue for enough consolidation and abstraction to prevent experimentation from creating years of technology debt. Governance and observability should also work horizontally across different environments, including platforms such as SAP, Salesforce, and several AI model providers. That becomes increasingly important as businesses introduce autonomous agents. Leaders need to know which agents exist, what systems they can access, what actions they can take, and how each decision is recorded. AI gateways and agent control towers can provide a wider view across otherwise separate technology environments. Ed also introduces the idea of the frontier engineer. A prompt engineer concentrates on communicating effectively with a model. A frontier engineer understands how the model works, including its logic, mathematics, algorithms, and suitability for different workloads. He does not believe every company needs a large team of these specialists. However, he argues that enterprises need at least one person capable of assessing vendor claims and deciding whether a frontier model, specialist model, or open weight model fits a particular workload. Cost creates another reason to examine model selection. Sending every employee request or agent task to the most capable frontier model can become expensive. Some repeatable workloads may run on open weight models inside the company's cloud or hardware environment, giving finance teams greater cost certainty. Boomi is developing Boomi Prompt to route requests according to their complexity and requirements. A simple factual request might go directly to an API. A forecasting task may use a smaller model. A difficult analytical request could be sent to a frontier model. Ed uses the weather as a helpful example. Retrieving next Tuesday's forecast does not require a language model when a public weather API can return the answer directly. Asking a model to perform every form of automation wastes tokens, computing power, energy, and money. The episode closes with practical advice for CIOs. Avoid starting with a broad objective such as agentifying the entire business. Choose a department, identify a small number of tasks, define the expected return, and work backward. Once the team proves value and understands the operating requirements, it can repeat the process elsewhere. Could intelligent routing, stronger integration, and clearer business outcomes finally move enterprise AI beyond pilot purgatory? Listen to the episode and share your thoughts with me.
GARANTA SUA VAGA NO LUCRO 2X COM GRUPO PRIMO + G4CUPOM: SOCIOS NA OFICINACONHEÇA OS PRODUTOS DA CAFFEINE ARMYEm um ambiente de negócios cada vez mais desafiador — com juros altos, carga tributária, competição intensa e mudanças tecnológicas aceleradas — crescer de forma sustentável no Brasil exige muito mais do que uma boa ideia.Afinal, o que separa empresas que crescem, lucram e permanecem de pé daquelas que quebram no caminho? Até que ponto o cenário brasileiro é realmente um obstáculo — e quando ele vira desculpa para uma gestão fraca? É possível dobrar faturamento e lucro em apenas 12 meses sem colocar o negócio em risco?Para responder essa e outras perguntas, recebemos Tallis Gomes, Alfredo Soares e Bruno Nardon, fundadores do G4 Educação, para o episódio 309 do Podcast Os Sócios. Falamos sobre os erros mais caros no crescimento de uma empresa, o papel do líder nas decisões difíceis, a importância de escolher sócios complementares, a construção de uma cultura de vendas e como a inteligência artificial pode transformar a gestão, a eficiência e a competitividade dos negócios. Também percorremos a história do G4 — das trajetórias de Tallis Gomes, Bruno Nardon e Alfredo Soares ao encontro entre os três e à construção de uma das maiores empresas de educação e tecnologia para negócios do Brasil.Ele será transmitido nesta quinta-feira (30/07), às 12h, no canal Os Sócios Podcast.Hosts: Bruno Perini @bruno_perini e Malu Perini @maluperiniConvidados: Tallis Gomes @tallisgomes Bruno Nardon @bruno.nardon e Alfredo Soares @alfredosoaresSua marca no podcast Os Sócios: publicidade@timeprimo.com
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
The Cybercrime Wire, hosted by Scott Schober, provides boardroom and C-suite executives, CIOs, CSOs, CISOs, IT executives and cybersecurity professionals with a breaking news story we're following. If there's a cyberattack, hack, or data breach you should know about, then we're on it. Listen to the podcast daily and hear it every hour on WCYB. The Cybercrime Wire is brought to you Cybercrime Magazine, Page ONE for Cybersecurity at https://cybercrimemagazine.com. • For more breaking news, visit https://cybercrimewire.com
PODCAST EPISODE | An Analog Brain In A Digital Age With Marco Ciappelli Fifteen years ago, Rose Ross brought a client an idea for an awards program built specifically for enterprise tech startups. The client passed. She built it herself — and the Tech Trailblazers have been running ever since, independent, judged by practitioners, and open for entries until 3 September.
AI for business leaders doesn't have to be complicated. Learn practical AI and cybersecurity strategies in under three minutes with Eric Twiggs every Monday.
What does it really take to build an AI-ready enterprise when your data is fragmented, teams operate in silos, and years of technology decisions have created complexity that no large language model can magically fix? In this episode of Tech Talks Daily, I speak with Raymon Ohmori, Senior Principal Software Engineer at Valiantys, and Jiecheng Dong, Senior Software Engineer at Valiantys, about the work that goes into enterprise AI adoption and why successful AI transformation begins long before companies deploy agents, copilots, or autonomous workflows. Using Valiantys' work with Mercedes as a case study, Raymon and Jiecheng explain how modernizing software delivery and connecting data across teams can create the foundation required for AI systems to deliver meaningful business value. We discuss why fragmented data, organizational silos, poor governance, and unclear business problems continue to prevent many companies from moving beyond AI pilots. The conversation examines what it means to become AI-ready in practice. Jiecheng explains why enterprises need performant, structured, and queryable data rather than simply feeding huge volumes of information into large language models. Raymon shares why businesses must begin with real problems, stakeholder needs, and clearly defined outcomes to justify the cost of AI and successfully move projects into production. We also discuss the growing role of agentic AI and autonomous workflows in software engineering. How should engineering teams prepare AI agents to become active participants in software development? What tools, context, permissions, governance, and observability do these systems need to operate effectively? And why might treating an AI agent more like a new colleague than another software tool help teams think differently about deployment? Raymon and Jiecheng also share their perspectives on AI-assisted software development and developer productivity. As AI becomes increasingly capable of writing code, the role of the software engineer is shifting toward architecture, system design, requirements gathering, trade-off evaluation, and translating business needs into technical specifications. We also discuss the challenge facing junior developers and why companies still need to create pathways for new engineering talent. Finally, we examine the practical steps CIOs, CTOs, and engineering leaders can take today to build more connected, AI-enabled enterprises. From improving data ownership and governance to identifying costly problems that AI can realistically solve, this conversation offers a practical guide for companies trying to move from AI experimentation to production systems that deliver measurable value. Where is your company on its AI journey? Are fragmented data, organizational silos, and unclear business problems preventing your AI projects from reaching production, or have you found effective ways to turn experimentation into measurable results? Share your thoughts with me. Useful Links Valiantys Website: https://www.valiantys.com/ Valiantys LinkedIn: https://www.linkedin.com/company/valiantys/
What happens when AI moves beyond writing emails and summarizing meetings and starts influencing who gets hired, promoted, and paid? In this episode of Tech Talks Daily, I speak with David Lloyd, Chief AI Officer at Dayforce, about why HR is becoming one of the highest-stakes environments for artificial intelligence and how companies can introduce AI while protecting employee data, maintaining human accountability, and preparing for growing regulatory scrutiny. HR systems contain some of the most sensitive information companies hold, from salaries and performance records to benefits and personal data. At the same time, AI is increasingly being introduced across recruitment, workforce management, compensation, performance, and employee experience. David explains why this combination creates enormous opportunities but also places greater responsibility on employers to understand how AI systems operate and how decisions are made. A major theme throughout our conversation is the role of AI governance. David challenges the assumption that governance slows innovation, arguing that the right processes can help companies evaluate AI ideas quickly while reducing the risk of introducing systems that lack appropriate data, transparency, or regulatory safeguards. Dayforce recently achieved ISO/IEC 42001 certification for AI management systems and NIST AI Risk Management Framework attestation. David explains what independent validation means in practice and why companies evaluating AI vendors should ask for evidence of how systems are governed, tested, monitored, and audited. We also discuss the principle of "AI by choice." David argues that CIOs and HR leaders should never discover that a new AI capability has suddenly been activated across hundreds of employees without their knowledge. Companies need visibility into where AI is being used, what data employees can provide to models, and whether customer information is being used to train external AI systems. The conversation examines AI literacy and why HR leaders need to become comfortable with the technology themselves before guiding employees through changes to jobs and working practices. Employees are already experimenting with AI, sometimes through personal tools outside approved company systems. Rather than ignoring this behavior, David explains why companies should provide safe environments where people can learn while establishing clear rules around sensitive data. Human accountability remains central as AI takes on more responsibility. David discusses why people using AI should remain accountable for its outputs and why human oversight matters when technology influences decisions involving recruitment, compensation, performance, and careers. For CEOs, CHROs, CIOs, HR technology leaders, and anyone responsible for enterprise AI, this conversation provides practical guidance on responsible AI adoption, employee data, AI bias, model monitoring, regulatory compliance, vendor selection, and building AI governance that can stand up to scrutiny. The lesson is that governance does not have to be a brake on AI adoption. Done well, it can give companies the structure and confidence to move faster, make better decisions about where AI belongs, and continue using the technology when regulators, employees, customers, and boards start asking harder questions. https://www.dayforce.com/ https://www.linkedin.com/company/dayforce/ https://www.linkedin.com/in/dtlloyd/
Could the disaster recovery plan designed to protect your company make a ransomware incident even worse? In this episode, I speak with Darren Thomson, Vice President and Chief Technology Officer for EMEA at Commvault, about Resilience Operations, commonly known as ResOps, and why cyber recovery now requires security, infrastructure, identity and data teams to work from one coordinated plan. Darren argues that many companies are accepting a difficult reality. Even with considerable investment in prevention and detection, a breach may eventually succeed. That does not make cybersecurity controls any less necessary, but it means recovery can no longer be treated as a secondary activity managed by another department. The problem is that security operations and infrastructure teams have traditionally worked toward different objectives. Security specialists concentrate on identifying and stopping threats. Infrastructure teams protect data, maintain backups and restore systems after outages. During a cyberattack, a successful recovery requires both sets of expertise. A backup administrator may be able to restore data quickly, but a forensic specialist must establish whether that data is clean. Without that confirmation, the company risks restoring malware and restarting the incident. Darren explains why a conventional disaster recovery plan may be particularly dangerous during ransomware. These plans were commonly designed for physical failures such as a lost data center. Data would be copied from one location to another so operations could continue. If the source data is infected, however, fast replication can carry the malware into the recovery environment. This is where ResOps enters the discussion. Darren describes it as an operating model rather than a product. It combines established practices from security and infrastructure management into a continuous program for testing, learning and improving recovery. Individual technology projects may come from the program, but resilience itself never reaches a final completion date. AI adds pressure on both sides. Criminals can use it to create faster and more effective attacks, while defenders can use machine learning to inspect large volumes of information, detect patterns and identify the newest clean recovery point. Companies must also protect AI systems as they would any other business application, including the models, data repositories and identities connected with them. Darren offers one practical starting point for CIOs and CISOs: Mean Time to Clean Recovery, or MTCR. This measures how long it takes to restore an application and its data with evidence that both are free from compromise. Before measuring MTCR, leaders must define their minimum viable company. These are the systems and services the business cannot operate without. Once that list exists, teams can test how long a verified clean recovery would take and replace assumptions with evidence. The initial answer may be uncomfortable. Teams may know how to restore an application without knowing whether the backup is clean. Security may know how to inspect the system but lack an established workflow with the recovery team. Darren sees those gaps as the starting point for a useful ResOps program because they provide everyone with a shared problem and a measurable objective. If your most important systems disappeared today, how long would it take to bring the minimum viable company back using verified clean data? Listen to the episode and share your answer with me.
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