The Tech Blog Writer Podcast

In this episode of Tech Talks Daily, I'm joined by Kiren Sekar, Chief Product Officer at Samsara, to unpack how AI is finally showing up where it matters most, in the frontline operations that keep the global economy moving. From logistics and construction to manufacturing and field services, these industries represent a huge share of global GDP, yet for years they have been left behind by modern software. Kiren explains why that gap existed, and why the timing is finally right to close it. We talk about Samsara's full-stack approach that blends hardware, software, and AI to turn trillions of real-world data points into decisions people can actually act on. Kiren shares how customers are using this intelligence to prevent accidents, cut fuel waste, digitize paper-based workflows, and scale expert judgment across thousands of vehicles and job sites. The conversation goes deep into real examples, including how large enterprises like Home Depot have dramatically reduced accident rates and improved asset utilization by making safety and efficiency part of everyday operations rather than afterthoughts. A big part of our discussion focuses on trust. When AI enters physical operations, concerns around monitoring and surveillance surface quickly. Kiren walks through how adoption succeeds only when technology is introduced with care, transparency, and a clear focus on protecting workers. From proving driver innocence during incidents to rewarding positive behavior and using AI as a virtual safety coach, we explore why change management matters just as much as the technology itself. We also look at the limits of automation and why human judgment still plays a central role. Kiren explains how Samsara's AI acts as a force multiplier for experienced frontline experts, capturing their hard-won knowledge and scaling it across an entire workforce rather than trying to replace it. As AI moves from pilots into daily decision-making at scale, this episode offers a grounded view of what responsible, high-impact deployment actually looks like. As AI continues to reshape frontline work, making jobs safer, easier, and more engaging, how should product leaders balance innovation with responsibility when their systems start influencing real-world safety and productivity every single day? Useful Links Connect with Kiren Sekar Learn more about Samsara Tech Talks Daily is Sponsored by Denodo

What if airlines stopped thinking in terms of seats and schedules and started designing for the entire journey instead? In this episode of Tech Talks Daily, I'm joined by Somit Goyal, CEO of IBS Software, to talk about how travel technology is being rebuilt at its foundations. Since we last spoke, AI has moved from experimentation into everyday operations, and that shift is forcing airlines to rethink everything from retailing and loyalty to disruption management and customer trust. Somit shares why AI can no longer sit on the edge of systems as a feature, and why it now has to be embedded directly into how decisions are made across the business. We discuss the growing gap between legacy airline technology and rapidly rising traveler expectations, and why this tension has become a defining moment for the industry. For Somit, travel tech is no longer back office infrastructure. It is becoming the operating system for customer experience and revenue. That shift changes how airlines think about retailing, moving away from selling flights toward curating outcomes across a multi day journey that includes partners, servicing, and real time operational awareness. The conversation also explores why agility now matters more than scale, and how airlines are approaching this transformation without breaking what already works. A major part of this episode focuses on IBS Software's deep co-innovation partnership with Amazon Web Services. Somit explains why this is far more than a cloud hosting arrangement, covering joint R&D, shared roadmaps, and AI labs designed to help airlines build modern retailing capabilities faster. We also unpack what "AI first" really means in practice, how intelligence is reshaping offer creation, pricing, order management, and disruption handling, and why responsible AI must be treated as a product rather than a legal safeguard. We also spend time on loyalty, one of the industry's most stubborn challenges. Somit outlines why converging reservations and loyalty systems is such a powerful unlock, how it enables real time personalization instead of generic segmentation, and why loyalty should evolve from a points ledger into an experience engine that delivers value before, during, and after a trip. As airlines race toward 2026, the big question is no longer whether transformation will happen, but who will move with enough clarity and trust to earn long-term loyalty. In a world where AI knows more about travelers than ever before, how do airlines use that intelligence to create better outcomes without crossing the line, and are they ready to rethink the journey from end to end? Useful Links Connect with Somit Goyal Learn more about IBS Software Tech Talks Daily is Sponsored by Denodo  

What happens when a podcast stops being something you listen to and becomes something you physically show up for? In this episode of Tech Talks Daily, I wanted to explore a different kind of tech story, one rooted in community, endurance, and real human connection. I was joined by Sam Huntington, a Business Development Officer at Wells Fargo, who has quietly built something special at the intersection of technology, entrepreneurship, and cycling through his podcast and community project, Hill Climbers. Sam's story starts far from a studio. It begins on a bike, moving through Philadelphia, Los Angeles, and eventually Austin, where chance conversations on group rides turned into friendships, business relationships, and eventually a podcast. We talk about why endurance sports and startups share the same mental terrain, the moments when you want to quit, and how those moments often define the outcome. Sam explains how Hill Climbers evolved from recorded conversations into weekly rides, live podcast tapings, and in person events that bring founders, investors, and operators together without name badges or pitch decks. We also dig into what makes Austin such a magnetic place for founders right now, and why community building outside Silicon Valley feels different when it is built around shared effort rather than curated networks. Sam shares lessons learned from taking a podcast offline, including the early weeks when hardly anyone showed up, the temptation to stop, and the persistence required to build momentum. There is a refreshing honesty in how he describes growing something slowly, resisting shortcuts, and letting trust compound over time. This conversation is also a reminder that meaningful networks are rarely built through algorithms. They are built through shared experiences, discomfort, friendly competition, and showing up consistently when no one is watching. Whether you are a founder, an investor, or someone trying to build a community of your own, there is something grounding in hearing how relationships form when work is not the opening line. As more of our professional lives move online, are we losing the spaces where real connection happens, and what would it look like for you to build community around a shared passion rather than a job title? Userful Links Connect with Sam Huntington Hill Climbers Website Instagram Tech Talks Daily is Sponsored by Denodo

What happens to patient care when hospital systems suddenly go dark and clinicians are forced back to pen and paper in the middle of a crisis? In this episode of the Tech Talks Daily Podcast, I speak with Chao Cheng-Shorland, Co-founder and CEO of ShelterZoom, about a problem that many healthcare leaders still underestimate until it is too late. As ransomware attacks, cloud outages, and system failures become more frequent, electronic health record downtime has shifted from a rare incident to a recurring operational risk with real consequences for patient safety, staff wellbeing, and hospital finances. Chao explains why traditional disaster recovery plans fall short in live clinical environments and why returning to paper workflows is no longer viable for modern healthcare teams. We discuss how EHR downtime can stretch from hours into weeks, how reimbursement delays and cash flow pressure compound the damage, and why younger clinicians are often unprepared for manual processes they were never trained to use. The conversation also explores the mindset shift now taking place among CIOs and CISOs, as resilience moves from a compliance checkbox to a survival requirement. At the heart of the discussion is ShelterZoom's SpareTire platform and the thinking behind treating uninterrupted access to clinical data as a baseline rather than a backup. Chao shares how the idea emerged directly from hospital conversations, why an external, always-available system is essential during cyber incidents, and how ShelterZoom's tokenization roots shaped a design focused on security without disruption. We also look at how rising AI adoption is changing the threat landscape and why many healthcare organizations are reordering priorities to secure continuity before rolling out new AI initiatives. As we look toward 2026, this episode offers a grounded view of how healthcare organizations must rethink downtime tolerance, data governance, and operational readiness in a world where digital outages can quickly become clinical emergencies. If downtime is now inevitable rather than hypothetical, what does real resilience look like for hospitals, and are healthcare leaders moving fast enough to protect patients when systems fail? Useful Links Connect with Chao Cheng-Shorland Learn more about ShelterZoom Tech Talks Daily is Sponsored by Denodo

Is your website still the front door to your business, or has AI already quietly changed where customers first meet your brand? In this episode of the Tech Talks Daily Podcast, I sit down with Dominik Angerer, Co-founder and CEO of Storyblok, to unpack how content, search, and discovery are shifting in an AI-first world. As search behavior moves away from blue links toward direct answers inside tools like ChatGPT and Google summaries, Dominik explains why many businesses are seeing traffic decline even while signups and conversions continue to grow. We explore how AI is reshaping the role of content management systems, from automation and orchestration to personalization at scale. Dominik shares why consistency now matters more than volume, how outdated content can actively harm brand visibility inside AI answers, and why the technical foundations built for SEO still play a major role as generative search takes hold. This conversation also dives into headless CMS architecture, why separating content from presentation has become even more valuable, and how structured, well maintained content gives AI systems something reliable to work with. Dominik also introduces the idea of joyful content, a belief that better tools lead to better work and ultimately better experiences for audiences. From AI-powered support workflows to personalized retail and loyalty experiences, he shares real examples of how forward-looking teams are already using content as an active system rather than a static archive. As businesses look toward 2026 and rethink how they show up across websites, apps, agents, and answer engines, this episode offers a grounded look at what needs to change and where to start. As AI becomes the place people go for answers rather than search results, how are you rethinking your content strategy, and what will you do differently after hearing this conversation? Connect with Dominik Angerer Learn more Storyblok Tech Talks Daily is Sponsored by Denodo

What happens when the push for smarter crypto wallets runs headfirst into the reality that everything on a public blockchain can be seen by anyone? In this episode of Tech Talks Daily, I wanted to take listeners who may not live and breathe Web3 every day and introduce them to a problem that is becoming harder to ignore. As Ethereum evolves and smart accounts unlock new wallet features, the surface area for risk grows at the same time. That is where privacy-first Layer 2 solutions enter the conversation, not as an abstract idea, but as a practical response to very real security and usability concerns. My guest is Joe Andrews, Co-founder and President at Aztec Labs. Joe brings an engineering mindset shaped by years of building consumer-facing applications and deep privacy infrastructure. Together, we unpack why privacy and security can no longer be treated as separate topics, especially as Ethereum rolls out more advanced account features. Joe explains how privacy-first Layer 2 networks act as an added line of defense, reducing exposure to threats that come from fully transparent balances, identities, and transaction histories. We also talk about what Aztec actually is, often described as the Private World Computer, and why that framing matters. Joe shares learnings from Aztec's public testnet launch earlier this year, what surprised the team once thousands of nodes were running in the wild, and how the community has stepped up in ways the company itself could not have planned for. There is also an honest discussion about the UK crypto scene, the missed opportunities, and the quiet resilience of builders who continue to ship despite regulatory uncertainty. As we look ahead, Joe outlines what comes next as Aztec moves closer to enabling private transactions on a decentralized network, and why the next phase is less about theory and more about real people using privacy in everyday interactions. If you are curious about how privacy-first Layer 2 solutions fit into Ethereum's roadmap, or why privacy might be the missing piece that finally makes smart wallets usable at scale, does this conversation change how you think about the future of crypto, and where would you like to see this technology go next? Useful Links Connect with Joe Andrews Learn more about Aztec Labs Tech Talks Daily is Sponsored by Denodo

What happens when the systems designed to make life easier quietly begin shaping how we think, decide, and choose? In this episode of the Tech Talks Daily Podcast, I sit down with Jacob Ward, a journalist who has spent more than two decades examining the unseen effects of technology on human behavior. From reporting roles at NBC News, Al Jazeera, CNN, and PBS, to hosting his own podcast The Rip Current, Jacob has built a career around asking uncomfortable questions about power, persuasion, and the psychology sitting beneath our screens. Our conversation centers on his book The Loop: How A.I Is Creating a World Without Choices and How to Fight Back, written before ChatGPT entered everyday life. Jacob explains why his core concern was never about smarter machines alone, but about what happens when AI systems learn us too well. Drawing on behavioral science, newsroom experience, and recent academic research, he argues that AI can narrow our sense of possibility while convincing us we are gaining freedom. The result is a subtle tension between convenience and control that many listeners will recognize in their own digital lives. We also explore the idea of AI companies behaving like nation states, accumulating talent, influence, and authority without the checks that usually accompany that kind of power. Jacob reflects on the speed of AI deployment, the belief systems driving its biggest champions, and why individual self control is unlikely to be enough. Instead, he makes the case for systemic responses, cultural guardrails, and a renewed focus on protecting human skills that cannot be automated away. There is room for optimism here too. We talk about where AI genuinely helps, from medicine to scientific discovery, and how leaders can hold hope and skepticism at the same time without slipping into hype or fear. From preserving entry level work as a form of apprenticeship to resisting the urge to outsource thinking itself, this episode offers a thoughtful look at what staying human might mean in an age of intelligent machines. Jacob has also appeared on shows like The Joe Rogan Experience, This Week in Tech, and The Don Lemon Show, but this conversation strips things back to fundamentals. How much choice do we really have, and what are we willing to give up for frictionless answers? If AI is quietly closing the loop around our decisions, what does fighting back actually look like for you, and where do you think that line between help and influence should be drawn? Useful Links Connect With Jacob Ward Check out his website and book

How is HR changing when AI, economic pressure, and rising employee expectations all collide at once? In this episode of Tech Talks Daily, I'm joined by Simon Noble, CEO of Cezanne HR, to unpack how the role of HR is evolving from a traditional support function into something far more closely tied to business performance. Simon shares why HR is increasingly being judged on outcomes like retention, capability building, and readiness for change, rather than policies, processes, or cost control. Yet despite that shift, many HR leaders still find themselves pulled back into a compliance-first mindset as budgets tighten, skills shortages persist, and new legislation raises the stakes. We explore how AI fits into this picture without stripping the humanity out of HR. Simon is clear that AI should automate administration and free up time, rather than replace human judgment or empathy. Used well, it removes friction from onboarding, compliance, and everyday queries, giving HR the space to focus on culture, leadership, and long-term talent development. Used poorly, it risks adding noise without value. The difference, he argues, comes down to data. Without clean, consolidated data, AI simply cannot deliver meaningful insight, no matter how advanced the technology appears. The conversation also looks inward at Cezanne HR's own growth journey. Simon describes rapid expansion as chaos with better branding, and explains why maintaining culture, trust, and clarity becomes harder, yet more important, as teams scale. From onboarding new employees to ensuring a consistent customer experience, the same principles apply internally as they do for customers using HR technology. We also touch on trust, transparency, and the growing focus on areas like pay transparency, data responsibility, and employee confidence in how their information is handled. As expectations continue to rise, HR's credibility increasingly rests on accuracy, fairness, and the ability to turn insight into action. As HR steps closer to the center of business strategy, what mindset shift is needed to move from reacting to change toward actively shaping it, and how prepared is your organization to make that leap? Useful Links Connect with Simon Noble Learn more about Cezanne HR Tech Talks Daily is Sponsored by Denodo

What does it really mean when AI moves from answering questions to making decisions that affect real people, real money, and real outcomes? In this episode of Tech Talks Daily, I'm joined by Joe Kim, CEO of Druid AI, for a grounded conversation about why agentic AI is becoming the focus for enterprises that have moved beyond experimentation. After years of hype around generative tools, many organizations are now facing a tougher question. Can AI be trusted to take action inside core business processes, and can it do so with the accuracy, security, and accountability that enterprises expect? Joe brings a rare perspective shaped by decades leading large-scale enterprise software companies, including his time as CEO of Sumo Logic. He explains why Druid AI deliberately avoids positioning itself as a generative AI company, and instead focuses on systems that can make decisions, trigger workflows, and complete tasks inside regulated, high-stakes environments. We unpack why accuracy thresholds matter when AI touches billing, healthcare, admissions, or compliance, and why security and governance are no longer secondary concerns once AI is allowed to act. We also talk about scale and proof. Druid AI now supports over 120 million conversations every month, a figure that keeps climbing as enterprises move agentic systems into production. Joe shares how those conversations translate into measurable business outcomes, from operational efficiency to revenue growth, and why many AI initiatives fail to reach this stage. His "5 percent club" philosophy cuts through the noise, focusing on the small number of use cases that actually deliver return while most others stall in pilots. The conversation also explores why higher education has become a surprising pressure point for AI adoption, how outdated systems contribute to student churn, and how conversational agents can remove friction at moments that decide whether someone enrolls, stays, or leaves. We close by looking ahead at Druid AI's next chapter, including new platform capabilities designed to make building and deploying agents faster without sacrificing control. As more enterprises demand results instead of promises, are we ready to judge AI by the decisions it makes and the outcomes it delivers, and what should that accountability look like in your organization? I'd love to hear your thoughts. Where do you see agentic AI delivering real value today, and where do you think the risks still outweigh the rewards? What does it really mean when AI moves from answering questions to making decisions that affect real people, real money, and real outcomes? In this episode of Tech Talks Daily, I'm joined by Joe Kim, CEO of Druid AI, for a grounded conversation about why agentic AI is becoming the focus for enterprises that have moved beyond experimentation. After years of hype around generative tools, many organizations are now facing a tougher question. Can AI be trusted to take action inside core business processes, and can it do so with the accuracy, security, and accountability that enterprises expect? Joe brings a rare perspective shaped by decades leading large-scale enterprise software companies, including his time as CEO of Sumo Logic. He explains why Druid AI deliberately avoids positioning itself as a generative AI company, and instead focuses on systems that can make decisions, trigger workflows, and complete tasks inside regulated, high-stakes environments. We unpack why accuracy thresholds matter when AI touches billing, healthcare, admissions, or compliance, and why security and governance are no longer secondary concerns once AI is allowed to act. We also talk about scale and proof. Druid AI now supports over 120 million conversations every month, a figure that keeps climbing as enterprises move agentic systems into production. Joe shares how those conversations translate into measurable business outcomes, from operational efficiency to revenue growth, and why many AI initiatives fail to reach this stage. His "5 percent club" philosophy cuts through the noise, focusing on the small number of use cases that actually deliver return while most others stall in pilots. The conversation also explores why higher education has become a surprising pressure point for AI adoption, how outdated systems contribute to student churn, and how conversational agents can remove friction at moments that decide whether someone enrolls, stays, or leaves. We close by looking ahead at Druid AI's next chapter, including new platform capabilities designed to make building and deploying agents faster without sacrificing control. As more enterprises demand results instead of promises, are we ready to judge AI by the decisions it makes and the outcomes it delivers, and what should that accountability look like in your organization? I'd love to hear your thoughts. Where do you see agentic AI delivering real value today, and where do you think the risks still outweigh the rewards? Useful Links Connect with Joe Kim, CEO of Druid AI. Druid AI Website Tech Talks Daily is Sponsored by Denodo  

The world is building data centers, identity rails, and AI policy stacks at a speed that makes 2026 feel closer than it is. In this conversation, Rajesh Natarajan, Global Chief Technology Officer at Gorilla Technology Group, explains what it takes to engineer platforms that remain reliable, secure, and sovereign-ready for decades, especially when infrastructure must operate outside the safety net of constant cloud connectivity. Raj talks about quantum-safe networking as a current risk, not a future headline. Adversaries are capturing encrypted traffic today, betting on decrypting it later, and retrofitting quantum-safe architecture into national platforms mid-lifecycle is an expensive mistake waiting to happen. He also highlights the regional nature of AI infrastructure, Southeast Asia prioritizing sovereignty, speed, and efficiency, Europe leaning on regulation and telemetry, and the U.S. betting on raw cluster scale and throughput. Sustainability at Gorilla isn't a marketing headline, it's an engineering requirement. If a system can't prove its environmental impact using telemetry like workload-level PUE, it isn't labeled sustainable internally. Gorilla applies the same rigor to IoT insight per unit of energy, device lifecycles, and edge-level intelligence placement, minimizing data centralization without operational justification. This episode offers marketers, founders, and technology leaders a rare chance to understand what national-scale resilience looks like when platform alignment breaks first, not technology. Remembering that decisions must be reversible, explicit, and measurable is the foundation of how Gorilla is designing systems that can evolve without forcing rushed compromises when uncertainty becomes reality. Useful links: Connect with Dr Rajesh Natarajan Gorilla website Tech Talks Daily is Sponsored by Denodo  

What makes live events feel personal in an age of algorithms making the calls? That's the tension marketers are living in right now. Ben Kruger, Chief Marketing Officer at Event Tickets Center, sits at the center of this shift. He has spent 20 years shaping server-side systems and performance marketing strategies, including a decade of persistence chasing a role at Google before landing a position in New York just as eCommerce demand went into overdrive during the pandemic. Now, at ETC, he runs marketing for more than 130,000 live events simultaneously. It's a scale that forces automation to step in. The industry moves in real time, resellers update prices by the hour, artists trend globally overnight, weather can shift demand before a stadium gate opens. Ben credits Google's AI tools and internal models as a competitive advantage, but he also talks openly about the risks. The early excitement of automation gave way to skepticism after seeing unaligned promises from new platforms and unpredictable campaign behavior in tools that remove control from brands. There's a well-rounded argument to explore here. On one side, AI enables a small team to do the work of thousands, writing content at a volume no human team could deliver alone. On the other, removing risk from campaigns, or removing channel-level choices from advertisers, can reduce trust and increase low-quality creative output. Advantage+ tools that make placement decisions automatically, without brand input, might scale reach, but can reduce clarity of intent and control of outcomes. Some CMOs see that as smart acceleration, others see it as an overcorrection that creates opacity and dependency on platforms optimizing for their own incentives. And somewhere in the middle is the opportunity. ETC's approach shows a future where repetition in rapid testing generates sharper insight, where lean teams move faster, where humans stay in the loop to validate outcomes, and where creativity stays grounded in audience understanding, economics, and transparency. Marketers listening to Ben will hear someone who wants experimentation, control, clarity, and long-term audience trust to exist side by side. Useful links: Connect with Ben Kruger on LinkedIn  Event Tickets Center website Tech Talks Daily is Sponsored by Denodo

What does it really take to build software that can grow from a single line of code to millions of users a day without losing its soul along the way? In this episode of Tech Talks Daily, I'm joined by Alex Gusev, CTO at Uploadcare, for a wide-ranging conversation about scale, simplicity, and why leadership in technology starts with people long before it gets anywhere near frameworks or tooling. Alex has spent two decades building server-side systems, often inside small teams, and has seen firsthand how early decisions echo through a company's future, for better and for worse. We talk openly about the realities of early-stage engineering, including why shipping imperfect code is often the only way to survive, how technical debt should be taken on deliberately rather than by accident, and why knowing when to slow down and clean things up is one of the hardest leadership calls to make. Alex shares his belief that simplicity is the strongest ally in high-load environments, and how over-engineering, often inspired by copying the playbooks of much larger companies, creates fragility instead of strength. Our conversation also digs into his continued faith in Ruby on Rails, a framework that divides opinion but still plays a central role in many successful products. Alex reframes the debate around speed, focusing less on raw performance metrics and more on how quickly teams can build, adapt, and maintain systems over time. It's a practical view shaped by real-world trade-offs rather than theory. Beyond code, we explore why Alex puts people ahead of technology and process, and how creating psychological safety inside teams leads to better decisions, lower churn, and smarter use of limited resources. He also reflects on personal experiences that reshaped his approach to leadership, the growing tech scene in Kyrgyzstan, and why he finds as much inspiration in Dostoevsky as he does in engineering blogs. If you've ever questioned whether modern engineering culture has overcomplicated itself, or wondered how to balance ambition with sustainability as your product grows, this episode offers plenty to think about. Where do you think your own team is adding complexity without realizing it, and what might change if you started with people first? Useful Links Connect with Alex Gusev Learn more about Uploadcare Tech Talks Daily is sponsored by Denodo

If you have ever opened Candy Crush over the holidays without thinking about the design decisions behind every swipe, this episode offers a rare look behind the curtain.  I sit down with Abigail Rindo, Head of Creative at King, to unpack how accessibility has evolved from a well-meaning afterthought into a core creative and commercial practice inside one of the world's most recognizable gaming studios.  With more than 200 million people playing King's games each month, Abigail explains why inclusive design cannot be treated as charity or compliance, but as a responsibility that directly shapes product quality, player loyalty, and long-term growth. One of the moments that really stayed with me in this conversation is the data. More than a quarter of King's global player base self identifies as having an accessibility need. Even more players benefit from accessibility features without ever labeling themselves that way. Abigail shares how adjustments like customizable audio for tinnitus, reduced flashing to limit eye strain, and subtle interaction changes can quietly transform everyday play for millions of people. These are not edge cases. They are everyday realities for a massive audience that lives with these games as part of their daily routine. We also dig into how inclusive design sparks better creativity rather than limiting it. Abigail walks me through updates to Candy Crush Soda Saga, including the "hold and drag" mechanic that allows players to preview a move before committing. Inspired by the logic of holding a chess piece before placing it, this feature emerged directly from player research around visibility, dexterity, and comfort. It is a reminder that creative constraints, when grounded in real human needs, often lead to smarter and more elegant solutions. Beyond mechanics and metrics, this conversation goes deeper into storytelling, empathy, and team culture. Abigail explains why inclusive design only works when inclusive teams are involved from the start, and how global storytelling choices help King design worlds that resonate everywhere from Stockholm to Antarctica. We also talk about live service realities, blending quantitative data about what players do with qualitative insight into why they do it, especially when a game has been evolving for more than a decade.  

What does it actually mean to prove who we are online in 2025, and why does it still feel so fragile? In this episode of Tech Talks Daily, I sit down with Alex Laurie from Ping Identity to talk about why digital identity has reached a real moment of tension in the UK. As more of our lives move online, from banking and healthcare to social platforms and government services, the gap between how identity should work and how it actually works keeps widening. Alex shares why the UK now feels out of step with other regions when it comes to online identity schemes, and how heavy reliance on centralized models is slowing adoption while weakening public trust. We spend time unpacking the practical consequences of today's verification systems. Age checks are regularly bypassed, fraud continues to grow, and users are often asked to hand over far more personal data than feels reasonable just to access everyday services. At the same time, public pressure around online safety is rising fast. That creates an uncomfortable push and pull between tighter controls and the expectation of fast, low-friction access.  Alex makes the case that this tension exists because the underlying approach is flawed, and that proving something simple, like age, should never require revealing an entire digital identity. From there, the conversation turns to decentralized identity and why it is gaining momentum globally. Instead of placing sensitive data into large centralized databases, decentralized models allow individuals to hold and present verified credentials on their own terms. For me, this reframes digital identity as a right rather than a feature, and opens the door to systems that feel more privacy-aware, inclusive, and resilient. We also explore how agentic AI could play a role here, helping people manage, present, and protect their credentials intelligently without adding complexity or new risks. With fresh consumer research from Ping Identity informing the discussion, this episode looks closely at where trust, privacy, and identity are heading next, and why the choices made now will shape how we prove who we are online for years to come. Are we finally ready to rethink digital identity, and if so, what does that mean for all of us?

What does it really mean to keep humans at the center of AI when agentic systems are accelerating faster than most organizations can govern them? At AWS re:Invent, I sat down with Michael Bachman from Boomi for a wide-ranging conversation that cut through the hype and focused on the harder questions many leaders are quietly asking. Michael leads technical and market research at Boomi, spending his time looking five to ten years ahead and translating future signals into decisions companies need to make today. That long view shaped a thoughtful discussion on human-centric AI, trust versus autonomy, and why governance can no longer be treated as an afterthought. As businesses rush toward agentic AI, swarms of autonomous systems, and large-scale automation, Michael shared why this moment makes him both optimistic and cautious. He explained why security, legal, and governance teams must be involved early, not retrofitted later, and why observability and sovereignty will become non-negotiable as agents move from experimentation into production. With tens of thousands of agents already deployed through Boomi, the stakes are rising quickly, and organizations that ignore guardrails today may struggle to regain control tomorrow. We also explored one of the biggest paradoxes of the AI era. The more capable these systems become, the more important human judgment and critical thinking are. Michael unpacked what it means to stay in the loop or on the loop, how trust in agentic systems should scale gradually, and why replacing human workers outright is often a short-term mindset that creates long-term risk. Instead, he argued that the real opportunity lies in amplifying human capability, enabling smaller teams to achieve outcomes that were previously out of reach. Looking further ahead, the conversation turned to the limits of large language models, the likelihood of an AI research reset, and why future breakthroughs may come from hybrid approaches that combine probabilistic models, symbolic reasoning, and new hardware architectures. Michael also reflected on how AI is changing how we search, learn, and think, and why fact-checking, creativity, and cognitive discipline matter more than ever as AI assistants become embedded in daily life. This episode offers a grounded, future-facing perspective on where AI is heading, why integration platforms are becoming connective tissue for modern systems, and how leaders can approach the next few years with both ambition and responsibility.  Useful Links Learn More About Boomi Connect with Michael Bachman Algorithms to Live By: The Computer Science of Human Decisions Tech Talks Daily is sponsored by Denodo

What does responsible AI really look like when it moves beyond policy papers and starts shaping who gets to build, create, and lead in the next phase of the digital economy? In this conversation recorded during AWS re:Invent, I'm joined by Diya Wynn, Principal for Responsible AI and Global AI Public Policy at Amazon Web Services. With more than 25 years of experience spanning the internet, e-commerce, mobile, cloud, and artificial intelligence, Diya brings a grounded and deeply human perspective to a topic that is often reduced to technical debates or regulatory headlines. Our discussion centers on trust as the real foundation for AI adoption. Diya explains why responsible AI is not about slowing innovation, but about making sure innovation reaches more people in meaningful ways. We talk about how standards and legislation can shape better outcomes when they are informed by real-world capabilities, and why education and skills development will matter just as much as model performance in the years ahead. We also explore how generative AI is changing access for underrepresented founders and creators. Drawing on examples from AWS programs, including work with accelerators, community organizations, and educational partners, Diya shares how tools like Amazon Bedrock and Amazon Q are lowering technical barriers so ideas can move faster from concept to execution. The conversation touches on why access without trust falls short, and why transparency, fairness, and diverse perspectives have to be part of how AI systems are designed and deployed. There's an honest look at the tension many leaders feel right now. AI promises efficiency and scale, but it also raises valid concerns around bias, accountability, and long-term impact. Diya doesn't shy away from those concerns. Instead, she explains how responsible AI practices inside AWS aim to address them through testing, documentation, and people-centered design, while still giving organizations the confidence to move forward. This episode is as much about the future of work and opportunity as it is about technology. It asks who gets to participate, who gets to benefit, and how today's decisions will shape tomorrow's innovation economy. As generative AI becomes part of everyday business life, how do we make sure responsibility, access, and trust grow alongside it, and what role do we each play in shaping that future? Useful Links Connect With Diya Wynn AWS Responsible AI Tech Talks Daily is sponsored by Denodo

What does it really mean to support developers in a world where the tools are getting smarter, the expectations are higher, and the human side of technology is easier to forget? In this episode of Tech Talks Daily, I sit down with Frédéric Harper, Senior Developer Relations Manager at TinyMCE, for a thoughtful conversation about what it takes to serve developer communities with credibility, empathy, and long-term intent. With more than twenty years in the tech industry, Fred's career spans hands-on web development, open source advocacy, and senior DevRel roles at companies including Microsoft, Mozilla, Fitbit, and npm. That journey gives him a rare perspective on how developer needs have evolved, and where companies still get it wrong. We explore how starting out as a full-time developer shaped Fred's approach to advocacy, grounding his work in real-world frustration rather than abstract messaging. He reflects on earning trust during challenging periods, including advocating for open source during an era when some communities viewed large tech companies with deep skepticism. Along the way, Fred shares how studying Buddhist philosophy has influenced how he shows up for developers today, helping him keep ego in check and focus on service rather than status. The conversation also lifts the curtain on rich text editing, a capability most users take for granted but one that hides deep technical complexity. Fred explains why building a modern editing experience involves far more than formatting text, touching on collaboration, accessibility, security, and the growing expectations around AI-assisted workflows. It is a reminder that some of the most familiar parts of the web are also among the hardest to build well. We then turn to developer relations itself, a role that is often misunderstood or measured through the wrong lens. Fred shares why DevRel should never be treated as a short-term sales function, how trust and community take time, and why authenticity matters more than volume. From open source responsibility to personal branding for developers, including lessons from his book published with Apress, Fred offers grounded advice on visibility, communication, and staying human in an increasingly automated industry. As the episode closes, we reflect on burnout, boundaries, and inclusion, and why healthier communities lead to better products. For anyone building developer tools, managing technical communities, or trying to grow a career without losing themselves in the process, this conversation leaves a simple question hanging in the air: how do we build technology that supports people without forgetting the people behind the code? Useful Links Connect with Frédéric Harper Learn More About TinyMCE Tech Talks Daily is sponsored by Denodo

What does it really take to build a fintech company that quietly fixes one of the most frustrating problems SMEs face every day? In this episode of Tech Talks Daily, I'm joined by Pierre-Antoine Dusoulier, the Founder and CEO of iBanFirst, for a candid conversation about entrepreneurship, timing, and why cross-border payments have remained broken for so long.  Pierre-Antoine's story begins in London, where his early career as an FX trader felt like a compromise at the time, yet quietly gave him a front-row seat to inefficiencies most people accepted as normal. That experience would later shape two companies and a very clear point of view on how money should move across borders. Pierre-Antoine walks through his first venture, Combeast.com, one of France's earliest FX brokerages for retail investors, and what he learned from selling it to Saxo Bank and staying on to run Western European operations. That chapter matters, because it exposed the gap between how sophisticated FX markets really are and how poorly SMEs are served when FX and payments are bundled together inside traditional banks. Out of that frustration, IbanFirst was born in 2016 with a simple idea: treat cross-border payments as a specialist discipline, not a side feature. Today, IbanFirst serves more than 10,000 clients across Europe and processes over €2 billion in transactions every month. We dig into why growth has continued while many fintechs have slowed, from a product designed to be used daily, to proactive sales, to a new generation of CFOs and CEOs who expect the same clarity and speed at work that they get from consumer fintech tools.  Pierre-Antoine explains how real-time FX rates, payment tracking using SWIFT GPI, and multi-entity account management change the day-to-day reality for SMEs trading internationally. We also talk about Brexit, and how being rooted in continental Europe created an unexpected opening. Pierre-Antoine shares why expanding into the UK, including the acquisition of Cornhill, made sense, and why London's payments ecosystem still stands apart in scale and depth. Along the way, he is refreshingly open about the heavy investment required in compliance, trust, and regulation, and why nearly a third of IbanFirst's team focuses on operations and oversight. Looking ahead, Pierre-Antoine lays out a bold vision for the SME payments market, predicting a future where specialists replace banks in much the same way fintech reshaped consumer money transfers. As cross-border trade grows and currency volatility becomes a daily concern, his perspective raises an interesting question for anyone running an international business today:  if specialists already exist, why keep relying on systems that were never designed for how SMEs actually operate? Useful Links: Connect with Pierre-Antoine Dusoulier Learn more about iBanFirst, Tech Talks Daily is sponsored by Denodo

What happens when artificial intelligence moves faster than our ability to understand, verify, and trust it? In this episode of Tech Talks Daily, I sit down with Alexander Feick from eSentire, a cybersecurity veteran who has spent more than a decade working at the intersection of complex systems, risk, and emerging technology. Alex leads eSentire Labs, where his team explores how new technologies can be secured before they quietly become load-bearing parts of modern business infrastructure. Our conversation centers on a timely and uncomfortable reality. AI is being embedded into workflows, products, and decision-making systems at a pace most organizations are not prepared for. Alex explains why many AI failures are not caused by malicious models or dramatic breaches, but by broken ownership, invisible dependencies, and a lack of ongoing verification. These are not technical glitches. They are organizational blind spots that quietly compound risk over time. We also explore the ideas behind Alex's recently published book on trust and AI, which he made freely available due to the speed at which real-world AI failures were already overtaking theory. From prompt injection and model drift to the dangers of treating non-deterministic systems as if they were predictable software, Alex shares why generative AI requires a fundamentally different security mindset. He draws a clear distinction between chatbot AI and embedded AI, and explains the moment where trust quietly shifts away from humans and into systems that cannot take accountability. The discussion goes deeper into what trust actually means in an AI-driven organization. Alex argues that trust must be earned, measured, and monitored continuously, not assumed after a successful pilot. Verification becomes the real work, not generation, and leaders who fail to recognize that shift risk scaling errors faster than they can contain them. We also talk about why he turned his book into an AI advisor, what that experiment revealed about the limits of models, and why human responsibility cannot be automated away. This is a grounded, practical conversation for leaders, technologists, and anyone deploying AI inside real organizations. If AI is becoming part of how decisions get made where you work, how confident are you that someone truly owns the outcome? Useful Links Connect with Alexander Feick Learn more about eSentire Tech Talks Daily is sponsored by Denodo

How much value do your developers actually get to deliver in a typical week, and how much of their time is quietly lost to meetings, context hunting, and process drag? I'm joined by Phil Heijkoop, Global Practice Head of Developer Experience at Valiantys, for a conversation that cuts through the hype surrounding AI and asks a harder question about why so many engineering teams still struggle to see meaningful returns.  Phil argues that most organizations are only unlocking a small fraction of a developer's true contribution, not because of a lack of talent, but because process drag slowly squeezes out deep, focused work. AI, he explains, does not fix this by default. Without the right foundations in place, it simply accelerates the wrong work at scale. We explore the long shadow cast by the "move fast and break things" mindset and why that philosophy becomes risky inside regulated, enterprise environments where resilience and trust matter more than speed alone. Phil shares what he sees when organizations chase shiny new tooling while ignoring technical debt, unclear standards, and fragile workflows.  From protecting uninterrupted time for deep work to automating manual friction points and setting shared guardrails, he outlines how teams can realistically unlock three to five times more output before AI even enters the picture. Only then, he says, does AI act as a multiplier rather than a source of chaos. The conversation also digs into developer experience as a business lever, not a perk, and why leadership clarity, cultural trust, and consistent standards matter as much as tooling choices. We discuss the growing risks in the software supply chain, the sustainability of open source dependencies, and what recent high-profile retirements signal for enterprise teams that depend on them.  If AI is accelerating your organization in the wrong direction, what foundational changes would you need to make today to ensure it amplifies value instead of friction, and how honest are you willing to be about what is really slowing your teams down? Useful Links Connect with Phil on LinkedIn Learn more about Phil's work Valiantys Website Tech Talks Daily is sponsored by Denodo  

What happens when the future of money stops being about speculation and starts being about people, ownership, and agency? In this episode of Tech Talks Daily, I'm joined by Dr. Friederike Ernst, co-founder of Gnosis, to unpack a conversation that goes far beyond crypto price cycles or technical hype. This is a thoughtful discussion about where blockchain is heading and, just as importantly, where it could go wrong if we are not paying attention. Friederike has spent more than a decade building foundational infrastructure for the Ethereum ecosystem, from smart wallets to decentralized exchanges and blockchain networks that quietly power large parts of Web3. But as she explains, the industry is now standing at a fork in the road. One path leads to blockchain becoming a silent backend upgrade for banks and incumbents, improving efficiency while keeping power centralized. The other path is far more ambitious, using blockchain to return ownership, control, and financial agency to everyday people. We talk about why financial infrastructure, despite working reasonably well for many of us in Europe, remains deeply inefficient, expensive, and exclusionary at a global level.  A major theme of this episode is usability. Friederike is clear that technology only matters if it improves real lives. She explains why early blockchain products asked too much of users and how that is now changing, with experiences that feel as simple as using a neobank or debit card while preserving true ownership under the hood. The goal is not to make everyone a crypto expert, but to make financial tools that work seamlessly while remaining genuinely user-owned. We also explore the darker possibilities. Like any powerful technology, blockchain can be used to empower or to control. Friederike does not shy away from the risks of surveillance, social scoring, and misuse, and she argues that the real battle ahead is cultural, not technical. Values like privacy, free expression, and personal agency need to be defended openly, or the technology will be shaped without public consent. As we look toward 2026, this conversation offers a refreshing reminder that the future of money is still being written. The question is whether it will be owned by communities or quietly absorbed by the same institutions we already rely on. After listening to this episode, where do you think that future should land, and what choices are you willing to make to influence it? Useful Links Connect With Dr. Friederike Ernst Learn More about Gnosis Tech Talks Daily is sponsored by Denodo      

In this episode of Tech Talks Daily, I'm joined by Stuart Thompson, President of ABB's Electrification Service Division, to explore the intersection of industrial sustainability, energy security, and cutting-edge technology.   As industries face growing energy demands and climate targets, Stuart explains how companies can modernize their infrastructure to drive efficiency, reduce carbon footprints, and stay ahead of the energy curve.   Navigating the Industrial Sustainability Challenge   We start by addressing the urgent need for industries to rethink their energy and carbon strategies. Stuart highlights the significant role of construction and manufacturing in global energy-related emissions, stressing that many businesses are still behind on their 2030 sustainability targets.   We dive into the emerging shift from capital expenditure (CapEx) to operational expenditure (OpEx) models, such as predictive maintenance, to maximize value from existing assets.   Asset Modernization   Stuart explains how asset modernization—upgrading intelligent components like switchgear within existing infrastructure—can dramatically improve efficiency and reduce carbon without the need for costly, full-scale replacements.   He also shares examples, including Intel's semiconductor upgrades and Jadal Steel's success in Oman, demonstrating how targeted upgrades can meet sustainability goals while boosting productivity.   Smarter Energy Management with AI and AR   We explore how AI and augmented reality (AR) are transforming service delivery and operational intelligence. Stuart discusses how AI-powered predictive maintenance helps companies anticipate failures and optimize energy management, while AR facilitates remote assistance for faster issue resolution.   He also touches on how these technologies contribute to energy savings and carbon reduction by automating service reports and enabling real-time visibility into asset performance.   BESS as a Service: Solving the Energy Security Trilemma One of the key innovations Stuart highlights is ABB's Battery Energy Storage as a Service (BESSaaS), a solution designed to solve the "energy trilemma" of security, cost, and sustainability.   With on-site battery storage and AI-driven energy trading, businesses can bypass slow grid connections, ensure energy security, and even turn their energy storage into a profit center. This model is already making waves in industries ranging from data centers to manufacturing.   A Glimpse into the Future: ABB's Investment in Asset Management Tech   As we look to the future, Stuart reveals ABB's upcoming investment in asset management technology, set to be announced globally in early December 2025. This exciting move will have a significant impact on major customers like the London Underground and Saudi Electric Commission, further cementing ABB's role as a leader in energy innovation.   Don't miss this episode, where we discuss the latest trends in industrial sustainability, energy security, and technology's pivotal role in shaping a greener, more efficient future.   Useful Links Connect with Stuart on Linkedin Learn more about ABB Tech Talks Daily is sponsored by Denodo

Are we finally treating water risk like a board-level issue, rather than a line item that only shows up when something breaks?   In this episode, I'm joined by Emilio Tenuta, SVP and Chief Sustainability Officer at Ecolab, to unpack why water has become a strategic variable for business, right alongside energy and carbon. Ecolab works with customers across more than 40 industries in more than 170 countries, so Emilio has a front row seat to how quickly the conversation is changing.   Why water risk feels different in 2025 One of the most useful parts of this conversation is how Emilio frames water as "hyperlocal." A company can publish a global target, but the real pressure shows up basin by basin, site by site, community by community.   We also discuss the misconception that water is primarily an operational concern. The knock-on effects show up in uptime, expansion plans, permitting, reputation, and the social license to operate.   Emilio points to disclosure data that puts real money behind the issue. CDP has estimated water-related supply chain risks at $77 billion across responding companies, which helps explain why boards are paying closer attention.   Where AI meets water and energy   AI is a catalyst in two directions at once. It can help organizations measure, predict, and reduce waste, but it also drives demand for more data centers, more power, and more cooling.   We examine the tension many people are whispering about: building digital capacity in places already facing water stress. Emilio's view is pragmatic: the answer is responsible innovation, coupled with transparency on how water is used and how impacts are managed.   That takes us into Ecolab's push toward digital visibility and real-time control, because you cannot improve what you cannot see.   From "site to chip" cooling and smarter stewardship   Emilio shares that Ecolab's 3D TRASAR Technology for direct-to-chip liquid cooling is designed to protect high-performance servers by monitoring coolant health indicators in real time and translating that data into actionable steps for operators.   We also discuss what happens when AI is applied to the water side of the data center equation. Ecolab and Digital Realty have described a pilot across 35 US data centers to reduce water use by up to 15% and avoid up to 126 million gallons of potable water withdrawn annually.   To round things out, we discuss circularity as a business strategy, the role of collaboration through efforts like the Water Resilience Coalition, and why Ecolab's Watermark Study is worth reading if you want a pulse check on water stewardship and public sentiment.   So after listening, where do you land on the big question: is AI going to become a stress test for local water systems, or a tool that finally helps us run them better, and why? Useful Links:  Connect with Emilio Tenuta Learn more Ecolab Follow Ecolab on Linkedin Tech Talks Daily is sponsored by Denodo

How do you move faster with AI and cloud innovation without losing control of security along the way?   Recorded live from the show floor at AWS re:Invent in Las Vegas, this episode of Tech Talks Daily features a timely conversation with Kimberly Dickson, Worldwide Go-To-Market Lead for AWS Detection and Response Services. As organizations race to adopt agentic AI, modernize applications, and manage sprawling cloud environments, Kimberly offers a grounded look at why security must still sit at the center of every decision.   Kimberly explains how her role bridges two worlds at AWS. On one side are customers dealing with prioritization fatigue, fragmented security signals, and growing pressure to do more with fewer resources. On the other hand, there are the internal service teams building products like Amazon GuardDuty, Amazon Inspector, and AWS Security Hub. Her job is to connect those realities, shaping services based on what customers actually struggle with day to day. That perspective sets the tone for a conversation focused less on hype and more on practical outcomes.   We unpack how AWS thinks about security culture at scale, from infrastructure and encryption through to threat intelligence gathered across Amazon's global footprint. Kimberly shares how AWS uses large-scale honeypots to observe attacker behavior in real time, feeding that intelligence back into detection services while also working with governments and industry partners to take down active threats. It is a reminder that cloud security is no longer just about protecting individual workloads, but about contributing to a safer internet overall.   The conversation also dives into new announcements from re:Invent, including the launch of AWS Security Hub, extended threat detection for EC2 and EKS, and the emergence of security-focused AI agents. Kimberly explains how these tools shift security teams away from manual investigation and toward faster, higher-confidence decisions by correlating risks across vulnerabilities, identity, network exposure, and sensitive data. The goal is clear visibility, clearer priorities, and remediation that fits naturally into existing workflows.   We also explore how AWS approaches security in multi-cloud and hybrid environments, why foundational design principles still matter in an AI-driven world, and how open standards are helping normalize security data across vendors. Kimberly's reflections on re:Invent itself bring a human close to the episode, highlighting the pride and responsibility felt by teams building systems that millions of organizations depend on.   As AI adoption accelerates and security teams are asked to keep pace without slowing innovation, what would it take for your organization to move faster while still trusting the foundations you are building on?

In this episode of Tech Talks Daily, I sit down with Yuyu Zhang to unpack a shift that many developers can feel but struggle to articulate. Yuyu's journey spans academic research at Georgia Tech, building recommendation systems that power TikTok and Douyin at global scale, and leading the Seed-Coder project at ByteDance, which reached state-of-the-art performance among open source code models earlier this year. Today, he is part of Codeck, where the focus has moved beyond AI assistance toward autonomous coding agents that can plan, execute, and verify real engineering work. Our conversation begins with a simple but revealing observation. Most AI coding tools still behave like smarter autocomplete. They help you type faster, but they do not own the work. Yuyu explains why that distinction matters, especially for teams dealing with complex systems, tight deadlines, and constant interruptions. Autonomy, in his view, is not about replacing engineers. It is about giving them back their flow. We explore Verdent, Codeck's autonomous coding agent, and Verdent Deck, the desktop environment designed to coordinate multiple agents in parallel. Instead of one AI reacting line by line inside an editor, these agents operate at the task level. They plan work with the developer upfront, execute independently in safe environments, and validate their output before handing anything back. The result feels less like using a tool and more like managing a small engineering team. Yuyu shares how parallel agents change both speed and predictability. One agent can implement a feature, another can write tests, and another can investigate logs, all without stepping on each other. Just as important, he walks through the safeguards that keep humans in control. Explicit planning, permission boundaries, sandboxed execution, and clear, reviewable diffs are all designed to address the very real concerns engineering leaders have about letting autonomous systems near production code. The discussion also turns personal. Having worked on some of the highest-scale systems in the world, Yuyu reflects on why developers lose momentum. It is rarely about raw ability. It is about constant context switching. His goal with Verdent is to preserve mental focus by offloading interruptions and letting engineers return to work with clarity rather than cognitive fatigue. We close by looking ahead. The definition of a "good developer" is changing, just as it has many times before. AI is not ending programming. It is reshaping it, pushing human creativity, judgment, and design thinking to the foreground while machines handle the repetitive churn. If autonomous coding agents are becoming colleagues rather than helpers, how comfortable are you with that future, and what would you want to stay firmly in human hands?

How do you capture every moment of a golf tournament spread across hundreds of acres, tens of thousands of shots, and dozens of players competing at the same time? That question sits at the heart of this conversation recorded at AWS re:Invent, where I sat down with Eric Hansen, VP of Product at the PGA Tour, and Elaine Chiasson, who leads the global golf team at AWS, to unpack how data and AI are reshaping the way fans experience the game. Eric explains why modern professional golf has more in common with Formula 1 than most people realize. Every ball struck, every position on the leaderboard, and every shift in momentum generates data that needs to be processed instantly. With more than thirty thousand shots across a single tournament and only a fraction of them shown on traditional broadcasts, the PGA Tour faces a constant challenge. How do you give fans context, insight, and a sense of presence when most of the action is never seen on screen? Elaine shares how AWS has helped the Tour build the foundation to answer that question. From migrating decades of video and shot data into the cloud to applying generative AI for automated commentary, language translation, and real time insights, this partnership goes far beyond infrastructure. Together, they are experimenting with automated camera switching, AI driven production workflows, and personalized fan experiences that surface the right information at the right moment, whether you are following the leaderboard or a single favorite player. The conversation also digs into trust and accuracy. Eric walks through how the PGA Tour validates AI generated commentary to ensure it stays aligned with the sport's standards, while Elaine highlights why operational discipline and governance matter just as much as innovation. They explore what hyper personalization looks like inside the PGA Tour app, how global broadcasts could evolve, and why the long term opportunity lies in making every shot matter for every fan. As live sports move toward a future shaped by data, automation, and AI agents working behind the scenes, this episode offers a clear look at what that transformation really involves. So as golf continues to blend tradition with technology, what kind of fan experience do you want to see next, and how comfortable are you with AI calling the shots? Useful Links Connect with Eric Hansen, VP of Product at the PGA Tour. Connect with Elaine Chiasson Learn more about AWS and PGA Tour Tech Talks Daily is sponsored by Denodo

How do you make sense of an industry that is changing at a pace few predicted, especially with SIGNAL London still fresh in our minds and Twilio unveiling the next stage of its vision for customer engagement? That question sits at the heart of today's conversation with Peter Bell, VP of Marketing for EMEA at Twilio, who joined me to unpack what the past year has taught both companies and consumers about AI's role in shaping modern experiences. Peter begins by grounding everything in a single, striking shift. Only a year ago, AI-powered search barely registered in global traffic. Today it accounts for around a fifth of all searches. That leap signals a broader behavioral shift as consumers move instinctively toward conversational interfaces, which, in turn, leaves brands with a clear message. The clock has moved on. AI is no longer a nice-to-have. It is a direct response to how people now choose to discover, question, and buy. Our conversation turns to the gap between customer expectations and the experiences they receive. Peter discusses why brands often struggle to integrate channels, data, and AI coherently. He explains how first party data has become the anchor for any serious AI strategy, why generic public models cannot solve brand-specific tasks, and why the most successful teams start with simple, tightly scoped problems. A password reset may not sound glamorous, yet it is the kind of focused use case that teaches teams how to govern data, automate safely, and build confidence in the process. We also spend time on branded calling, RCS, and the evolution of voice. Peter breaks down what modern messaging now looks like and why trust sits at the center of every interaction. His explanation of Conversational Relay shows why natural voice exchanges finally feel within reach after years of frustration with rigid IVR systems. The thread running through all of this is clear. Consumers want speed and clarity, but they want reassurance too, and brands need to honor both sides of that equation. Later in the conversation, Peter makes one of the episode's most compelling points. Brand visibility has become harder, not easier, because much of the early research now occurs within AI tools. Buyers form opinions long before they speak with a sales rep. That shift explains why so many B2B companies are returning to high-impact brand channels, whether that is F1 sponsorships or other standout moments that keep them in the initial consideration set. We close with the topic that Peter believes will define the next stage of enterprise AI. Model Context Protocol. MCP has emerged as a quiet breakthrough, enabling LLMs to access data across CRM systems, files, and other software through a standard protocol. This removes one of the biggest blockers in AI projects: the practical challenge of connecting disparate data to a model built for a specific purpose. As Peter puts it, MCP gives companies a realistic way to make the special-purpose models that deliver reliable ROI. It is a wide-ranging conversation shaped by SIGNAL London's announcements, the evolving customer journey, and a year in which AI moved from curiosity to expectation. I would love to know what part stood out most to you. Are you seeing the same shifts Peter describes in your own business, and how are you preparing for the year ahead? Useful Links Interact with the Inside the Conversational AI Revolution report. Learn more about the Signal event Connect with Peter Bell, VP of Marketing for EMEA at Twilio. Tech Talks Daily is sponsored by Denodo

Why do smart people still click when every instinct tells them they should pause first? That question sits at the heart of this conversation with Denny LeCompte, CEO of Portnox and a rare cybersecurity leader who brings a background in cognitive psychology to identity, trust, and human error.   It is a discussion that pulls back the curtain on the habits, shortcuts, and blind spots that shape our decisions long before a breach becomes a headline.   Denny explains why people rely on benevolence cues, confirmation biases, and loss aversion, and then shows how attackers weaponize each. He explains why training alone cannot fix human fallibility and why a different design mindset is needed if we want security people can actually live with.   Through clear examples and thought-provoking analogies, he describes how teams can build environments that remove opportunities for mistakes rather than punishing people for being human.   We also explore what Zero Trust really means beyond marketing-speak. Denny cuts through the noise and frames it as a mindset shift rather than a product category. He draws on real conversations with CISOs to explain why passwordless adoption moves slowly and why the next wave of identity risk will come from AI agents operating within networks. It is a future in which the line between human and machine identity blurs, requiring access control to evolve just as quickly.   Later, Denny shares a personal story about a mentor who influenced his views, then explains Portnox's unified access control approach as organizations retire VPNs and passwords. His main point: security only works when systems reflect human nature, removing friction and helping people make safe choices. Every policy and workflow is a decision that impacts security outcomes.   What part of Denny's perspective made you reconsider your habits?   Useful Links Connect with Denny LeCompte, CEO of Portnox Learn more about Portnox Tech Talks Daily is sponsored by Denodo    

Have you ever wondered what it takes to run technology for one of the largest commercial real estate companies in the world? That question shapes my conversation with Yao Morin, Global CTO at JLL, as we look at how AI is changing the places where we work, shop, and gather. Real estate may seem traditional from the outside, yet inside JLL the pace is intense. With more than 5 billion square feet under management and huge volumes of daily activity, the pressure on property teams is real and the limits of manual work are easy to see. Yao explains how this reality led to the creation of Property Assistant, JLL's new AI solution built on JLL Falcon. Falcon acts as the company's enterprise AI foundation, giving teams a secure and scalable way to use data across global operations. She describes how the platform hides complexity so developers and property teams can work with AI without thinking about which model sits behind it. We talk through everyday examples, like overcrowded meeting rooms and confusing layouts, that the assistant can flag and address through recommendations drawn from live sensor data. The assistant goes far beyond space planning. It helps teams understand rising tenant concerns, patterns in work orders, and hidden risks before they grow into larger operational issues. Yao sees AI as a partner that handles heavy data processing so people can focus on the messy, human context. That balance is central to how JLL builds its tools, and she explains why this approach gives property teams more confidence and clarity in fast-changing environments. We also explore how AI is influencing the future design of buildings. As hybrid work, flexible retail, and rising industrial needs continue to shift demand, AI can gather layouts, analyze usage, and offer guidance at a speed traditional methods cannot match.  This creates a continuous feedback loop that helps teams adjust space before frustrations grow. For Yao, it is a way to bring real-time understanding into a sector that once relied on long cycles and guesswork. Security surfaces often in our conversation. Yao details how Falcon enforces monitoring, privacy controls, and consistency across the company, which is vital when working with sensitive client data across many regions. A centralized platform allows JLL to invest deeply in safeguards rather than spreading risk across scattered tools. She highlights how trust sits at the center of the brand and why it shapes every AI decision they make. As we shift toward the future, Yao shares how JLL is expanding its pipeline to more than fifty AI assistants aimed at productivity, client insight, and sustainability. She gives examples of tools that adjust energy usage and support portfolio planning, offering a view into how AI will support both performance and environmental goals. It is clear that AI has moved from experimentation to daily use inside JLL, with real business impact already taking shape. The episode closes with a powerful reflection on leadership and representation. Yao talks openly about her own journey, the weight of visibility, and how she learned to turn moments of feeling out of place into motivation. She explains why active sponsorship matters, why belonging is a measurable business priority, and how diverse viewpoints reduce blind spots in product design. Her message is heartfelt, practical, and filled with hope for the next generation of leaders. As you listen, I would love to know which part of Yao's story stays with you. Do you see AI changing your own workplace or the spaces you pass through every day? And how do you think better representation shapes the products we build? Share your thoughts and join the conversation. Useful Links Connect With Yao Morin Learn more about JLL Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com

Did you ever stop and wonder how many hours you lose each week hunting for files, tabs, links, or half-written ideas scattered across your apps? It is a familiar frustration, and it sits at the center of today's fast-tracked conversation with Dropbox VP of Engineering, Josh Clemm. Josh has spent two decades building products shaped around scale, personalisation, and clarity, and he brings that mix of experience to Dropbox's push into AI and knowledge management. In this episode, Josh shares stories from his time at LinkedIn and Uber, including the surprising Krispy Kreme promotion that took down Uber Eats across the globe and triggered a major rethink of architecture and resiliency. That experience shaped his belief that chaos often teaches the most. It also sets the stage for why he sees AI fluency as a leadership requirement rather than a trend.  You will hear how Dropbox is approaching internal experimentation, why context rot and work slop are real problems inside companies, and why the empty chat box often creates more anxiety than opportunity. Josh walks through the thinking behind Dropbox Dash, a standalone AI powered knowledge layer that connects all of your cloud apps, understands their content, and turns search into something sharper and faster. He explains why context aware AI is the next leap, how Dash builds knowledge graphs across apps, and why the future of AI might look less like single player workflows and more like tools that sit inside the flow of teamwork. It is a wide ranging conversation that moves from engineering history to the practical steps behind building AI products that feel useful rather than overwhelming. So here is the question that sits underneath everything Josh shared. What would your day look like if your information finally made sense without you having to chase it? Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com

What does learning look like when technology shifts faster than most university systems can adapt? That question shaped my conversation with Rob Telfer, who leads education strategy for D2L across Europe, the Middle East, and Africa. Rob returned to the show with a clear view of how AI is transforming higher education and why so many institutions are struggling to keep pace with expectations from students, employers, and society. Rob opened by laying out the reality universities face today. Financial strain, fluctuating enrolment, employer demands changing at speed, and a generation of learners preparing for roles that may not even exist yet. Against that backdrop, he described AI as the biggest catalyst the sector has seen in decades and explained how it has already reshaped academic policy, assessment models, and daily teaching practice. We explored practical examples of where AI is already creating meaningful change. Rob shared how D2L is helping institutions introduce adaptive learning, on demand student support, and content creation tools that reduce the pressure on educators. These are not speculative ideas. They are used by universities serving tens of thousands of learners, improving accessibility, easing workloads, and giving students faster, more personal support. The conversation moved to employability, a worry at the centre of almost every higher education debate. Rob explained how curriculum design needs to shift from theory first to skill first, and how deeper collaboration between academia and industry can help close widening gaps. He described why AI should be woven through the learning experience rather than bolted on at the end, and how that alignment can shape graduates who are confident with the tools they will soon use in the workplace. A striking theme came from the mismatch between student behaviour and institutional policy. Many students use AI daily, even where guidance is unclear or restrictive. Rob argued that ignoring the reality only pushes students into the shadows. Universities that teach responsible use, clear evaluation methods, and prompt literacy will better prepare their learners for the world they are about to enter. We ended by looking ahead to 2026. Rob believes the institutions that thrive will be the ones that act with intent, create clear AI policies, invest in meaningful technology, and keep human connection at the centre of learning. Those that resist or delay may find themselves struggling to compete in a sector where expectations rise quickly and alternatives for learners continue to grow. If you work in education or care about the future of learning, Rob's insights offer a candid, practical view of what must change. Which of his observations resonates most with your own experience, and how should universities evolve from here? I would love to hear your thoughts. Useful Links Connect with Rob Telfer on LinkedIn Learn more about D2L Follow on LinkedIn, Twitter, and Facebook Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com

How do you guide a workforce through the fastest shift in technology most of us have seen in our careers? That question shaped my conversation with David Martin from BCG, who works at the intersection of talent, culture, and AI. He joined me from New York, with Amelia listening in, and quickly painted a clear picture of what is really happening inside global enterprises right now. We started with the widening split between AI fluent teams and those stuck in endless pilots. David explained why the organizations getting results are the ones doing fewer things with far greater ambition. Many others scatter energy across small use cases, save minutes instead of hours, and never reach a scale where value becomes visible. Training surfaced early as one of the biggest gaps. Not surface level workshops, but the deeper hands-on learning that helps people change how they work. David described why frontline teams lag behind, why engineers still miss major capabilities, and how leadership behaviour dramatically affects adoption. Curiosity and communication play a bigger role than most expect. We explored the move from isolated AI experiments to real workflow transformation. David shared examples from engineering, customer service, and operations where companies are finally seeing measurable results. He also explained why agents remain underused, with hesitation, data quality, and unfamiliarity still slowing progress. Shadow AI added another layer, with half of workers already using tools outside corporate systems. The conversation returned often to people. David outlined BCG's 10-20-70 rule, showing why technology is never the main bottleneck. Culture, roles, and process make or break outcomes. Leaders who provide clarity and a sense of direction see faster adoption. Those who remain hesitant create uncertainty that spreads across teams almost instantly. As we looked toward 2026, David shared cautious optimism. He sees huge potential in areas like healthcare and sustainability, along with a wave of workflow redesign that will reshape daily work. His own learning habits are simple, from podcasts to regular reading, and driven by a desire to set a strong example for his children as they grow into a world shaped by AI. If you want a grounded view of where AI is genuinely delivering change, this conversation offers rare clarity. What resonates with you most from David's perspective, and how will you approach your own learning in the year ahead? I would love to hear your thoughts.   Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com

Did you know that when many people hear "Orange," they still ask if it involves SIM cards? That was the perfect place to begin my conversation with Sahem Azzam, President for IMEA and Inner Asia at Orange Business. Once we cleared that up, it opened the door to a much richer story about what enterprise innovation looks like across one of the fastest-moving regions on the planet. Sahem joined me from Dubai, a city that has become a living case study for what happens when a region refuses to think small. As we compared notes from Gitex Global, it became clear that what is happening across the Middle East is not a short burst of enthusiasm. It is a deliberate long-term shift driven by young populations, bold government ambition, and a willingness to adopt new technologies before anyone else. Sahem explained how this appetite for speed is shaping the region's digital transformation and how Orange Business is supporting it through cloud, connectivity, cybersecurity, digital integration, and large-scale smart city programmes. He shared practical stories that peeled back the curtain on cognitive city design, energy optimisation, and the pressure on enterprises to simplify sprawling hybrid IT environments. What stood out was how often the conversation returned to value. Better user experiences, lower costs, and new revenue paths. Everything Orange Business builds must deliver one of those outcomes. Sahem talked through platformization, why unified infrastructure matters, and how enterprises can reduce complexity in an age where cloud, security, networking, and AI all collide at once. We also discussed the growing focus on responsible AI and the shared need for transparency. Sahem spoke about data ownership, trusted models, and the careful guardrails that must sit behind every AI deployment. The rise in cyber threats is making this more important than ever, and he offered a candid look at how Orange Cyberdefense approaches modern security through an integrated view of infrastructure, operations, and risk. What gave this conversation a personal edge was Sahem's final reflection on learning. After years at Stanford, London Business School, and Harvard, he still sees human experience as the most valuable teacher. Listening to people, sharing problems, comparing perspectives. Events like Gitex remind him that optimism is contagious and that the future of the region will be shaped by collaboration as much as technology. If you want a grounded view of digital transformation from someone living it every day, this conversation is a rare window into both the opportunities and the tension behind innovation at scale. Have you seen the same momentum in your own region, and how do you stay ahead of the pace of change? I would love to hear your thoughts.   Tech Talks Daily is Sponsored By Denodo. To learn more, visit denodo.com/aws

Did you ever walk into a conference session thinking you were ready for the week, only to realise the announcements were coming so fast that you almost needed an agent of your own to keep up? That was the mood across Las Vegas, and it was the backdrop for my conversation with Madhu Parthasarathy, the general manager for Agent Core at AWS. He has spent the week at the centre of AWS's wave of agentic AI news, working on the ideas that are already moving from keynotes and demos into the hands of real enterprise teams. Sitting down with him offered a rare moment of clarity among the noise, and his calm take on what actually matters helped bring the bigger picture into focus. Madhu talked through the thinking behind Agent Core and why he believes 2026 will be the year enterprises finally begin shifting from prototypes to production scale agents. He walked me through the two areas customers keep coming back to, trust and performance, and why the new policy framework and agent evaluations could remove long standing barriers to deployment.  His examples were grounded in real behaviour he is seeing inside large companies, whether that is internal support workloads, developer productivity, meeting preparation, or customer facing flows designed to reduce the friction between intent and outcome. We also explored the deeper shift introduced by Nova Forge, including the idea of blending enterprise data with model checkpoints to create domain specific agents that can work with greater accuracy and context. Madhu explained why there will never be a one size fits all model and how choice remains central to AWS's approach to agentic AI. My guest also reflected on how infrastructure changes, such as Trainium three ultra servers and expanded Nova model families, are shaping the pace at which companies can experiment, evaluate, and adopt emerging capabilities. Trust surfaced again and again in our conversation. Madhu was clear that non-deterministic systems also introduce concerns, which is why action boundaries and guardrails are becoming as important as model quality. He described the excitement he is seeing from customers who now feel they have workable ways to give agents responsibility without handing over the keys entirely.  As he put it, this is the moment where confidence begins to grow because the guardrails finally meet the expectations of enterprise leaders. We closed with the topic many people have been whispering about all week, modernization. Madhu reflected on AWS Transform, the push to help organisations move away from legacy architectures far faster than before, and the impact that agentic systems will have as they support full stack migrations across Windows environments and custom languages.  Madhu cuts through the noise with a grounded view of reliable autonomy, multi agent orchestration, policy driven safety, and the shift toward agents as true collaborators. The question now is where you see the biggest opportunity. How might these agent-based systems change your workflows, and what would it take for you to trust them with the tasks you never seem to have time for? I would love to hear your thoughts.

Have you ever wondered how an idea that begins with two friends in a pub ends up shaping conversations about health all over the world? That was on my mind as I met  Graham Link & Timothy Gnaneswaran from Movember on the show floor at AWS re:Invent. Their story has grown far beyond the mustache that everyone recognises. What started with a simple gesture of support has become a movement that now reaches millions, raises vast sums through a global fundraising platform, and backs projects focused on prostate cancer, testicular cancer, mental health, and suicide prevention. Hearing them describe how that original spark grew into something this wide and long lasting gave the conversation a real sense of depth. Recording in the middle of re:Invent added its own flavour. AI news filled the halls, yet Timothy and Graham were there speaking with engineers and builders about something deeply human. Their booth stopped people in their tracks, offered barbershop shaves, and created space for personal stories. They talked openly about how Movember built its own platform to handle sixty to eighty million dollars in four weeks, how it must stay resilient every minute, and how AWS has supported them for more than a decade. They also shared how technology shapes the work behind the scenes, whether it is clinical quality registries, digital conversations tools, or new research paths that explore how AI might support healthier behaviours. What stayed with me most was the honesty about the tensions they face. Men are still reluctant to talk about their health. Loneliness is rising. Social platforms create new openings and new barriers at the same time. They see how AI can help someone begin a difficult conversation, yet they are clear about the risks when people rely on tools that were never designed for mental health support. They also talked about the patterns they see across different regions, the sobering statistics in the major markets where they operate, and how younger audiences now gather in gaming communities rather than traditional spaces. Movember knows it needs technology to reach scale, but it never wants to lose the human connection at the heart of its mission. What part of their story stands out most for you, and where do you think technology can genuinely help shape the next chapter of men's health?

Did you know a single Formula 1 car produces 1.1 million data points every second from hundreds of sensors? That number alone sets the tone for this conversation with Ruth Buscombe, an F1 strategist, analyst, and F1TV presenter whose work sits at the meeting point of engineering precision and real time storytelling. We met at AWS re:Invent in Las Vegas, and her insights into how much pressure, judgment, and creativity are wrapped inside each decision brought the sport to life in a fresh way for anyone who has ever stared at a dashboard of metrics and wondered what really matters. This discussion goes far deeper than split times and tyre choices. Ruth explains how AWS and F1 are rethinking race strategy through real time insights and cloud compute, from TrackPulse and root-cause analysis all the way to predictive graphics that let commentary teams spot a race-defining moment before it happens. She also reflects on the sport's changing culture, the growth of new fan communities, and the shift from old telemetry to modern systems that process millions of data points every second. Her stories from the paddock at Ferrari, Alfa Romeo, and F1TV help frame just how intense the job can be when 12,000ths of a second separate pole from second place. There are moments in this conversation that remind us that F1 strategy is as much about human pattern recognition as it is about machine intelligence, and that the strongest engineers find ways to absorb pressure without losing their instinct. What stood out most was how clearly Ruth links F1 to decision making in every industry. Whether she is talking about marginal gains, pattern detection, or the discipline needed to separate noise from signal, her examples make perfect sense to both race fans and tech leaders. She shares how AWS tools allow broadcasters and engineers to interpret scenarios instantly, why the sport needed to move past manual diagnosis, and how new tools even help verify whether a driver's mistake came from a small steering slide or a split-second shift error. Her passion is infectious and her explanations cut straight to the heart of what makes the blend of live racing and cloud computing work so well. As you listen, think about how your own team makes choices under pressure and ask yourself one last question. If you were in the garage making a call with the whole world watching, which signals would you trust and how fast could you act? Useful Links: Connect with Ruth  Sign up to Ruth's Newsletter AWS Insights  

Have you ever wondered how a company with nearly a million associates across continents keeps everyone learning, aligned, and prepared for constant change? That question sat at the heart of my conversation with Victor Arguelles, the VP of Global Learning Design and Development at Marriott International. Victor began his career as a high-school educator, and it is clear that this early experience shapes his entire approach to enterprise learning. He brings the empathy and discipline of the classroom into a global operation where cultural nuance, business complexity, and operational scale collide every day. Across our conversation, Victor opens up about what digital transformation in learning actually looks like behind the curtain at Marriott. Rather than focusing on tools alone, he explains how mindset, process, and cultural confidence dictate success. He talks about the delicate balance between global standardization and local relevance, and how Marriott validates learning experiences to understand how change will feel for associates before any deployment begins. It becomes clear that the company's commitment to people first is not a slogan, it is the foundation of the entire learning strategy. Victor also shares how Marriott is using partners and platforms to reimagine training in a way that fits into the flow of work. He describes how digital adoption tools have reduced training seat time by as much as 60 percent and given associates real support inside the tools they use every day. This shift has created confidence, improved performance, and given teams more time with guests, which he considers the most meaningful return on investment of all. Looking ahead, Victor reflects on the role AI will play in learning, from measurement to content creation, and how emerging tools could eventually provide adaptive, contextual support in real time. If you are a tech or business leader trying to understand how large enterprises truly modernize learning, this conversation offers a grounded and human view of what it takes. And as Victor looks toward 2026 and beyond, he shares why he believes the next wave of learning innovation will be shaped by AI, data, and a deeper understanding of behavior inside the flow of work. What stood out to you in his approach, and how do you see the future of enterprise learning evolving? I would love to hear your thoughts.

Have you ever wondered how an industry known for delays and uncertainty suddenly starts operating with the pace of a tech company? That thought stayed with me as I spoke with Eppie Vojt, the Chief Digital and AI Officer at West Shore Home. His team is bringing applied AI into home remodeling in a way that feels practical, grounded, and surprisingly human. Eppie explains how a strong data foundation allowed them to introduce agentic systems without the usual chaos. Those systems now handle scheduling, permitting, forecasting, and communication in the background. The result is a level of certainty that customers rarely experience in remodeling. When someone signs a project, they already know the installation date. Hours of operational work happen silently, and that alone changes the entire experience. We also talk about the culture that made this possible. Instead of forcing new tools onto teams, leadership encouraged small experiments and curiosity. That simple move flipped the mood internally. Departments began approaching Eppie with ideas rather than waiting to be pushed. The rollout was gradual, giving people time to shift into more valuable work without fear or disruption. Looking ahead, Eppie sees huge potential in letting customers start their journey in different ways. Tools like photogrammetry and digital twins could help people get early pricing guidance without a full in-home visit. It reflects a bigger change across physical industries as AI becomes something that quietly supports accuracy, safety, and convenience. If you care about real AI adoption rather than hype, this one offers a clear view into what works. I'd love to hear what stood out to you after listening. Useful Links Connect with Eppie Vojt on LinkedIn Learn more about West Shore in this video Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

What does it really mean to run a company that aims to be "good" before it ever thinks about becoming "great"? That was the question sitting with me as I sat down with Appfire's CEO, Matt Dircks. The conversation took us straight into the heart of modern leadership, purpose, and the realities of running a global SaaS business during a period of change. Matt has led organisations through rapid growth, mergers, cultural resets, and shifting market expectations. What stood out in our discussion was how open he is about the parts of leadership that are messy. He talked about transparency, dealing with hard decisions, and the challenge of building a culture where people feel safe enough to be honest without losing accountability. His philosophy is grounded in something simple. You cannot scale trust unless you behave in ways that earn it every day. We explored how Appfire is evolving beyond its acquisition roots, expanding from Atlassian aligned tools into cross platform solutions that support enterprises across Microsoft, Salesforce, GitHub and more. Matt explained why the company is investing heavily in new AI native products and why being close to customers is becoming a priority as their needs become more complex. He also shared how openness, active communication, and a willingness to be challenged guide the way he leads through uncertainty. The more we talked, the clearer it became that Appfire's next chapter is a blend of product innovation, cultural maturity, and a renewed focus on service. Matt's story offers a useful lens for anyone wrestling with questions about values, growth, and the human side of technology. What does a "good company" look like in practice, and how does that shape the road to long term success? I'd love to hear what resonated with you, so let me know your thoughts. Useful Links Connect With Matt Dircks on LinkedIn Learn more about Appfire The No Asshole Rule: Building a Civilized Workplace and Surviving One That Isn't by Robert I. Sutton  Range: Why Generalists Triumph in a Specialized World by David Epstein Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.  

What happens when AI adoption surges inside companies faster than anyone can track, and the data that fuels those systems quietly slips out of sight? That question sat at the front of my mind as I spoke with Cyberhaven CEO Nishant Doshi, fresh from publishing one of the most detailed looks at real-world AI usage I have seen. This wasn't a report built on opinions or surveys. It was built on billions of actual data flows across live enterprise environments, which made our conversation feel urgent from the very first moment. Nishant explained how AI has moved out of the experimental phase and into everyday workflows at a speed few anticipated. Employees across every department are turning to AI tools not as a novelty but as a core part of how they work. That shift has delivered huge productivity gains, yet it has also created a new breed of hidden risk. Sensitive material isn't just being uploaded through deliberate actions. It is being blended, remixed, and moved in ways that older security models cannot understand. Hearing him describe how this happens in fragments rather than files made me rethink how data exposure works in 2025. We also dug into one of the most surprising findings in Cyberhaven's research. The biggest AI power users inside companies are not executives or early career talent. It is mid-level employees. They know where the friction is, and they are under pressure to deliver quickly, so they experiment freely. That experimentation is driving progress, but it is also widening the gap between how AI is used and how data is meant to be protected. Nishant shared how that trend is now pushing sensitive code, R&D material, health information, and customer data into tools that often lack proper controls. Another moment that stood out was his explanation of how developers are reshaping their work with AI coding assistants. The growth in platforms like Cursor is extraordinary, yet the risks are just as large. Code that forms the heart of an organisation's competitive strength is frequently pasted into external systems without full awareness of where it might end up. It creates a situation where innovation and exposure rise together, and older security frameworks simply cannot keep pace. Throughout the conversation, Nishant returned to the importance of visibility. Companies cannot set fair rules or safe boundaries if they cannot see what is happening at the point where data leaves the user's screen. Traditional controls were built for a world of predictable patterns. AI has broken those patterns apart. In his view, modern safeguards need to sit closer to employees, understand how fragments are created, and guide people toward safer workflows without slowing them down. By the time we reached the end of the interview, it was clear that AI governance is no longer a strategic nice-to-have. It is becoming a daily operational requirement. Nishant believes employers must create a clear path forward that balances freedom with control, and give teams the tools to do their best work without unknowingly putting their organisations at risk. His message wasn't alarmist. It was practical, grounded, and shaped by years working at the intersection of data and security. So here is the question I would love you to reflect on. If AI is quickly becoming the engine of productivity across every department, what would your organisation need to change today to keep its data safe tomorrow? And how much visibility do you honestly have over where your most sensitive information is going right now? I would love to hear your thoughts. Useful Links  Connect with Cyberhaven CEO Nishant Doshi on LinkedIn Learn more about Cyberhaven Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

Why does it feel as though every headline about the future of work points to AI pushing entry-level roles off a cliff? That question stayed with me as I sat down with Robin Adda, a long-time learning and development leader, bestselling author, and one of the most balanced voices I have heard on skills, technology, and the workplace. Robin argues that AI can protect white-collar roles rather than erode them, and hearing him explain why immediately shifted the tone of the conversation. From the start, Robin talks about how traditional training models have failed to keep pace with reality. Companies know the skills gap is widening, yet many still rely on broad, generic programmes that miss what people actually need. His journey toward building SkillsAssess grew out of that frustration. He realised that training without insight only scratches the surface, and employees end up going through motions instead of growing in ways that matter. Inside organisations, the picture is even more complicated. Robin describes teams that want to move forward but have no clear road map, along with job seekers who struggle with basic digital tasks long before they reach more advanced expectations. Opportunity exists, yet people often cannot reach it because they lack a personal starting point. His work focuses on bridging that divide by giving individuals clarity and giving leaders accurate visibility into their workforce. We also talk about the emotional weight behind all of this. Anxiety around AI is everywhere, especially for people who feel their role is drifting into uncertainty. Robin has seen organisations handle this well by focusing on clear information rather than vague reassurance. When people understand what they need to learn and why, their fear gradually shifts into something more constructive. Another area that stood out was his emphasis on human strengths. As routine work moves to AI systems, qualities like curiosity, communication, and thoughtful decision making become even more valuable. Robin explains how behavioural profiling and tailored learning pathways can help companies build stronger teams rather than rely on technology to smooth every challenge. By the end of our conversation, I found myself thinking differently about the future of work. Robin's perspective is grounded in decades of watching technology rise, fall, and rise again. He sees AI as a chance to rethink employability rather than fear the disruption. In his view, if we use these tools wisely, we can build a workforce that is more confident, more adaptable, and more resilient. So here is the question I want to leave you with. If learning could finally become personal, and if AI could help people understand their own potential instead of replacing it, what would that change for you and your organisation? And how would it reshape the way you think about your career? I would love to hear your thoughts. Find out more at https://skillsassess.ai and by following the SkillsAssess' LinkedIn Listen to Robin and key industry guests on the SkillsAssess podcast - When Skills Matter Connect with Robin directly on LinkedIn Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

Have you ever wondered what it looks like when an enterprise finally breaks free from spreadsheet-driven decision paralysis and lets AI take the wheel? That was the question at the back of my mind as I sat down with Bianca Anghelina, the founder of Aily Labs.  In our conversation, Bianca explains how her career inside large global enterprises shaped her view of the world. She saw first hand how companies could gather astonishing amounts of data but struggled to translate it into choices that actually mattered.  That friction pushed her to imagine something bolder, a decision intelligence platform that could remove the hand-stitched chaos of manual analysis and replace it with real-time clarity. She shares how she took the leap during an uncertain moment in 2020, trusting the idea that disruption often grows during difficult periods. Hearing her describe that early stage reminded me how many founders take quiet risks long before the public sees any success. What stood out most was the simplicity of her philosophy. Every company will eventually use AI, but only the ones that rewire their culture and everyday routines will turn it into measurable value. Bianca talks about the shift from pilots to production, the widening gap between firms that run AI at scale and those still treating it as a side project, and how leaders need to rethink their role if they want to see material financial impact. She also shares how Aily Labs uncovered a hundred million dollars in opportunities instantly for one enterprise, and how their AI agents connect previously isolated functions to solve resource allocation, supply chain shocks, and board-level scenarios in minutes instead of months. We also look ahead. Bianca outlines her vision for fully autonomous decision-making agents and the long path toward an operating model where strategy, execution, and action flow through a single intelligent layer. Her optimism about where this can lead Fortune 500 organisations over the next five years left me thinking about how quickly boardrooms will need to adapt. At the same time, she grounds that vision in her own story, acknowledging the mentors and supporters who helped her grow from corporate leader to founder. If you are wrestling with the business case for AI, or trying to understand why so many firms still struggle to get past experimentation, this episode offers a clear window into what happens when AI is built into the centre of how an enterprise thinks. It is a rare mix of founder story, practical insight, and a glimpse of the future. What part of Bianca's thinking resonates most with your own experience, and how do you see decision intelligence reshaping leadership teams in the years ahead? Let me know your thoughts.   Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

Is AI quietly pushing us to work alone when creativity has always thrived on collaboration? I'm joined by Joseph "Coop" Cooper, co-founder of Nullshot, to unpack a different vision for how AI should support creators, builders, and teams. And before any Interstellar fans get too excited, this is not the cinematic space explorer navigating wormholes; this is a serial entrepreneur building something very real on Earth, where conversations turn into working applications in real time. Coop shares how his journey from modding video games as a child to launching multiple ventures across crypto and developer tools shaped his belief that current AI tools lean too heavily towards individual productivity. He explains the thinking behind Nullshot's jam rooms, where multiple people can co-create with AI in a shared space, instead of building in isolation. We explore how this model encourages quieter voices to contribute, removes the pressure of pitching ideas, and replaces it with live prototypes that speak for themselves. Alongside the enthusiasm for this collaborative future, Coop also addresses the tougher questions around ownership, fair credit, and how contributions should be recognised without being gamed. There is an honest discussion about whether AI-powered creation lowers barriers for everyone or risks shifting too much power towards the platforms that control it. The balance between opportunity and risk feels central to what Nullshot is attempting to achieve. As teams, founders, and creators look for better ways to bring ideas to life together, this conversation offers a grounded look at what shared AI creation could mean in practice. Are we ready to move from solo prompts to collective building, and what might that shift say about how we define creativity in the next phase of digital work? What do you think, could collaborative AI change the way your team builds, and how would you feel about sharing ownership in a live creative space? Useful Links Learn More About Nullshot Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

Is the UK quietly slipping into the role of a cautious observer while other nations shape the future of AI with greater confidence and intent? In this episode of Tech Talks Daily, I sit down with Rav Hayer, Managing Director at ThoughtWorks and Head of BFSI, to explore why our approach to AI regulation may be slowing progress at a time when momentum matters.  We move beyond the headlines of multi-billion pound investment announcements and look at what is really happening on the ground for business leaders trying to innovate in an environment shaped by uncertainty, shifting guidance, and risk aversion. Throughout our conversation, Rav shares his perspective on how this climate is affecting founders, scaleups, and established enterprises alike. We examine why so much British innovation still finds its way overseas, and what that says about ownership, long-term competitiveness, and the confidence gap holding many organisations back.  I also ask Rav to compare the UK's position with regions such as Singapore, Brazil, and Saudi Arabia, where proactive regulation is being used to encourage innovation rather than create friction. Together, we unpack the hidden costs of ambiguity, from time lost in legal interpretation to talent being drawn away from building meaningful progress at home. We close the episode on a more human note as Rav reflects on his personal journey, the role his parents played in shaping his work ethic, and the values that continue to guide his leadership today. As the UK weighs protection against progress, should we continue to step carefully, or is it time to show greater conviction and direction in our AI strategy? I would love to hear your thoughts on where that balance should sit. What do you think, and how should the UK move forward from here? Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

What happens when a seasoned finance leader steps into the world of enterprise software and decides to rebuild the financial close with AI at its core? In my conversation with Darren Heffernan, CEO of Trintech, we look at the shifts taking place inside the office of the CFO and how automation is reshaping a discipline that has relied on spreadsheets and manual routines for generations. Darren's story spans public practice, GE Capital, and twenty years inside Trintech, which gives him a rare view of both the pressure inside finance teams and the opportunities created when workflow, data, and intelligence finally come together. Across our discussion, Darren explains how Trintech has spent decades refining the financial close by embedding intelligence directly inside the workflow rather than bolting it on. He talks through real examples of AI identifying exceptions, writing rules, scanning volumes of transactions, and reaching back to a human for review so the outcome remains transparent and traceable. His point is that trust and clarity matter as much as speed, especially in a profession where regulators, auditors, and boards expect every action to be explainable. It is a reality check for anyone comparing providers claiming to deliver AI without the decades of grounding needed to understand how finance actually works. We also talk about the human side of transformation. Darren believes the people who learn to work with AI will thrive, and he pushes back against the idea that automation threatens finance roles. Instead, he sees a future where agents and humans collaborate while accountants focus on judgment, interpretation, and value. His reflections on leadership, mentorship, humility, and the maturity that comes from doing almost every role inside a company add a personal texture to the story. It is clear that his philosophy of making time count is not a slogan, it is a way of working that shapes how Trintech designs its products and how teams support customers. As we look toward 2026, Darren shares his view on the next frontier in finance. He describes a future where AI powered workflows not only detect issues but take action, improve continuously, and still respect the need for control. His message is simple. Finance runs on trust, and AI must strengthen that trust, never weaken it. So how should leaders approach this moment, and what might the financial close look like once AI becomes a reliable partner rather than a confusing buzzword? I would love to hear what you think.

What happens when a leader realises that the success of every major initiative, from AI projects to return to office plans, rests on something far deeper than strategy or tools? In my conversation with Phil Gilbert of Irresistible Change, we look at why culture is the deciding factor behind whether transformation takes root or quietly falls apart. Phil has spent a career inside some of the most complex organisations on the planet, and his work at IBM showed that change only becomes real when people want it, when they feel part of it, and when they see its value in their daily work. Across our conversation, Phil explains how he approached transformation inside a company with nearly four hundred thousand employees without forcing anyone into compliance. Instead of relying on memos or mandates, he treated change like a young startup that needed to earn believers. He focused on proof rather than persuasion, clarity rather than slogans, and an understanding that people respond to meaning, autonomy, and trust. It is a refreshing contrast to the typical corporate playbook that often leans on pressure rather than participation. We talk through the mindset shifts that helped him rebuild a culture at scale, including treating change like a product with a clear value proposition. Phil shares stories from inside IBM and reflects on why the same lessons now apply across industries. Today's workforce is more informed, more selective, and less willing to accept top down directives that lack substance. His view is that leaders who miss this reality are the ones left wondering why their carefully crafted strategies never quite land the way they expected. Phil's new book, Irresistible Change, digs into these ideas in detail. Our conversation gives a taste of that thinking and offers practical insight for anyone wrestling with transformation in their own organisation. Culture shapes the outcome of every big shift, whether leaders acknowledge it or not. So how can organisations build change that people choose to be part of, and what might be possible if more leaders approached transformation this way? I would love to hear your thoughts. Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

What happens when your entire market disappears overnight? That was the reality facing LoopUp when the pandemic transformed the way the world communicates. In this episode of Tech Talks Daily, I sit down with Steve Flavell, co-CEO of LoopUp, to talk about how his company turned disruption into a defining moment of reinvention. LoopUp began in 2003 with a mission to make conference calls less painful. For over a decade, the company grew steadily, even going public on the London Stock Exchange in 2016. But when Teams and Zoom became household names during the pandemic, LoopUp's core business all but vanished. Faced with that challenge, Steve and his team made a bold pivot, moving into global cloud telephony for Microsoft Teams. That shift didn't just save the company, it transformed it into what Steve now calls the world's most multinational telco, providing enterprise voice services in 136 countries. Steve shares what it took to steer through that transformation, from managing fivefold surges in traffic to building a scalable global service model. He also reflects on the leadership lessons learned along the way, including the power of persistence, transparent communication, and the strength of his 22-year co-founder partnership with Michael Hughes. This is a story of resilience, clarity, and strategic courage. For any founder or business leader who's ever faced a market shock or wondered how to evolve when everything changes, Steve's journey offers an honest and inspiring roadmap for rebuilding stronger than before.

What happens inside a transformation program when every decision must withstand scrutiny, every dependency carries weight, and every undocumented rule inside a legacy system can change the outcome of an entire initiative? That was the starting point for my conversation with Adebimpe Ibosiola, a specialist who has spent her career working in regulated industries where nothing is ever as simple as it looks on paper. In a space where leaders often feel pressure to modernize at speed, she argues that the real progress comes from slowing down long enough to understand the truth of the systems, people, and cultures already in place. During the discussion, Adebimpe shared how many organisations walk straight into failure because they begin with visions instead of diagnosis. She explained how hidden logic in old systems, variations in compliance interpretation, and the invisible labour teams carry out daily can derail the best-intentioned roadmap.  Her view is that transformation only becomes possible when leaders commit to technical truth-finding and accept that legacy platforms often contain valuable intelligence worth translating rather than discarding. It was eye-opening to hear how she decodes behavioural quirks in systems, aligns teams around shared language, and builds processes where correct behaviour becomes the easiest path. We also spoke about the human journey that accompanies digital change. Adebimpe sees emotional resilience, micro wins, and psychological safety as core components of sustainable progress in any regulated environment. Her approach blends structure with empathy, especially when teams feel pressure from audit requirements or fear of missteps. She also offered powerful reflections on why collaboration is the real competitive advantage for future professionals and how diversity strengthens decision-making in high-stakes environments. This conversation stays with you because it reframes transformation through honesty, clarity, and human understanding rather than slogans or promises of fast fixes. It also highlights an emerging truth. Regulated industries are moving toward a future shaped by people who can translate across technology, regulation, and culture rather than those who see transformation as a tooling exercise. What stood out to you in Adebimpe's perspective? And where do you think regulated organisations should begin if they hope to create change that actually lasts? I would love to hear your thoughts. Connect with Adebimpe Ibosiola on LinkedIn  Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

Why do entire organisations invest millions building resilient data centres yet leave their endpoints exposed to outages that can last days? That question kept coming back to me during my conversation with James Millington of IGEL at the Now and Next event, because it highlights a gap that most IT leaders still underestimate. James walked me through the reality he sees every day. Companies have high availability strategies for their servers, cloud platforms, and networks, yet the devices workers rely on remain the weakest point. When ransomware or system failure hits, the response often involves scrambling for spare laptops, calling suppliers, and hoping inventory exists. As James pointed out in our chat, many firms quietly rely on a handful of unused machines sitting in a cupboard. That approach might have worked a decade ago, but today's threat landscape exposes every delay. Our discussion centred on IGEL's dual boot approach, a fresh way to recover access within minutes by placing IGEL OS alongside Windows on the same device. Instead of waiting hours or even weeks to rebuild machines, organisations can simply switch to a secure environment that restores access to cloud apps, collaboration tools, and virtual desktops. James shared stories of analysts admitting no comparable solution exists, and of customers having light bulb moments as they calculated the true cost of endpoint recovery. The theme running underneath it all was simple. You cannot coordinate your crisis response unless your people have a working device in their hands. Everything else depends on that. This episode also reflects a wider shift in how organisations think about resilience. Leaders are beginning to question old assumptions about failover, preparation, and what it takes to keep people productive when attacks or outages strike. The conversations I heard throughout Now and Next showed that businesses are realising the endpoint is no longer a peripheral concern. It is the gateway to every service that keeps a company running. When that gateway fails, everything slows. James also shared lighter moments from his journey. His career began as a DJ, something he has circled back to at IGEL events, and it was fascinating hearing how skills from that era still show up in his approach to communication and timing. It reminded me how varied experiences shape the leaders driving today's conversations around security, SaaS evolution, Zero Trust, and the growing overlap between IT and operational technology. So here is my question for you. As cyber risks rise and downtime becomes harder to tolerate, how ready do you feel for the disruption that begins at the endpoint? I would love to hear your thoughts. Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

What happens when a founder who built a billion dollar company during a global crisis steps into the centre of industrial AI and begins reshaping how entire organisations think and work? That question sat at the heart of my conversation with Somya Kapoor, CEO of IFS Loops, recorded live on the show floor at IFS Industrial X Unleashed. Somya's journey carries a level of grit and perspective that shines through every answer. She shared how surviving the Gulf War as a child shaped her instinct to take on the hardest problems in technology. That mindset not only guided her early career at SAP, ServiceNow, and other enterprise giants, it also laid the foundation for Loops, the agentic platform she co-founded in 2020 with a simple scribble on a notepad that eventually grew into one of the most significant acquisitions in the IFS ecosystem. Her stories about early rejections, the wave of scepticism around AI in the early days, and the first customer conversations held on Zoom during lockdown reveal the human side behind a platform many now take seriously across the industrial world. Across the episode, Somya explained in plain terms what makes IFS Loops so different. The platform connects data across systems using natural language, helps redesign processes that used to be locked inside individual applications, and introduces digital workers that remove the grunt work from everyday operations. She brought the technology to life with examples that landed with real clarity. From supplier order handling to complex field service tasks, and the now famous Kodiak Gas case where thousands of hours were saved each year, she showed how agentic workflows change what is possible for industrial companies who have spent decades wrestling with fragmented data and rigid processes. We also talked about the importance of keeping people at the centre of AI driven change. Somya was clear that amplification, not replacement, is the story that matters. The shift requires new skills, new supervision models, and a thoughtful approach to adoption. Her reflections on change management, the energy she felt from customers at the event, and the speed at which leaders now want to move painted a picture of an industry that feels very different from the early days of AI excitement. The hesitation has faded. Curiosity has taken over. Action is starting to follow. Somya closed with a message aimed at every leader who might still be watching from the sidelines. The technology is real, adoption is accelerating, and the window to learn, experiment, and adapt is narrowing. She believes this is the moment for teams to decide whether they want to lead or be led by others who are moving faster. As you listen to this conversation, I'd love to hear what stood out for you. Do you feel the same shift in confidence and urgency around industrial AI that Somya described? Let me know your thoughts.   Tech Talks Daily is Sponsored by NordLayer: Get the exclusive Black Friday offer: 28% off NordLayer yearly plans with the coupon code: techdaily-28. Valid until December 10th, 2025. Try it risk-free with a 14-day money-back guarantee.

Have you ever wondered what happens when the browser stops being a simple window to the web and starts becoming the control point for how AI touches every part of enterprise life? That was the starting point for my conversation with Michael Shieh, founder and CEO of Mammoth Cyber. What followed was a detailed look at why the browser is turning into the foundation of enterprise AI and why the shift is arriving faster than many expect. Michael shared why employees already spend most of their working lives inside a browser and how this makes it the natural place for AI to support decisions, speed up routine work, and act as the interface between people, applications, and data. But we also spoke about the uncomfortable reality behind that convenience.  When consumer AI browsers rush ahead with features that harvest data or request wide-reaching permissions, the trade off between speed and governance becomes harder to ignore. Michael explained how this gap leaves security teams unable to see where sensitive data is being sent or how shadow AI creeps into daily workflows without oversight. During our conversation he broke down what makes an enterprise AI browser different. We talked about policy controlled access, device trust, identity federation, and the safeguards that protect AI from hazards like indirect prompt injection. Michael also described how the Mammoth team built a multi layer security model that monitors what the AI can view, what it cannot view, and how data moves across applications in real time. His examples of DLP at the point of use, low friction controls for workers, and granular visibility for security teams showed how the browser is becoming the new enforcement boundary for zero trust. We also covered the growing tension between traditional access models like VPNs or VDI and the faster, lightweight deployment Mammoth is offering to large enterprises. Hearing Michael explain how some customers replaced heavy remote access stacks in weeks made it clear that this is more than a new product category. It hints at an early move toward AI shaped workflows running directly at the endpoint rather than through centralised infrastructure. As he looked ahead to the next few years, Michael shared why he expects the browser to operate as a kind of operating system for enterprise AI, blending native AI agents, web apps, and policy controls into a single environment. This episode raises an important question. If the browser becomes the place where AI reads, writes, and interprets information, how should enterprises think about identity, trust, and control when the pace of AI adoption accelerates again next year? I would love to hear your thoughts.