The Tech Blog Writer Podcast

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.

What happens when a former NHL player who once faced Wayne Gretzky ends up running a global data company that sits at the center of the AI boom? That question kept coming back to me as I reconnected with Mike McKee, the CEO of Ataccama, seven years after our last conversation. So much has shifted in the world since then, yet the theme that shaped this discussion felt surprisingly grounded. None of the big promises of AI can take hold unless leaders can rely on the data sitting underneath every system they run. Mike brings a rare mix of stories and experience to this theme. His journey from the ice to the C suite feels like its own lesson in discipline, teamwork, and patience, and he openly reflects on the way those early years influence how he leads today. But the heart of this conversation sits in the reality he sees inside global enterprises. Everyone is racing to build AI powered services, yet the biggest blockers are messy records, inconsistent metadata, long forgotten databases, and years of quality issues that were never addressed. It is a blunt problem, and Mike explains why the companies winning with AI right now are the ones treating data trust as a foundation rather than an afterthought. Across the discussion, he shares stories from organisations like T Mobile and Prudential, where millions of records, thousands of systems, and vast volumes of structured and unstructured data must be monitored, understood, and governed in real time. Mike walks through how teams build confidence in their data again, why quality scores matter, and how automation now shapes everything from compliance to customer retention. What stood out most is how quickly the expectations have shifted. Boards and CEOs now treat data as a strategic asset rather than an operational chore, and entire roles have emerged above the chief data officer to steer these programmes. This episode is also a reminder that AI progress is never only about models or GPUs. Mike pulls back the curtain on why organisations struggle to measure AI readiness, how they can avoid bottlenecks, and what it takes to prioritise the work that actually moves the needle. His point is simple. Without trustworthy data, AI remains a promise rather than a practical tool. With it, businesses can act with confidence, respond faster, and make decisions that genuinely improve outcomes for customers and employees. So as AI reaches deeper into systems everywhere, how should leaders rethink their approach to data trust, governance, and quality? And if you have been on your own journey with data challenges, where have you seen progress and where are you still stuck? 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 former Microsoft leader walks away from tech, immerses himself in personal wellbeing, and accidentally discovers one of the biggest blind spots in the global spa, salon, and wellness industry? That question sat with me as I spoke with Sudheer Koneru, founder and CEO of Zenoti, who has shaped one of the most influential platforms powering beauty, wellness, and fitness operations in more than fifty countries. This conversation takes an interesting path. Sudheer began his career inside Microsoft during its high-growth era, then built and exited a successful enterprise software company, only to step away from the industry entirely. Those two quiet years focused on health and family revealed something surprising. The spa and salon sector he was engaging with as a customer lacked modern tools, consistent experiences, and operational systems that could help both staff and guests thrive. That realisation moved him from passive observation into building Zenoti, a platform designed for large brands with multi location operations. Today, Zenoti supports more than twelve thousand businesses and processes millions of bookings each year. Across our discussion, Sudheer explained why staff turnover shapes guest trust far more than most of us realise. He shared the emotional aspect of returning customers wanting familiar faces, the operational pressure this creates, and the measurable business impact when those connections are lost. We also talked about the role of AI. Unlike many narratives that focus on automation replacing creativity, Sudheer was clear that AI is strengthening the personal side of the industry. He described how tools like Zeni and Hyperconnect reduce missed calls, increase upsells, support new staff with real context, and free human teams to offer better on site care. Hearing how Zenoti has grown as a profitable unicorn while staying selective about its customer base added another layer. Sudheer credits this discipline as one of the company's strongest decisions, along with a willingness to focus on brands that truly benefit from the platform's depth. As the wellness and beauty sectors move further into AI supported operations, the question becomes whether businesses can adopt new capabilities without losing the warmth and familiarity that keep guests returning. After listening, how do you feel about AI supporting personal service industries, and where do you see the right balance landing? 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 enterprise AI moves faster than the data foundations meant to support it? That question guided my conversation with Sumit Mehra, CTO and Co-Founder of Tredence, who joined me while travelling between customer meetings on the US West Coast. Sumit has a clear view of what is coming next, and he believes we are entering a phase he calls data Darwinism.  In his view, the next stage of AI advantage will not be won by the companies with the most models or the flashiest demos, but by those with the strongest data habits. Clean, governed, connected data is now the primary fuel for autonomous decision systems, and the enterprises that fail to address this will struggle to move past surface level gains. As we unpacked this shift, it became obvious how much of the real work in AI has only just begun. Over the years, Tredence built a reputation for solving the last mile of analytics by bringing insights out of slide decks and into the hands of the people doing the work. Sumit described that early chapter with a sense of pride, but he was quick to point out that another transition is already here. With agents now influencing and making decisions across supply chains, forecasting, and customer experience, enterprises are moving from reviewing insights to reviewing decisions. That shift demands stronger data platforms, tighter governance, and a cultural adjustment that many organisations are still wrestling with. Sumit spoke openly about how teams need support to trust agent driven outcomes, and how the leadership layer plays a major role in closing the long standing divide between business and technical groups. Our discussion also moved into the rise of real time decision systems, the move toward unified data platforms, and how vertical AI is reshaping expectations inside industries that rely on precision. Whether it was supply chain visibility, marketing personalisation, or the growing need for credible governance models, Sumit emphasised that organisations can no longer rely on siloed data or fragmented strategies. As Tredence expands deeper into regulated industries through its acquisition of Further Advisory, the work ahead touches everything from finance to healthcare. It left me thinking about how ready most companies truly are for this next phase, where every agent is only as reliable as the data beneath it. Where do you stand on data Darwinism, and how prepared do you think your own organisation is for what comes next? 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 becomes the centre of how we shop, yet trust still determines whether any of it works? That question shaped my conversation with Romain Fouache, CEO of Akeneo, who joined me to unpack the latest consumer data on AI driven shopping experiences. Retail giants might be setting the pace, but the real story sits in how everyday shoppers feel about these new tools. Akeneo's recent research caught my attention when it revealed that eighty four percent of consumers who acted on an AI recommendation were satisfied with the purchase. The appetite is clearly there, yet trust remains fragile, especially when only forty five percent feel confident in AI powered suggestions and even fewer enjoy their chatbot interactions. Romain sees this moment as both a turning point and a warning, one that demands honest conversations about transparency and product data. As we worked through the findings, Romain explained why good AI depends entirely on high quality product information and why poor data is still the biggest threat to customer confidence. He argued that brands can reduce friction, improve discovery, and deliver more relevant experiences by grounding their AI tools in reliable product knowledge rather than guesswork. He also spoke about why many chatbots continue to miss the mark. The issue is less about the technology and more about the lack of strong product foundations beneath it. When recommendations go wrong, trust erodes quickly, and rebuilding that trust will require clear communication about how data is used and why certain suggestions appear. I found his view on privacy particularly interesting, especially his belief that better intent based interactions could lower the industry's dependence on invasive data collection. Looking ahead to 2026, Romain shared why he expects conversational shopping to become a primary way people browse and evaluate products. He believes the shift away from keyword driven search is already happening and that smaller retailers should not feel outpaced by the largest platforms. With the right product experience strategy, he says, AI opens new opportunities for global reach and category diversification. The conversation also touched on why product experience, rather than product data alone, will determine the brands that build loyalty in an increasingly competitive environment. It left me wondering how ready businesses truly are for a world where product information must be accurate, real time, and aligned with the way AI tools interpret customer intent. What do you think matters most for building trust in AI powered shopping? 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 events become the most human channel in a world increasingly shaped by AI? That thought set the tone for my conversation with Muhammad Younas, founder and CEO of vFairs, who has spent years helping organisations design in-person, virtual, and hybrid experiences at a remarkable scale. With more than fifty thousand events delivered and over one hundred million attendees served, he has a front row view of how event technology is changing and why the next wave will look very different from what planners have relied on until now. Rather than fearing the impact of AI, Muhammad sees a near future where mundane tasks fade into the background and planners focus on strategy, creativity, and connection. Throughout the discussion, Muhammad returned to a simple idea. Every event is unique, and technology should adapt to that reality rather than forcing people into rigid templates. He believes the next chapter of event tech will focus on specialised workflows that understand industry needs, whether that is a job fair, a healthcare gathering, a global town hall, or a conference that carries an entire community's voice. He also sees events becoming one of the most important expressions of first party marketing as digital channels get louder and harder to trust. When people choose to attend, they bring intent, time, and attention, and no online algorithm can replace that. We also explored why virtual events and webinars continue to grow long after the urgent push of the pandemic. Muhammad explains that these formats thrive because they offer reach, convenience, and year round value. They generate content that fuels engagement far beyond the event itself, and they remove the barriers that keep global audiences locked out of traditional venues.  Meanwhile, vFairs keeps pushing forward, from smart matchmaking on trade show floors to tools that help planners capture meaningful connections and follow through on them. In an era driven by AI, he argues that events will matter even more because they protect the authenticity and human contact that many feel is slipping away. Muhammad's own story, from running hundreds of events himself to building a platform chosen by global brands, adds a human layer to all this technology. It raises an important question. As AI reshapes the work behind the scenes, how will event planners and organisations reimagine the experiences people value most? I would love to hear what you think. 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 say about the future of work when AI competency starts to feel as expected as basic reading? That question sat with me throughout my latest conversation with Artem Kroupenev, VP of Strategy at Augury, who returns to the show with a perspective that lands with fresh clarity. Workforce costs remain high, industries are shifting, and the job market continues to reset its foundations. In that environment, Artem argues that AI literacy is no longer something ambitious candidates use to stand out. It is becoming a baseline expectation that employers will quietly assume. The way we talk about skills is changing, and the speed of that shift matters. Across our discussion, Artem reflects on how this transition is unfolding inside factories and industrial operations, where Augury has spent the last decade building predictive machine health systems. He describes a world where AI takes on tasks, not entire roles, and where the real opportunity for workers sits in judgment, collaboration, and the kind of problem solving that software cannot replicate. He highlights patterns from the SOPH 2025 data that show strong confidence across manufacturing leaders, yet also reveal a gap between optimism and real capability. It paints a picture of an industry moving quickly, yet still learning how to measure and translate AI value into outcomes people can trust. What struck me most was how Artem links mindset to readiness. Individuals who treat AI as a companion in their daily workflow, rather than a novelty to test occasionally, start building the fluency that future roles will quietly demand. Employers who approach AI simply as a tool upgrade often overlook the harder work of reshaping processes, KPIs, and expectations. And the organisations that fail to adapt risk widening the gap between AI empowered and AI hesitant teams, something Artem believes will show up in hiring, competition, and long term viability. This conversation looks beyond the usual headlines about automation and considers what the next five years might actually feel like for people joining the workforce or leading teams through change. If AI becomes as expected as reading and writing, what does that mean for education, career paths, and employer responsibility? I would love to hear your view. 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 resilience look like when your business depends on keeping data, apps, and infrastructure running flawlessly in a world that never sleeps? At IGEL's Now & Next event in Frankfurt, I sat down with Sush Kajaria from Nutanix to explore how the company is helping organizations simplify their cloud strategies and strengthen their endpoint environments through modern virtualization and prevention-first security. Our discussion looked at how IT teams are adapting to an increasingly complex technology stack, where workloads are spread across hybrid and multicloud environments. Sush Kajaria explains how partnerships with companies like IGEL are creating more seamless integration between data centers and the edge, giving IT leaders the control and visibility they need to protect business continuity. We also explored how automation, unified management, and secure access are helping enterprises reduce costs without sacrificing flexibility or performance. The conversation moved beyond infrastructure to address the human side of digital transformation. We discussed how hybrid work, evolving compliance requirements, and AI adoption are reshaping how IT teams operate, forcing leaders to rethink how they deliver secure and consistent experiences to employees everywhere. Nutanix's story is one of constant reinvention, driven by a clear mission to make enterprise IT invisible while keeping operations resilient and efficient. As organizations look ahead to 2026, this episode offers a grounded look at what it takes to balance innovation with reliability. How can IT leaders simplify their infrastructure without losing control, and what role will partnerships like IGEL and Nutanix play in defining the next chapter of enterprise resilience?     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 a global professional services firm commits over one billion dollars to AI and expects it to reshape the way its people work across every corner of the business? That question sat with me as I spoke with Russ Ahlers, Chief Information Officer at BDO USA, and someone who has spent three decades building technology foundations that hold up some of the most complex operations in the industry. This conversation goes straight into the reality of enterprise AI programs, the human decisions behind them, and the scale required to turn strategy into day to day transformation. Russ shares how BDO is approaching AI as a global effort rather than a series of disconnected projects. He explains how the firm's five year investment is designed to upgrade core systems, bring automation into areas that slow teams down, and build intelligent capabilities that support professionals across audit, tax, and advisory. I was interested in how he balances ambition with governance, and he offers a grounded view on why AI only delivers real value when firms focus on data quality, security, and practical use cases that free people to do higher value work. What stood out is Russ's long view. His time leading BDO International's IT strategy shaped the way he thinks about scale, convergence, and consistency. Across this episode he reflects on the lessons learned from supporting member firms worldwide, the importance of shared standards, and the cultural shift needed for AI to land with impact across a large workforce. His perspective is shaped by years of integrating new firms into the BDO network, where technology adoption and organisational change must move together. This episode is a chance to understand how a major global organisation is building its future on intelligent systems, why long term investments matter, and how leaders think about readiness, risk, and opportunity when the stakes are high. It also speaks to something more personal. Russ talks about the mindset behind modern IT leadership, the importance of curiosity, and the practical realities of running an innovation program that touches every part of the enterprise. Where do you stand on the idea of a billion dollar AI commitment, and what questions would you want answered before making a move like that? I would love to hear what you think.   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 take to build an AI-ready network in 2025? In this episode of Tech Talks Daily, I speak with Vikas Butaney from Cisco and Ali Tehrani from Presidio to unpack the biggest announcements from Cisco's Partner Summit and discuss how their collaboration is helping enterprises modernise networks for the AI era. Together, we explore how businesses can move faster, strengthen security, and simplify operations while adapting to a world of continuous data flow and intelligent automation. Vikas shares how Cisco's strategy is built around three customer imperatives: AI ready data centers, future proof workplaces, and digital resilience. He talks about how Cisco is weaving these priorities into new innovations such as secure routers with five times the throughput, Wi Fi 7 access points, and unified dashboards that bring Catalyst Center and Meraki together for a single view of the network. He also introduces AI Canvas, a multiplayer workspace that allows NetOps and SecOps teams to collaborate in real time, showing what it looks like when AI becomes part of the operational fabric rather than an add on. Ali joins the conversation with the partner's perspective, explaining how Presidio brings Cisco's architecture to life through the last mile of execution. He describes how the Cisco Unified Branch initiative uses AI workflows and branches as code to deliver zero touch rollout across thousands of sites. By combining automation, golden configuration templates, and telemetry driven SLAs, Presidio helps customers reduce deployment times from weeks to minutes while maintaining consistent performance and security. Throughout our discussion, we compare AI for networking, where AI helps to run and optimise the network, with networking for AI, which provides the infrastructure to power high volume AI workloads. We talk about how Cisco is building security directly into the network with Access Manager, simplifying IoT segmentation, and preparing for a post quantum world. This episode offers a clear, inside look at how Cisco and Presidio are shaping the next generation of secure, intelligent networks. So, how ready is your organisation for this new era of AI driven connectivity?   You said: Please also insert these links Press Release: Cisco Supercharges its Secure Enterprise Network Architecture for the AI Era Blog: Unlocking the AI Era: How Cisco is Delivering on its Vision for a Secure, Simplified, and Scalable Network Blog: From Fragmented to Future-ready with Unified Branch: Powering IT in the AI Era   ChatGPT said: What does it really take to build an AI ready network in 2025? In this episode of Tech Talks Daily, I speak with Vikas Butaney from Cisco and Ali Tehrani from Presidio to unpack the biggest announcements from Cisco's Partner Summit and discuss how their collaboration is helping enterprises modernise networks for the AI era. Together, we explore how businesses can move faster, strengthen security, and simplify operations while adapting to a world of continuous data flow and intelligent automation. Vikas shares how Cisco's strategy is built around three customer imperatives: AI ready data centers, future proof workplaces, and digital resilience. He talks about how Cisco is weaving these priorities into new innovations such as secure routers with five times the throughput, Wi Fi 7 access points, and unified dashboards that bring Catalyst Center and Meraki together for a single view of the network. He also introduces AI Canvas, a multiplayer workspace that allows NetOps and SecOps teams to collaborate in real time, showing what it looks like when AI becomes part of the operational fabric rather than an add on. Ali joins the conversation with the partner's perspective, explaining how Presidio brings Cisco's architecture to life through the last mile of execution. He describes how the Cisco Unified Branch initiative uses AI workflows and branches as code to deliver zero touch rollout across thousands of sites. By combining automation, golden configuration templates, and telemetry driven SLAs, Presidio helps customers reduce deployment times from weeks to minutes while maintaining consistent performance and security. Throughout our discussion, we compare AI for networking, where AI helps to run and optimise the network, with networking for AI, which provides the infrastructure to power high volume AI workloads. We talk about how Cisco is building security directly into the network with Access Manager, simplifying IoT segmentation, and preparing for a post quantum world. If you want to learn more about Cisco's announcements and vision for the AI era, check out these resources: Cisco Supercharges its Secure Enterprise Network Architecture for the AI Era Unlocking the AI Era: How Cisco is Delivering on its Vision for a Secure, Simplified, and Scalable Network From Fragmented to Future Ready with Unified Branch: Powering IT in the AI Era This episode offers a clear, inside look at how Cisco and Presidio are shaping the next generation of secure, intelligent networks. So, how ready is your organisation for this new era of AI driven connectivity?   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 if the real weakness in enterprise cybersecurity isn't the cloud or the network, but the endpoint sitting on every desk? In this episode, Klaus Oestermann, CEO of IGEL Technology, joins me at the Now and Next event in Frankfurt to discuss why he calls the endpoint the forgotten link in digital transformation. Klaus explains how decades of detect and mitigate thinking have left enterprises vulnerable, and why it is time to move toward a prevention-first security model that stops attacks before they start. He shares how IGEL's dual boot architecture allows organizations to recover thousands of devices in minutes, and why prevention-first design can deliver measurable ROI with an average 62 percent reduction in endpoint IT costs and more than 900,000 dollars in annual savings. During our conversation, Klaus also reflects on the surge in ransomware across critical sectors and why governments and enterprises alike are rethinking their endpoint strategies. He talks about how IGEL has become an essential part of modern Zero Trust frameworks, protecting sectors like healthcare, manufacturing, and public services, while partnering with leading technology providers to build stronger, integrated defenses. We also explore how those savings can be reinvested into Zero Trust, AI innovation, and new layers of defense, as well as how IGEL is helping secure critical national sectors from healthcare to manufacturing. From Audi's factory floors to government agencies, Klaus outlines a future where resilience begins at the endpoint, not the data center. Do you think enterprises are ready to make that shift? I would love to hear your thoughts after the episode. Useful Links Connect with Klaus Oestermann on LinkedIn Learn more about IGEL Follow on LinkedIn, Twitter and YouTube 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 if filing your taxes was as effortless as asking your AI assistant a question? For millions of people, the annual ritual of gathering receipts, logging into confusing portals, and racing against deadlines remains one of life's most dreaded tasks. But what if that stress could disappear completely, replaced by a real-time financial ally working quietly in the background? In this episode of Tech Talks Daily, Neil sits down with Snir Yarom, Chief Technology Officer at Taxfix, to explore how the Berlin-based fintech is redefining the relationship between people and their money. Snir shares how Taxfix has become truly AI native, embedding intelligence into every layer of its product, technology, and culture. This transformation is not about adding AI features, but about rethinking how products are designed, developed, and delivered in an era where customer expectations evolve faster than most companies can keep up. Snir explains how his teams are using AI to supercharge productivity, accelerate discovery, and even code 40 percent faster while maintaining human oversight and trust at the core. The conversation also dives into Snir's vision for the future of tax and personal finance, an always-on AI assistant that continuously optimizes your finances rather than showing up once a year to tally the damage. He discusses the concept of product market fit collapse in the age of AI and how legacy companies risk falling behind when they fail to adapt at the same pace that technology evolves. From governance and transparency to human in the loop systems, Snir outlines how Taxfix is balancing innovation with accountability in one of the world's most regulated industries. As AI reshapes finance, the question isn't whether it will change how we manage money, but how far that change can go while keeping human trust intact. Could your next tax return be filed without you even noticing? Listen in, then share your thoughts, would you trust an AI to manage your taxes from start to finish? Useful Links: Connect With Snir Yarom on LinkedIn Learn more about us Taxfix here https://medium.com/taxfix https://www.instagram.com/teamtaxfix/ https://www.facebook.com/taxfix.de/ https://github.com/taxfix     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 if the real story of AI isn't about chatbots or copilots at all, but about what happens when intelligence becomes part of the infrastructure of how work gets done? That's the idea driving this conversation with Vahid Taslimi, CEO and co-founder of Zenphi, who joins me from Melbourne, Australia, to discuss how his team is quietly redefining the way organizations think about automation. Vahid believes the real potential of AI lies not in flashy interfaces or generative tools, but in its ability to act as an invisible layer that powers everyday business operations. He explains how Zenphi is embedding AI into workflow automation for companies across sectors—from Gordon Food Service, which uses AI to manage access reviews and reduce shadow IT, to Action Behavior Centers in the US, where AI ensures compliance in sensitive healthcare processes. In each case, the focus is on operational AI that improves efficiency, accuracy, and decision-making without exposing organizations to unnecessary risk. We also talk about the importance of starting small, proving value, and scaling sensibly, echoing lessons learned from the early days of SaaS adoption. Vahid shares his views on how to move from AI experiments to enterprise-wide deployment, how to build compliance and governance into every layer, and why the future of automation depends on empowering non-developers to shape their own workflows. His no-code approach is enabling HR, finance, and operations teams to experiment safely with AI, achieving compounding gains without depending entirely on IT departments. Throughout our chat, Vahid brings to life the concept of "AI as infrastructure" with grounded stories and practical insights. He also reflects on how Zenphi balances innovation with reliability, ensuring that even regulated industries can integrate AI responsibly. As he puts it, sometimes the smartest systems are the ones you never see. So how close are we to a world where AI is simply part of the background of every business process? And what will it take for companies to trust AI at the infrastructure level rather than the interface?    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 can leadership in Formula One teach the rest of us about business transformation? In this episode of the Tech Talks Daily Podcast, I sit down with Seb Sheppard, whose career has taken him from flying helicopters in the Royal Navy to leading engineering teams in Formula One and steering post-merger integrations across multiple industries. His story isn't just one of impressive career shifts but of understanding what truly drives high performance—people, trust, and focus. Seb shares how growing up in Chile and working across different cultures taught him the value of clear communication and empathy in leadership. He explains why protecting technical teams from distractions can often be the most productive thing a leader can do, and how wellbeing initiatives work best when driven by employees themselves rather than top-down policies. Drawing on his time at Alpine F1, he also reveals the delicate balance between cost control and performance improvement, describing how he helped grow the engineering team by a third while staying within strict budget limits. Our conversation also explores the human side of mergers and acquisitions. Seb discusses why integration efforts often fail when companies overlook culture and people, and how proactive communication—long before an announcement is made—can make the difference between success and attrition. He also speaks about the evolving relationship between technology and leadership, explaining how AI can be embraced without losing the human element that drives creativity and trust. If you're a leader facing constant change, this episode is a masterclass in adaptability, humility, and practical wisdom. You'll come away with lessons from both the skies and the racetrack that apply directly to your own teams and projects. Connect with Seb Sheppard at www.sebsheppard.com or on LinkedIn at linkedin.com/in/sebsheppard. 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.

How do you secure a world where trusted internal traffic now travels over the public internet? That's the question I put to Doug Merritt, CEO of Aviatrix, in this thought-provoking conversation recorded for Tech Talks Daily. Doug brings decades of experience from his time leading Splunk and other major technology players, and he now finds himself at the forefront of reshaping how enterprises think about cloud security. We discuss why the cybersecurity landscape is more treacherous than ever, especially as AI accelerates both defense and attack capabilities. Doug explains why the old "castle and moat" mindset no longer applies in the age of cloud workloads, where perimeters are atomized and workloads are ephemeral. He outlines how identity, endpoint, and network security form a three-legged stool—yet too many organizations focus on one leg while neglecting the others. Doug also shares why embedding protection directly into the network fabric changes the rules for defending the cloud, and how his team at Aviatrix is helping companies close dangerous visibility gaps. We explore the rise of agentic AI, the growing sophistication of lateral movement attacks, and why even trusted identities can pose risk in distributed environments. As we look to the future, Doug argues that the path forward is clear: build on strong foundations, simplify the noise, and make network visibility a first-class citizen in enterprise defense. What do you think—are most organizations ready to shift from bolted-on tools to truly embedded cloud security? I'd love to hear your thoughts after listening. 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.

  Every software team, no matter its size or sophistication, has wrestled with the same quiet threat, technical debt. But what if the issue isn't just messy code or outdated frameworks, but something more human? That's the question Ernesto Tagwerker, Founder and CEO of OmbuLabs.ai, has been asking as he works at the intersection of AI, developer experience, and legacy modernization. In this episode of Tech Talks Daily, Ernesto joins me from Philadelphia to unpack why technical debt is so misunderstood and why the term has drifted far from Ward Cunningham's original metaphor. He argues that many teams treat it as a one-off cleanup task when, in reality, it's a living health issue that must be managed continuously. As he explains, "Every time you have to work around messy code, you're paying interest. And if later never comes, that interest piles up until progress grinds to a halt." We explore how AI is changing the way engineers think about remediation and developer experience (DX). Ernesto shares how OmbuLabs.ai uses AI agents to automate parts of the Rails upgrade process, scanning codebases for deprecations and generating actionable plans for clients. But his caution is clear, these tools are only as smart as the people orchestrating them. When used carelessly, they can generate invisible layers of new debt just as fast as they resolve the old. Ernesto also reflects on research from Google that reveals how "technical debt" varies wildly between teams and projects. He explains why leadership alignment is vital, how recurring surveys can help identify developer pain points, and why organizations should measure "technical health" rather than chase the unrealistic goal of zero debt. We discuss the cultural shift required for long-term success and why allocating even 10 to 20 percent of each sprint to DX improvements can dramatically reduce burnout and turnover. Finally, Ernesto offers his take on the future. AI will continue to automate repetitive work and surface smarter insights, but human oversight remains non-negotiable. In his words, "AI agents are only as good as their human operator." This conversation goes beyond code reviews and sprint retrospectives. It's about redefining what progress means in software development, healthier systems, happier developers, and smarter collaboration between humans and machines. Listen now to hear how Ernesto Tagwerker and OmbuLabs.ai are rethinking technical debt, DX, and AI-driven engineering for the decade ahead.   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 if business intelligence didn't stop at answering what happened, but could finally explain why? In this episode of Tech Talks Daily, I sit back down with Alberto Pan, Chief Technology Officer at Denodo, to unpack how Deep Query is redefining enterprise AI through reasoning, transparency, and context. We explore how Deep Query functions as an AI reasoning agent capable of performing open-ended research across live, governed enterprise data. Instead of relying on pre-built dashboards or static reports, it builds and executes multi-step analyses through Denodo's logical data layer, unifying fragmented data sources in real time. Alberto explains how this semantic layer provides the business meaning and governance that traditional GenAI tools lack, transforming AI from a surface-level Q&A system into a trusted analytical partner. Our conversation also digs into the bigger picture of explainable AI. Deep Query reports include a full appendix of executed queries, allowing users to trace every insight back to its source. Alberto breaks down why this level of auditability matters for enterprise trust and how Denodo's support for the Model Context Protocol (MCP) opens the door to more interoperable, agentic AI systems. As we discuss how Deep Query compares with RAG models and data lakehouses, Alberto offers a glimpse into the future of business intelligence—one where analysts become guides for AI-driven research assistants, and decision-makers gain faster, deeper, and more transparent insights than ever before. So what does the rise of reasoning agents like Deep Query mean for the next generation of enterprise AI? And how close are we to a world where AI truly understands the why behind the data? Tune in and share your thoughts after listening.   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.

For years, many businesses believed that Apple devices were inherently secure. That illusion has faded. In this episode of Tech Talks Daily, I speak with Adam Boynton, Senior Security Strategy Manager at Jamf, about why visibility across macOS and iOS is no longer a luxury but a necessity. Adam explains how Jamf has evolved from device management to full Apple-native security intelligence, protecting over 75,000 organizations and more than 32 million devices. He shares how attackers no longer target individual operating systems but entire ecosystems, exploiting the gaps between how Apple secures its platforms and how enterprises actually monitor them.  From real-world cases to lessons learned at Jamf's annual JNUC conference, Adam describes how telemetry provides security teams with the truth about what's really happening on their endpoints, enabling them to transition from reactive incident response to proactive defense. Our conversation covers everything from the architectural blind spots that traditional Windows-centric tools can't see to the rise of AI-driven analysis that turns complex forensic investigations into minutes-long processes. We also explore how Jamf's partnerships, such as those with Elastic, are creating an open and integrated future for enterprise security, blending deep Apple signals with cross-platform context. For anyone still clinging to the myth that macOS or iOS "just work" without attention to security, this episode is a wake-up call. Adam outlines practical advice on patching, mobile hygiene, and zero trust, while revealing how Jamf's latest innovations are quietly making the most secure way the easiest way for users. Listen to hear how Jamf is redefining modern Apple security, turning management, identity, and protection into a seamless whole, and why accurate visibility—not assumptions—is now the objective measure of cybersecurity readiness. 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.

There was a time when a computer science degree almost guaranteed a fast track into a well-paid career. But that promise is slipping. In today's Tech Talks Daily episode, I reconnect with Hans de Visser, Chief Technology Officer at Mendix, to discuss why recent graduates are finding it more challenging than ever to secure their first role in technology, and what they can do about it. Hans brings decades of experience in software engineering and low-code innovation, and his perspective on today's market is both sobering and optimistic. We discuss new research indicating a sharp decline in junior developer openings since 2024 and explore how the rapid rise of AI has altered the hiring equation.  The expectation now is that young developers arrive fluent in automation, generative AI, and multidisciplinary tools —skills that few university programs can thoroughly teach. Yet, as Hans points out, this doesn't mean opportunity has vanished. It just looks different. Our conversation unpacks what this new reality means for aspiring developers. Hans explains how Mendix evaluates candidates by testing their ability to think critically about AI-assisted code rather than generate it.  He explains why graduates must master both traditional software foundations and modern tools, such as low-code platforms and agile applications. And he offers advice on building a mindset of lifelong learning, staying curious, experimenting with new tools, and understanding how AI can amplify rather than replace human creativity. For anyone feeling disheartened by the tightening job market, Hans offers balance and hope. He believes that as the definition of software developer evolves, new hybrid roles will emerge at the intersection of business, creativity, and technology. The graduates who will thrive are those who treat AI as a collaborator, not a competitor. Listen to this episode to hear how Mendix is helping redefine what it means to build software in the age of AI, and why today's tech graduates may need to think less about securing a single job title and more about creating a career that never stops learning. 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 cybersecurity look like beyond Earth's atmosphere? That's the question at the heart of this conversation with Kristiina Omri, Vice President of Special Programs at CybExer Technologies, and Aare Reintam, the company's COO. We met in Tallinn on the eve of the Software Defined Space Conference to explore how Estonia, in collaboration with the European Space Agency, is helping define the future of space cybersecurity through the world's first Space Cyber Range. The story begins unexpectedly—with a childhood memory of marmalade in a tube, the same kind sent to Soviet astronauts in orbit. For Aare Reintam, that small detail became the first spark of fascination with space, one that decades later evolved into CybExer's partnership with ESA. Together they've created a digital testing environment where satellites, ground stations, and communication protocols can be stress-tested for cyber resilience long before launch.  It's a bold move in an era when satellites underpin everything from GPS and precision farming to air travel and climate observation, yet often rely on decades-old technology vulnerable to attack. Kristiina Omri explains how the Space Cyber Range replicates real-world missions, allowing engineers and analysts to train under simulated attack conditions that feel indistinguishable from their actual control systems. The range combines the precision of digital twins with the competitive intensity of cyber exercises, preparing teams for threats that can ripple from orbit to everyday life on Earth. The conversation covers everything from the growing space-debris crisis to the global shortage of cybersecurity professionals, and the urgent need to blend space engineering with cyber education. We also discuss the deeper strategic implications. What happens when quantum computing enters the battlefield? How should Europe prepare for the convergence of cyber and kinetic threats in orbit? And what lessons can be learned from Estonia's leadership in NATO cyber defense as it extends that expertise to the stars? By the end of the discussion, one theme stands out clearly: the future of cybersecurity is no longer confined to our planet. From digital twins to orbital trust networks, CybExer Technologies and the European Space Agency are proving that the next frontier for cyber readiness lies in space itself.

In this episode, I sit down in Tallinn with Madis Võõras, Head of the Estonian Space Office at Enterprise Estonia, to unpack how Estonia is carving out a real role in the European space sector through brains, code, and smart partnerships. Madis explains how his team connects Estonian companies with the European Space Agency, brings public investment back into the local economy, and uses space projects as a launchpad for globally competitive products and services. He shares why Estonia's sweet spot is software, how the country's digital public infrastructure became a reference point for European programs, and why the next wave of value will come from data, cybersecurity, and rapid deployment rather than rockets alone. We also talk about what it takes to build a space economy in a market of 1.3 million people. Madis walks through lessons from early contracts, the rise of an Earth observation data hub, and a business incubator that has already helped dozens of founders move from idea to revenue. He is candid about the gaps too, including the need for more hardware depth and the reality that international cooperation is the fastest route to scale. From optical communications between Tallinn and Helsinki to the practical use of AI inside satellite programs, you will hear a pragmatic roadmap rather than hype. If you want a grounded look at how space policy meets startup grit, and why collaboration with the European Space Agency is a catalyst rather than a finish line, this conversation is for you. What should Estonia prioritize next to punch above its weight in the global space economy, and where do you see the biggest opportunities for software and AI in space services? Share your thoughts and join the discussion.

What role does cybersecurity play when the battlefield extends beyond Earth's atmosphere? In this special episode recorded live in Tallinn for the fifth anniversary of the Software Defined Space Conference, I sit down with Kalev Koidumäe, CEO of the Estonian Defence and Aerospace Industry Association, to explore how software and security are transforming the future of space and defense. Kalev shares how Estonia, a nation of just 1.3 million people, has built global credibility through innovation, collaboration, and cyber resilience. From the lessons of the 2007 state-level cyberattack to the country's integration of space technologies within NATO's defense framework, Estonia has developed a model that combines agility with strategic foresight. Our conversation spans everything from the evolution of Estonia's space sector to its growing ecosystem of AI-driven defense technologies, autonomous systems, and satellite solutions. Kalev also explains how lessons from the war in Ukraine are reshaping Europe's defense landscape and accelerating the need for resilient, software-defined systems. What makes this discussion particularly fascinating is the balance Estonia maintains between national sovereignty and international cooperation. Kalev explains how the country's reserve army model, cyber education initiatives, and public-private partnerships have created an ecosystem where innovation is both strategic and deeply rooted in civic responsibility. It's a blueprint for how smaller nations can play a meaningful role in global security through ingenuity and collaboration. As the world navigates an era of heightened geopolitical tension and rapid technological advancement, this discussion offers a glimpse into how small nations can make a big impact in securing both cyberspace and outer space. So what can larger nations learn from Estonia's approach to innovation, readiness, and cyber defense? And how might software continue to redefine the future of space security? Share your thoughts after listening.

Artificial intelligence has changed how we think about service, but few companies have bridged the gap between automation and genuine intelligence. In this episode of Tech Talks Daily, I'm joined by Puneet Mehta, CEO of Netomi, to discuss how customer experience is evolving in an age where AI doesn't just respond but plans, acts, and optimizes in real time. Puneet has been building in AI long before the current hype cycle. Backed by early investors such as Greg Brockman of OpenAI and the founders of DeepMind, Netomi has become one of the leading platforms driving AI-powered customer experience for global enterprises. Their technology quietly powers interactions at airlines, insurers, and retailers that most of us use every day. What makes Netomi stand out is not its scale but the philosophy behind it. Rather than designing AI to replace humans, Netomi built an agent-centric model where AI and people work together. Puneet explains how their Autopilot and Co-Pilot modes allow human agents to stay in control while AI accelerates everything from response time to insight generation. It is an approach that sees humans teaching AI, AI assisting humans, and both learning from each other to create what he calls an agentic factory. We explore how Netomi's platform can deploy at Fortune 50 scale in record time without forcing companies to overhaul existing systems. Puneet reveals how pre-built integrations, AI recipes, and a no-code studio allow business teams to roll out solutions in weeks rather than months. The focus is on rapid time-to-value, trust, and safety through what he calls sanctioned AI, a framework that ensures governance, transparency, and compliance in every customer interaction. As our conversation unfolds, Puneet describes how this evolution is transforming the contact center from a cost center into a loyalty engine. By using AI to anticipate needs and resolve issues before customers reach out, companies are creating experiences that feel more personal, more proactive, and more human. This is a glimpse into the future of enterprise AI, where trust, speed, and empathy define the next generation of customer experience. Listen now to hear how Netomi is reimagining the role of AI in service and setting new standards for how businesses build relationships at scale.

What if the biggest barrier to AI adoption isn't the technology itself, but our ability to learn, adapt, and reskill? That question sits at the heart of my conversation with Sagar Goel, Managing Director and Partner at Boston Consulting Group, who leads the firm's global work on digital workforce development and reskilling. Speaking from Singapore, Sagar brings a rare combination of data, strategy, and humanity to the discussion on how AI is reshaping the global workforce—and why the frontline is struggling to keep up. Drawing on BCG's latest "AI at Work" research, Sagar reveals a surprising trend: frontline AI usage has stalled at around 50 percent for the first time. He explains why many companies are still approaching AI as a tool rollout rather than a behavioral and cultural shift. According to him, employees often don't know where or how to use AI effectively, leadership support is lacking, and training programs are too shallow to spark genuine adoption. The result is a productivity paradox—AI potential without real impact. Sagar also unpacks another counterintuitive finding: leaders are more worried than their teams about losing their jobs to automation. He attributes this to leaders' heightened awareness of structural disruption and their own vulnerability in adapting mid-career. Meanwhile, countries across the Global South are outpacing the US in AI adoption, driven by youthful populations, economic necessity, and a hunger for differentiation in tight job markets. Throughout the discussion, Sagar draws a clear line between upskilling and reskilling—two terms often used interchangeably but representing distinct needs. Upskilling, he explains, should embed AI fluency into daily workflows from the CEO down, while reskilling must redeploy people into new, higher-value roles as automation accelerates. He cites IKEA's decision to retrain 8,000 call center staff into design consultants as a model example of turning disruption into opportunity. We close with a candid reflection on leadership responsibility in the age of AI. For Sagar, the message is simple but profound: if skills don't show up on your balance sheet, they won't show up in your business performance. As the half-life of skills shrinks to five years, he urges CEOs to integrate workforce readiness directly into strategy, or risk being outpaced by those who do. This episode is a grounded, data-driven look at what it truly takes to prepare people—not just machines—for an AI-driven world.