Tech Talks Daily

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 Eppie Vojt on LinkedInWest Shore in this video

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 The No Asshole Rule: Building a Civilized Workplace and Surviving One That Isn't Range: Why Generalists Triumph in a Specialized World 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 Cyberhaven CEO Nishant Doshi on LinkedInCyberhaven 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. https://skillsassess.aiSkillsAssess' LinkedIn When Skills Matter 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? In this Fast Tracked conversation, 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.

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.