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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 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.    

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 happens when early-stage founders realise their go-to-market strategy just isn't working? Do they double down on outdated advice or take a fresh look at how modern buyers actually engage?  In this episode of Tech Talks Daily, I sit down with Richard Lowry, founder of Springboard IQ, to unpack how he's helping startups rebuild broken GTM strategies in just seven days through a crowdsourced, operator-led model that challenges everything we think we know about growth. Richard explains how Springboard IQ brings together six active operators to co-create a go-to-market blueprint that's fast, focused, and grounded in the realities of today's market. This approach delivers practical strategy and design rather than execution, giving founders clarity on where to focus their time and energy. As Richard puts it, founders should save their passion for the demo because that's where it really matters. The conversation explores why technical founders often mis-hire sales talent, why relying on outdated accelerator advice can derail growth, and why many teams hit a “GTM wall” long before real scale begins. We also discuss why the future of GTM might look very different from the digital-first strategies of the past. As inboxes flood with automated outreach and AI-generated content, Richard believes human-led activation through curated events, community experiences, and even spontaneous moments of connection will define the next era of startup growth. It's a conversation that blends practical lessons, honest stories (including one involving a soup kitchen in Lisbon), and a call to bring the human element back to how we sell, connect, and grow. So, could a crowdsourcing strategy from active operators be the smarter way for startups to go to market? And in an era of AI-saturated noise, will the next big differentiator simply be showing up in person? I'd love to hear your thoughts after you listen.

What happens when a world-class badminton player trades the court for the courtroom and then the boardroom? In this episode of Tech Talks Daily, I sit down with Tom Dunlop, CEO and co-founder of Summize, to explore how a former Great Britain athlete became one of the most forward-thinking leaders in legal technology. Tom shares how his journey from sport to law to entrepreneurship shaped his leadership philosophy and his belief in “high agency,” the mindset of taking ownership, driving action, and leading from the front. We talk about how that outlook helped him transform the traditional image of legal work into something faster, smarter, and more collaborative through Summize's AI-powered Contract Lifecycle Management platform. Rather than forcing users to adopt new software, Summize integrates directly into tools people already use like Teams, Slack, Outlook, and Word, embedding contract management seamlessly into everyday workflows. We also explore Tom's reflections on brand building in a historically conservative industry, the mental shift from risk-averse lawyer to decisive founder, and why he believes legal leaders should embrace innovation as a way to strengthen their role at the boardroom table. His story is as much about personal reinvention as it is about technological disruption, revealing how determination, discipline, and curiosity can reshape even the most traditional professions. So, how do you balance precision with risk when you move from legal advisor to entrepreneur? And what lessons from sport, law, and leadership can help us all perform better in the fast-changing world of work? I'd love to hear your thoughts after listening.

What if the key to creating cleaner, faster, and more efficient cities isn't building new infrastructure, but rethinking how we move what we already have? In this episode of Tech Talks Daily, I'm joined by Richard Savoie, co-founder of Adiona, whose AI-powered logistics platform is transforming how goods travel through urban environments. Richard's background as a patent-holding engineer and mentor in the medical device field gives him a unique perspective on precision, quality, and human-centered design. At Adiona, he applies that same discipline to logistics, helping delivery networks run smarter, leaner, and more sustainably. His FlexOps platform uses AI to optimise routes, model EV fleet conversions, and create digital twins of operations so companies can reduce emissions and increase efficiency—without replacing the people who make it all work. In our conversation, Richard shares why he believes in a humanistic approach to AI that empowers drivers, dispatchers, and warehouse workers instead of automating them out of existence. We also explore how Adiona's scenario modelling helps global brands like Coca-Cola and Australia Post cut costs while meeting 2030 sustainability goals, and what the future might hold as AI and robotics begin to converge for last-meter delivery. So, could the next big sustainability breakthrough come from reimagining the routes that already exist? And how might AI reshape the logistics networks that keep our world moving? I'd love to hear your thoughts after listening.

Deepfakes used to be a niche curiosity. Today they have become a sophisticated tool for manipulation, persuasion, and exploitation. In this episode of Tech Talks Daily, I sit down with Aleksander Gorkowienko, Head of Penetration Testing at Risk Crew, to examine how artificial intelligence has transformed deepfakes from playful face swaps into full-scale multimedia attacks designed to deceive even the most vigilant among us. Aleksander explains how we have entered the age of Deepfakes 2.0, where fake video, audio, images, and text merge to create hyper realistic digital experiences. These aren't the crude social media edits of a few years ago. They are now weaponized as tools for emotional manipulation, exploiting fear, urgency, and trust to trick victims into transferring money, sharing data, or compromising systems. Aleksander walks through real world examples of how criminals build these illusions, using stolen digital footprints to impersonate executives, family members, and trusted colleagues in live video calls. We discuss how AI's accessibility has accelerated this problem. With free tools and moderate computing power, almost anyone can now create a convincing fake offline. Aleksander shares how this ease of creation erodes trust online, making it harder to distinguish truth from fabrication. He also reveals how attackers rely less on technology itself and more on psychology, engineering scenarios that push people into acting before thinking. From a defense standpoint, Aleksander offers clear, actionable insights. He talks about the importance of multi factor verification, context based awareness, and fostering what he calls “streetwise vigilance” in the digital world. He compares it to walking through a city at night; you wouldn't flaunt your valuables, so why overshare online? We explore how organizations can conduct training and simulations to teach employees to pause, question, and verify before reacting. This episode is a timely warning for every business and individual operating in a world where reality can be faked in seconds. Aleksander's rule of thumb is simple but powerful: never trust a single source of information. Cross check, slow down, and think before you act. Because in the age of AI deception, trust must be earned every time. Listen now to hear Aleksander's firsthand perspective on how deepfakes are changing cybersecurity and what we can all do to stay one step ahead.

What if the real breakthrough in AI isn't the model itself, but the data that gives it knowledge? In this episode of Tech Talks Daily, I sit down with Edo Liberty, founder and Chief Scientist of Pinecone, to unpack how vector databases have quietly become the backbone of modern AI infrastructure. We explore why retrieval-augmented generation (RAG) works so effectively out of the box, and why fine-tuning large models often adds complexity without real-world value. Edo shares how Pinecone's research revealed that different models—from OpenAI to Anthropic—require differently structured context to perform well, a discovery that's reshaping how enterprises think about AI implementation. As the former Director of Research at Yahoo and AWS, Edo offers a grounded perspective on where the real innovation is happening. He explains how the shift from traditional data structures to vector representations is redefining how machines “know” and retrieve information, creating smarter, context-aware systems. We also touch on his recent transition to Chief Scientist, his excitement for returning to hands-on research, and why he believes the convergence of AI and data represents the defining technological shift of our lifetime. So, what does it mean for developers, business leaders, and anyone building with AI when knowledge becomes an accessible layer of infrastructure? Can we build systems that truly “know” as humans do? Join the conversation, and after listening, I'd love to hear your thoughts—do you think the future of AI lies in the models or in the data that feeds them?

What if the biggest weakness in cybersecurity isn't a missing tool, but a cultural blind spot? That's the perspective of Dan Jones, Senior Security Advisor at Tanium, who joined me on Tech Talks Daily to share why he believes cybersecurity is fundamentally a people problem dressed up as a technology problem. Dan brings nearly three decades of experience in cyber operations, including leading cyber defence strategy for the UK Ministry of Defence. His career has shown him that technology alone doesn't secure organisations—it's the people at the front line, their leadership, and their ability to make the right decisions under pressure. He argues that while new tools flood the market every year, the make-or-break factor remains the same: how teams are led, supported, and empowered. In our conversation, Dan explains why leadership is often the overlooked part of cybersecurity, how culture shapes security outcomes, and why automation should be embraced not as a threat to jobs but as a way to give people time back for higher-value decision making. He shares examples from both military and enterprise contexts, showing how organisations succeed or fail based not on what tools they buy, but on how well they bring their people along for the journey. We also dig into one of today's hottest debates: the role of AI in cybersecurity. While many fear AI will displace jobs, Dan insists those fears are rooted in culture, not reality. He draws parallels to past industrial shifts, making the case that automation and orchestration are stepping stones that prepare teams for an AI-powered future—one where human judgment still sits firmly at the centre. This is a timely reminder for every leader and practitioner that cybersecurity is about more than firewalls and code. It's about trust, training, and people working together with the right tools at the right time. And yes, it's also about taking five minutes to brew a proper cup of tea—a lesson Dan believes says a lot about leadership and reflection. If you've ever wondered whether your organisation is focusing too much on tools and not enough on culture, this episode will make you stop and think. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

What does it take to deliver personalized financial guidance to more than 140 million people every single day? That is the question I put to Wan Agus, Head of Engineering at Intuit Credit Karma, in this episode of Tech Talks Daily. Most of us open the Credit Karma app to check our credit score, look at a loan option, or browse for a better credit card. What we rarely consider is the technology running behind the curtain. Wan revealed that his teams are powering more than 60 billion daily AI predictions to understand members' needs, protect their privacy, and guide them toward the right financial choices. He explained why accuracy is everything in fintech. A misplaced recommendation can mean more than a poor customer experience; it can damage someone's credit score and hold back their progress. Our conversation also looked at what happened after Intuit acquired Credit Karma. Two very different tech stacks had to be brought together, and identity systems had to be unified so members could move seamlessly between Credit Karma and products like TurboTax. Wan compared the process to playing two complex board games at once, where success depends on strategy and collaboration. We also explored how Credit Karma is blending traditional AI with generative AI. From early chatbot experiments to today's Wallet Analyzer and Tax Advisor, Wan shared how his teams decide when to push forward with new tools and when to slow down to ensure safety and trust. He also gave us a glimpse into the future, where agent-to-agent technology could bring open banking-style transparency to the U.S. So how do you scale personalization without losing trust? And what can every business leader learn from Credit Karma's balance between speed, culture, and responsibility? I would love to hear your thoughts after listening.

AI is quickly moving from boardroom buzzword to boardroom headache. Enterprises are waking up to the fact that bringing large language models in-house is not just about performance or cost, but about control, accountability, and trust. In this episode of Tech Talks Daily, I sit down with Octavian Tanase, Chief Product Officer at Hitachi Vantara, to unpack what this shift really means for business and technology leaders. Octavian explains why governance has become the defining challenge of the AI era. Companies are under pressure not only to innovate but also to meet new regulatory demands and maintain trust with customers. That requires more than patching together tools or hoping for transparency from public AI providers. It means creating governance frameworks that deliver traceability, auditability, and explainability as standard practice, not as afterthoughts. We explore why vector databases may need something like a time-machine capability to document when and how information is added, giving enterprises a provable audit trail. This level of accountability supports both internal oversight and external compliance, turning abstract AI ethics debates into real operational requirements. Our conversation also turns to the role of infrastructure. Hitachi Vantara's VSP One, with its tagline “One Data Platform, No Limits,” has been built to simplify data complexity across block, file, and object storage while providing a unified foundation for AI workloads. Octavian shares how this unified approach helps enterprises run compliant, explainable, and efficient AI across hybrid environments that span both on-premises and the cloud. This isn't just a story about technology, but about the future of trust in digital business. If AI remains a black box, its value will always be limited. If it becomes explainable, traceable, and accountable, it can transform not only efficiency but also relationships with customers, regulators, and partners. So, how can leaders strike the right balance between governance and innovation without slowing down progress? Octavian leaves listeners with a forward-looking perspective on what the next few years of enterprise AI will demand, and why those who build on strong governance today may end up with the most resilient advantage tomorrow.   ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

In this episode of Tech Talks Daily, I'm joined by Todd Grabowski from Johnson Controls to unpack the physics, products, and design choices shaping the next generation of data center cooling. It's a practical conversation that moves from chips and compressors to water, power, and land constraints, and what it really takes to keep modern infrastructure reliable at scale. Todd brings three decades of experience to the table and a front-row view of how Johnson Controls and the York brand have kept their focus on energy efficiency, reliability, and sustainability for more than a century. That longevity matters when the market is moving fast. He explains why cooling now sits alongside power as the defining constraint for data centers, and why roughly forty percent of a facility's energy can be spent on cooling rather than computation. If you lead technology, finance, or facilities, that single number should focus the mind. Todd walks through Johnson Controls' YVAM platform and the York magnetic bearing centrifugal compressor at its core, with real numbers on what that means in practice. Consuming around forty percent less energy than typical cooling devices of the past five years and operating in ambient conditions up to fifty-five degrees Celsius, it is designed for the reality of hotter climates and denser loads. The naval pedigree of the driveline is a nice twist, since it was originally built for quiet and high-reliability conditions long before hyperscale data centers needed the same. Sustainability threads through the entire discussion. Todd lays out how the company holds itself to internal targets while engineering solutions that reduce customer resource use. We talk about closed-loop designs that do not consume water, careful refrigerant choices with ultra-low global warming potential, and product footprints that consider carbon impact from the start. It is a useful reminder that sustainability is a systems problem, not a single feature on a spec sheet. I was especially interested in the three resources Todd says every modern cooling strategy must balance. Land, because you need somewhere to reject heat. Power, because every watt pulled into cooling is a watt not used for compute. Water, because many regions are already under stress and consumption cannot be the answer. Good design weighs these factors against the climate, the workload profile, and the operational model, then standardizes wherever possible so the same unit can run efficiently in Scandinavia or Dubai without special tweaks. We also dig into what AI means internally for Johnson Controls. It is showing up in manufacturing lines, speeding up design cycles, and improving the fidelity of compressor and heat transfer models. That translates into quicker time to market and more confidence in performance envelopes. On the market side, Todd is clear that demand has not softened. If anything, efficiencies tend to unlock more use cases, and the net effect is more workloads and continued pressure on facilities to cool them well. If your team is wrestling with when to adopt liquid cooling, how to reduce PUE through smarter chiller choices, or how to plan for climate variability across a global footprint, this episode offers an honest, grounded view from someone who has shipped the hardware and lived with its trade-offs. It also doubles as a quiet celebration of engineering craft. The kind that rarely makes headlines, yet underpins everything we build in the AI age. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA    

Here's the thing. Payments only look simple from the outside. In this Tech Talks Daily episode, I sit down with Roberto “Reks” Kafati, CEO and co-founder of DEUNA, to unpack how a scrappy one-click checkout idea grew into an intelligent payments infrastructure that now touches a large slice of Mexico's online economy.  Reks explains why Latin America's high decline rates aren't just an inconvenience but a growth killer, and how DEUNA's early focus on orchestration and checkout opened the door to something bigger. When a region routinely sees more than four out of ten online transactions knocked back, the bar for reliability sits in a different place. That practical problem set the stage for what came next. Athena, Real-Time Decisions, and 638 Signals per Transaction DEUNA's pivot point came when merchants asked a fair question. With all this payment data flying through the system, what should we do with it? The answer is Athena, DEUNA's AI-powered layer that watches every transaction and feeds merchants real-time insight, routing choices, and suggested actions. It is not another dashboard you promise to check and then ignore by Friday. It is a reasoning engine that sits on top of 638 data points per transaction and turns mess into movement. That is how you recover revenue without punishing good customers with extra friction, how you avoid surprise fees from networks, and how you protect recurring revenue when a processor wobbles. Reks walks us through results that speak plainly. Ramped merchants saw conversion lift from the original one-click experience. The infrastructure tier recovers meaningful GMV and trims fees. Enterprise clients report double-digit ROI and stick around for the compounding effect. Building Through Adversity and Betting on the Right Layer What resonated most was the human story behind the metrics. DEUNA was born in the first months of the pandemic, shaped by the shock that hit real-world businesses when revenue fell off a cliff and marketplaces became a lifeline with strings attached. Reks shares an unvarnished look at a tough 2023, the kind of year founders rarely talk about on record. Revenues dipped, deals went sideways, life got complicated. The team chose resilience and doubled down on a two-year vision. That bet is paying off. Over the past twenty-four months the company has grown at a pace that would bend a chart, and the focus has shifted from commoditizing orchestration to productizing intelligence. Put simply, earn trust at checkout, then make the data work for the merchant in real time. Agentic Commerce, US Expansion, and What Comes Next We also look forward. If chat interfaces begin to mediate more buying decisions, merchants will need infrastructure that can think, not just connect endpoints. That is the territory DEUNA calls intelligent infrastructure, and it is where Athena operates every day.  The company is now in active conversations with major US retailers, confident after winning head-to-head enterprise evaluations. Reks frames the opportunity without hype. If you can see acceptance trends by processor, by country, by card type, and act in the moment, you keep customers, protect margins, and avoid death by a thousand false declines. If you cannot, competitors will gladly welcome your frustrated shoppers. If you care about the real mechanics of growth, this conversation is for you. We talk conversion lift, recovered revenue, and the gritty bits of building a payments company that merchants actually rely on. We also talk about the days that test your resolve and the tenth day that reminds you why you started.

When I invited Or Eshed, CEO and co-founder of LayerX Security, onto Tech Talks Daily, I wanted to challenge a blind spot most teams carry into work each day. We talk about phishing, ransomware, and endpoint controls, yet we skip the place where employees actually live online. The browser. That quiet tab bar has become the front door to identities, payments, SaaS, and now AI. Or calls it a different operating system in its own right, and once you hear his examples of how extensions can intercept cookies, mimic logins, or even meddle with AI chats, the penny drops fast. Here's the thing. Blocking extensions across the board no longer fits how people work. Developers, marketers, sales teams, and support agents all lean on extensions for real productivity gains. Or's argument is simple. If the business depends on extensions, security has to meet people where they are with continuous, risk-based controls inside the browser itself. That means assessing code, permissions, ownership changes, and live behaviors, not relying on a static allow list that grows and grows while attackers slip through the cracks. We also unpack Extensionpedia, LayerX's free resource that lets anyone look up the risk profile of a specific extension. It is part education, part early warning system, and it serves a wider mission to raise the floor for everyone. Or shares how a technology alliance with Google has helped the team analyze extensions at serious scale, and why better data beats clever slogans in a space where signals change hour by hour. Malicious Extensions, AI Shortcuts, And The Culture Shift Security Needs One of the standout moments is a real-world story that starts at home and ends inside a corporate network. A spouse installs a screen-recording extension on a personal device, the browser profile syncs at work, and suddenly corporate credentials and sensitive sessions are mirrored to an untrusted machine. No shadowy APT needed. Just everyday sync doing exactly what it was designed to do. It is messy, human, and exactly why policy needs to be paired with continuous visibility in the browser. We explore the gray zone where productivity tools collide with privacy. Password managers, VPN helpers, and AI-everywhere extensions promise convenience, yet they can scrape data across SaaS apps or sync credentials in ways security leaders never intended. Or's advice is refreshingly pragmatic. Assume extensions are staying. Instrument the browser, score risk in real time, and adapt access based on what an extension actually does, not what it claims on a store page. Looking ahead, Or sees the browser taking an even bigger role as email, SaaS, and AI agents converge in one place. With AI companies building their own browsers, the last mile of user interaction gets denser, faster, and more valuable to protect. If 99 percent of enterprise users already run at least one extension, the task is clear. Know which ones are in play, understand how they behave, and keep policy dynamic. If this conversation sparks a rethink of your own approach, check your extensions in Extensionpedia, and then consider what modern, in-browser controls would look like in your environment. After this episode, you may never look at that tidy row of icons the same way again. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

During the IT Press Tour, I had the pleasure of speaking with Weimo Liu, CEO and co-founder of PuppyGraph, and hearing firsthand how his team is rethinking graph technology for the enterprise. In this episode of Tech Talks Daily, Weimo joins me to share the story behind PuppyGraph's “zero ETL” approach, which lets organizations query their existing data as a graph without ever moving or duplicating it. We discuss why graph databases, despite their promise, have struggled with mainstream adoption, often because of complex pipelines and heavy infrastructure requirements. Weimo explains how PuppyGraph borrows from his time at TigerGraph and Google's F1 engine to build something new: a distributed query engine that maps tables into a logical graph and delivers subsecond performance on massive datasets. That shift opens the door for use cases in cybersecurity, fraud detection, and AI-driven applications where latency and accuracy matter most. We also unpack the developer experience. Instead of rewriting schemas or reloading data every time requirements change, PuppyGraph allows teams to define nodes and edges directly from existing tables. That design lowers the barrier for SQL-focused teams and accelerates time to value. Weimo even touches on the role of graph in reducing AI hallucinations, showing how structured relationships can make enterprise AI systems more reliable. What struck me most in our conversation is how PuppyGraph's playful branding belies its serious engineering depth. Behind the “puppy” name lies a distributed engine built to scale with today's data volumes, backed by strong early adoption and a team that listens closely to customer needs. Whether you're exploring graph for cybersecurity, AI chatbots, or supply chain analytics, this discussion offers a glimpse of how the next generation of graph tech might finally break free from its niche and go mainstream. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

Artificial intelligence is no longer confined to experiments in labs or one-off pilot projects. For many enterprises, it is becoming the backbone of how they operate, innovate, and compete. But as companies race to deploy AI, the biggest challenge is not whether the technology works, but whether the foundations exist to scale it safely and effectively. In this episode of Tech Talks Daily, I'm joined by Christian Buckner, Senior Vice President of Data and AI Platform at Altair, a company known for combining rocket science with data science. Christian unpacks the concept of an AI Fabric, a framework that harmonizes enterprise data and embeds AI directly into a universal model. Rather than scattered tools and isolated projects, the AI Fabric acts as a living system of intelligence, helping organizations move faster, make better decisions, and unlock new kinds of automation. We talk about how global enterprises from automotive suppliers to petrochemical giants are already using Altair's technology to improve safety, optimize production, and cut costs. Christian shares examples including a transportation company that boosted revenue by $50 million in its first year of AI-driven dynamic pricing and a healthcare provider that saved $17 million in analysis time using knowledge graphs for drug discovery. The conversation also explores the hype and the risks around AI agents. While it is easy to spin up a proof of concept with a Python library, Christian explains why real enterprise impact requires governance, monitoring, and infrastructure to make agents trustworthy and sustainable. He likens it to building HR systems for AI, where agents need onboarding, oversight, and performance evaluation to operate alongside humans. We also touch on Altair's acquisition by Siemens and what this means for the future of industrial AI. By integrating Altair's data and AI expertise with Siemens' deep industrial systems, enterprises can add intelligence without ripping out existing infrastructure. The result is not about replacing workers but enabling them to become what Christian calls “10x employees,” augmented by AI tools and agents that multiply their effectiveness. For anyone curious about how AI will change product design, operations, and enterprise decision-making, this episode offers a rare inside look at the technology foundations being built today. You can learn more at altair.com/ai-fabric. ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

What if meetings stopped draining your time and instead became engines for action? That's the question driving Christoph Fleischmann, CEO of Arthur AI, and the conversation in today's episode of Tech Talks Daily. Christoph has spent his career at the intersection of human potential and technology, and now he's leading a company that wants to change how enterprises actually get work done. Arthur AI isn't another tool to add to the stack. It's a digital co-worker—an intelligent presence that joins meetings, captures knowledge, and keeps teams aligned across time zones and formats. Whether in XR spaces, on the web, or through conversational interfaces, Arthur AI blends real-time and asynchronous collaboration. The aim is to replace endless, inefficient meetings with something more dynamic: an environment where humans and AI collaborate side by side to deliver outcomes. This conversation goes beyond theory. Christoph shares how Fortune 500 companies are already using Arthur AI to align global strategies, manage complex transformations, and modernize learning and development programs. He explains how their platform is built on enterprise-grade security and a flexible, LLM-agnostic architecture—critical foundations for companies wary of vendor lock-in or compliance risks. We also touch on the cultural shift of inviting AI to take a real seat at the table. From interviewing and project management to knowledge sharing, Arthur AI represents a new category of work experience, one where digital co-workers support people rather than replace them. For leaders tired of meetings that go nowhere and knowledge trapped in silos, this episode offers a glimpse of what smarter, faster collaboration looks like at scale. Could the blueprint for the future of digital work already be here? ********* Visit the Sponsor of Tech Talks Network: Land your first job  in tech in 6 months as a Software QA Engineering Bootcamp with Careerist https://crst.co/OGCLA

When VMware Cloud Foundation 9.0 launched in June, it marked more than just another release. It was the clearest signal yet that Broadcom is betting big on the modern private cloud. In this episode of Tech Talks Daily, I sat down with Prashanth Shenoy, who leads marketing and learning for the VCF division at Broadcom, to discuss what the launch means for enterprises and how those themes are playing out live at VMware Explore in Las Vegas. Prashanth shares how VCF 9.0 was designed to help enterprises operate private clouds with the same simplicity and scale as public hyperscalers, while keeping sovereignty, security, and cost predictability front and center. He explains why this release is more than an infrastructure update. It's a shift toward a workload-agnostic, developer-centric platform where virtual machines, containers, and AI workloads can run side by side with a consistent operational experience. We also unpack Broadcom's headline announcements at the show. From making VCF an AI-native platform to embedding private AI services directly into the foundation, the message is clear: the AI pilots of the past are moving into production, and Broadcom wants VCF to be the default home for enterprise AI. Another major theme is cyber compliance at scale, with VCF now offering continuous enforcement, rapid ransomware recovery, and advanced security services that address today's board-level concerns. But perhaps the biggest takeaway is the momentum. Nine of the top ten Fortune companies are now running on VCF, more than 100 million cores have been licensed, and dozens of enterprises—from global giants to mid-sized insurers—are on stage at VMware Explore sharing their adoption stories. The so-called “cloud reset” that Prashanth has written about is not just theory. Companies are rethinking their cloud strategies, seeking cost transparency, avoiding waste, and building resilient, AI-ready private clouds. This conversation highlights how Broadcom is doubling down on VCF with a singular focus, a massive R&D commitment, and a clear vision of where private cloud is headed. If you want to understand why private AI, developer services, and cyber resilience are now central to enterprise strategy, this is a conversation worth hearing.

In this episode of Tech Talks Daily, I speak with Jane Ostler from Kantar, the world's leading marketing data and analytics company, whose clients include Google, Diageo, AB InBev, Unilever, and Kraft Heinz. Jane brings clarity to a debate often clouded by headlines, explaining why AI should be seen as a creative sparring partner, not a rival. She outlines how Kantar is helping brands balance efficiency with inspiration, and why the best marketing in the years ahead will come from humans and machines working together. We explore Kantar's research into how marketers really feel about AI adoption, uncovering why so many projects stall in pilot phase, and what steps can help teams move from experimentation to execution. Jane also discusses the importance of data quality as the foundation of effective AI, drawing comparisons to the early days of GDPR when oversight and governance first became front of mind. From Coca-Cola's AI-assisted Christmas ads to predictive analytics that help brands allocate budgets with greater confidence, Jane shares examples of where AI is already shaping marketing in ways that might surprise you. She also highlights the importance of cultural nuance in AI-driven campaigns across 90-plus markets, and why transparency, explainability, and human oversight are vital for earning consumer trust. Whether you're a CMO weighing AI strategy, a brand manager experimenting with new tools, or someone curious about how the biggest advertisers are reshaping their playbooks, this conversation with Jane Ostler offers both inspiration and practical guidance. It's about rethinking AI not as the end of creativity, but as the beginning of a new partnership between data, machines, and human imagination.

The enterprise network is under pressure like never before. Hybrid environments, cloud migrations, edge deployments, and the sudden surge in AI workloads have made it increasingly difficult to keep application connectivity secure and reliable. The old model of device-by-device, rule-based network management can't keep up with today's hyperconnected, API-driven world. In this episode of Tech Talks Daily, I sit down with Kyle Wickert, Field Chief Technology Officer at AlgoSec, to discuss the future of network management in the age of platformization. With more than a decade at AlgoSec and years of hands-on experience working with some of the world's largest enterprises, Kyle brings an unfiltered view of the challenges and opportunities that IT leaders are facing right now. We talk about why enterprises are rapidly shifting to platform-based models to simplify network security, but also why that strategy can start to break down when dealing with multi-vendor environments. Kyle explains the fragmentation across cloud, on-prem, and edge infrastructure that keeps CIOs awake at night, and why spreadsheets and manual change processes are still far too common in 2025. He also shares why visibility, intent-based policies, and policy automation are becoming non-negotiable in reducing risk and friction. Kyle doesn't just talk theory. He shares a real-world case study of a European financial institution that automated policy provisioning across firewalls and cloud infrastructure, integrated it with CI/CD pipelines, and reduced its change rejection rate from 25% to 4%. It's a compelling example of how the right approach to network management can deliver measurable improvements in agility, security, and business satisfaction.  

AI is rapidly becoming part of the healthcare system, powering everything from diagnostic tools and medical devices to patient monitoring and hospital operations. But while the potential is extraordinary, the risks are equally stark. Many hospitals are adopting AI without the safeguards needed to protect patient safety, leaving critical systems exposed to threats that most in the sector have never faced before. In this episode of Tech Talks Daily, I speak with Ty Greenhalgh, Healthcare Industry Principal at Claroty, about why healthcare's AI rush could come at a dangerous cost if security does not keep pace. Ty explains how novel threats like adversarial prompts, model poisoning, and decision manipulation could compromise clinical systems in ways that are very different from traditional cyberattacks. These are not just theoretical scenarios. AI-driven misinformation or manipulated diagnostics could directly impact patient care. We explore why the first step for hospitals is building a clear AI asset inventory. Too many organizations are rolling out AI models without knowing where they are deployed, how they interact with other systems, or what risks they introduce. Ty draws parallels with the hasty adoption of electronic health records, which created unforeseen security gaps that still haunt the industry today. With regulatory frameworks like the UK's AI Act and the EU's AI regulation approaching, Ty stresses that hospitals cannot afford to wait for legislation. Immediate action is needed to implement risk frameworks, strengthen vendor accountability, and integrate real-time monitoring of AI alongside legacy devices. Only then can healthcare organizations gain the trust and resilience needed to safely embrace the benefits of AI. This is a timely conversation for leaders across healthcare and cybersecurity. The sector is on the edge of an AI revolution, but the choices made now will determine whether that revolution strengthens patient care or undermines it. You can learn more about Claroty's approach to securing healthcare technology at claroty.com.

In November, Alex Adamopoulos, CEO of Emergn, joined me on Tech Talks Daily to talk about transformation fatigue and why so many well-intentioned change programs leave people drained rather than inspired. This time, he's back with a sharper question: if traditional transformation is broken, what actually works? His answer is refreshingly direct. Product thinking is strategic thinking, and it belongs everywhere in the enterprise, not just in product teams. In our conversation, Alex explains why HR, finance, and even legal teams now need product strategy skills as much as engineers or designers. He introduces Praxis, Emergn's newly launched platform that rebrands their long-standing VFQ approach and now embeds product thinking across entire organizations. With its AI-powered coach Stella, Praxis is designed to support continuous learning while helping teams make better day-to-day decisions. We also discuss why outcomes, not deliverables, have become the accurate measure of digital success. Alex likens it to leaders constantly returning to their boards like entrepreneurs on Shark Tank, demonstrating incremental value before securing the next round of support. This shift in accountability changes how teams plan, learn, and invest. Another essential thread is the link between burnout and broken transformation models. Alex recently co-authored a paper with Harvard professor Amy Edmondson on “Breaking the Failure Cycle,” and he shares how adopting a product mindset can help organizations move past fatigue by focusing on outcomes, embracing uncertainty, and avoiding the endless reinvention trap. Whether you're in a global enterprise grappling with AI adoption or a smaller company rethinking strategy, this episode is a reminder that transformation is not a program but a continuous practice. Product thinking offers a practical path forward, one that makes strategy executable, measurable, and, most importantly, sustainable.

In this episode of Tech Talks Daily, Neil sits down with Sean Li, co-founder and CEO of Magic Labs, to explore the intersection of crypto wallets, artificial intelligence, and the future of autonomous finance. Sean shares how Magic Labs has already onboarded over 50 million crypto wallets by pioneering simple login methods using email and SMS. Now, with Magic Newton, Sean is pushing into new territory where AI agents could securely manage digital assets on our behalf. From AI "concierges" executing investment strategies to cryptographic policy engines enforcing trust and control, the vision is clear: a financial internet where humans set the intent and machines handle the execution. We discuss the challenges of today's fragmented crypto experience, how smart wallets and AI could abstract away complexity, and why Sean believes everyone with an email address will eventually have multiple agents acting on their behalf. You'll also hear why he compares this shift to building a digital institution or constitution for autonomous finance. Whether you're a developer, investor, or simply crypto-curious, this episode offers a fascinating look at where Web3, AI, and programmable trust may be heading next.

In this episode of Tech Talks Daily, I'm joined for the third time by Justin Banon, the founder of Boson Protocol. A lot has changed since his last appearance. What started as a bold idea to decentralize e-commerce has now evolved into an ambitious, AI-first infrastructure aiming to redefine how we buy, sell, and interact with value itself. Justin walks us through the evolution of Boson. It began as a system for peer-to-peer digital and physical commerce, aiming to remove intermediaries like Amazon from the process. The next step was Fermion, a protocol designed specifically for high-value assets such as luxury goods, fine art, and real estate. Now, Boson is launching the Metasystem, a full-scale framework designed for what Justin calls “agentic commerce,” where AI agents transact on behalf of users. We talk about what that future looks like. Imagine an AI that not only shops for you but negotiates, verifies, and settles transactions securely. Justin predicts that in just a few years, these agents will outnumber human buyers and sellers by orders of magnitude. Boson's mission is to build the decentralized rails for that world while avoiding the centralization traps of today's tech giants. One particularly fascinating moment is our discussion of the Dolce & Gabbana glass suit. Purchased during the last bull run, this million-dollar piece of digital-physical fashion was not just fractionalized through Fermion but transformed into an AI persona called Dolce Lorien. This character now leads a gamified community campaign, rewarding participants with fractional ownership. It's luxury meets sci-fi, wrapped in Web3 narrative. We also dig into what decentralized infrastructure really means for legacy brands. With Fermion, companies can reclaim the secondary market, verify resales, reconnect with past buyers, and turn their customer base into a true community. This isn't just resale with a twist. It's a new type of programmable loyalty system. Justin shares how AI doesn't just enable commerce. It also supports his own personal growth. He reveals how he uses tools like ChatGPT and Speechify to create custom audio courses for niche subjects, walking through the woods while absorbing AI-generated masterclass-level insights. For those tired of seeing tech platforms control value creation while users are left with little ownership, this episode offers a glimpse of a different future. One where AI works directly for you. One where commerce is flexible, open, and fair. One where the infrastructure is built to stay that way.

The global pet industry has long been riddled with problems. From low-welfare breeding practices to online scams, the darker side of pet rehoming often goes unchecked. But what if there was a way to combine animal protection with a sustainable, profitable business model? In this episode of Tech Talks Daily, I speak with Axel Lagercrantz, co-founder and CEO of Pet Media Group, the company behind platforms like Pets4Homes in the UK and Lancaster Puppies in the US. Axel shares the story of how two friends with backgrounds in finance and tech came together to rethink what ethical pet ownership and commerce should look like. Since 2018, PMG has been working to remove anonymity and reduce fraud across pet marketplaces by embedding ethical standards directly into their platform's infrastructure. We explore how PMG uses custom-built AI to scan tens of thousands of images every day for signs of mistreatment, as well as to flag suspicious documentation and chat messages. Axel explains why ID verification, device fingerprinting, and real-time fraud detection are essential to maintaining user trust, especially in a high-emotion, high-value market like pets. He also talks through the company's expansion model, which focuses on acquiring local leaders and embedding PMG's standards from the ground up. With operations now spanning six countries and a 50 percent EBITDA margin, PMG's approach proves that protecting animals and scaling a business are not mutually exclusive goals. What stands out most is Axel's clarity of purpose. PMG isn't trying to digitize pet sales for convenience alone. The mission is to create a global infrastructure that prioritizes the welfare of animals and builds lasting trust between buyers and responsible breeders. If you care about technology that delivers real-world impact, this conversation will change how you think about one of the most overlooked parts of the digital economy.

When most people think of Wikipedia, they picture an endless scroll of human-readable pages. But there's another side to this ecosystem, one designed not just for people but also for machines. It's called Wikidata, and if you haven't heard of it, that's exactly why this conversation matters. In this episode of Tech Talks Daily, I'm joined by Lydia Pintscher, Wikidata Portfolio Manager at Wikimedia Deutschland, for a deep look into how structured, open data is quietly powering civic tech, cultural preservation, and knowledge equity across the globe. Wikidata is the backbone that helps turn static knowledge into something living, adaptable, and scalable. With over 117 million items, 1.65 billion semantic statements, and more than 2.34 billion edits, it's become one of the largest collaborative datasets in the world. But it's not just the size that makes it impressive. It's what people are doing with it. Lydia shares how volunteers and developers are building tools for everything from investigative journalism to public libraries, all without needing deep pockets or proprietary infrastructure. This isn't big tech. It's a global, grassroots movement making open data work for the public good. We explore how tools like Toolforge and the Wikidata Query Service lower the barrier to entry, allowing civil society groups to build sophisticated applications that would otherwise be out of reach. Whether it's helping connect citizens to government services or preserving disappearing languages, the use cases are multiplying fast. Lydia also reflects on how Wikidata fosters a sense of purpose for contributors, offering a rare example of what many call the good internet, where collaboration outweighs competition and building something meaningful beats chasing virality. If you're curious about where open knowledge is headed, how structured data can be a force for social impact, or why Wikidata might be the most important project you've never fully explored, this episode offers a window into a future where machines help humans build something better, together.

What does it take to make AI actually work at enterprise scale? In this episode of Tech Talks Daily, I'm joined by Ryan Steelberg, CEO of Veritone, to unpack the very real challenges and opportunities that come with bringing artificial intelligence into complex industries like media, law enforcement, and government. Ryan has been building AI solutions long before it became headline news. He co-founded Veritone in 2014 with a mission to solve the unstructured data problem. Think audio, video, and other media that doesn't fit neatly into rows and columns. Now, Veritone isn't just talking about AI. It's powering more than 3,000 clients across sectors with real applications that drive measurable ROI. We get into what it means to work with unstructured data at scale, and how Veritone processed over 58 million hours of media in 2024 alone. Ryan explains why traditional enterprises struggle to operationalize AI and how Veritone has evolved from a platform company into a creator of end-user applications designed for impact. This includes ad optimization for ESPN and video redaction for law enforcement. What's especially compelling is Veritone's growing footprint in high-barrier sectors like federal defense and law enforcement. Ryan talks through what it took to become a prime contractor for the U.S. Air Force and Defense Logistics Agency, how Veritone adapted its stack for secure deployments, and why the key to adoption in these sectors isn't just tech. It's trust and proximity to mission-critical outcomes. We also discuss the company's push into the $17 billion global training data market through the Veritone Data Repository. Ryan shares why VDR is gaining traction fast and how it positions the company as a key partner for the next generation of AI models. This isn't a story of hype or futuristic promises. It's a grounded look at what it really takes to scale AI in some of the most demanding enterprise environments. Whether you're deep in the AI world or still figuring out where your business fits, Ryan's perspective is honest, strategic, and full of lessons you can apply right now.

Is the future of finance programmable? In this episode of Tech Talks Daily, I'm joined by Ryan Galvankar, founder of Plaza Finance, to explore how programmable derivatives and on-chain bonds are reshaping the way we think about risk, leverage, and asset management in crypto. Plaza Finance isn't just another DeFi protocol. Since launching its core system on Base in April 2025, the team has introduced two standout tokens: bondETH and levETH. These programmable derivative tokens split Ethereum into customizable risk profiles, allowing both institutional and retail investors to choose their exposure with precision. Under Ryan's leadership, Plaza has already attracted over 600,000 testnet users, $2 million in early deposits, and $2.5 million in pre-seed funding. Ryan explains why this matters. Today's DeFi tools tend to sit at either extreme—ultra-safe or wildly speculative. Plaza aims to bridge that gap with products that reflect the diversity of traditional finance, yet remain liquid and composable across Ethereum's ecosystem. He also shares why Ethereum staking plays a central role, and how integrations with lending platforms and cross-chain bridges will make these tokens even more powerful. But Ryan doesn't stop at structured investing. He also launched OptFun, an ultra-short-term options trading platform that hit nearly $1 billion in trading volume within a month. It appeals to crypto natives seeking high-volatility speculation in a fair, on-chain environment. Together, these two platforms reflect what Ryan sees as a split in the future of DeFi: one track of thoughtful, long-term financial products that institutions will trust, and another track of high-speed, high-risk experimentation for users who live for volatility. He also gives his take on the rise of tokenized real-world assets, AI-generated portfolios, and what it will take to truly decentralize the next generation of finance. Whether you're deep into DeFi or still watching from the sidelines, this conversation sheds light on a pivotal moment where programmable finance is becoming real, and access to tailored financial tools is expanding faster than ever.

What if proving your right to work, rent, or even open a bank account didn't require digging out your passport or waiting weeks for manual verification? In this episode of Tech Talks Daily, I'm joined by Hamraj Gulamali, Head of Legal and Compliance at Zinc, to talk about how digital identities are changing the way we think about employment, data ownership, and trust. Hamraj brings a unique perspective to the conversation. A barrister-turned-startup leader, he now sits at the centre of one of the UK's most forward-thinking background check platforms. Zinc's mission is simple but ambitious: to make employment identity verification faster, safer, and fairer. But as Hamraj points out, this shift isn't just about convenience. It's about control. We discuss how digital IDs are already helping automate background checks, reduce onboarding delays, and improve accuracy in high-volume hiring environments. Hamraj explains why placing ownership of work identity back in the hands of individuals has the potential to unlock wider applications—from renting a home to streamlining banking processes. But there's also friction. Some industries face structural and cultural resistance. Others fear the cost of digital transformation or worry about public trust. Hamraj unpacks why regulators have both helped and hindered progress. He shares his view on the UK's Trust Framework, the Online Safety Act, and why transparency, retention policies, and robust cybersecurity are essential for building public confidence. As we look ahead, Hamraj offers a clear vision for how verified digital IDs could simplify everyday tasks, slash manual admin, and reduce the compliance burden across multiple sectors. This episode cuts through the noise to offer a calm, informed, and practical take on one of the most overlooked shifts in how we live and work. Whether you're in HR, tech, compliance, or just tired of carrying your passport across town on your first day of work, this conversation will get you thinking about what needs to happen next.

What does it take to build intelligent systems that are not only AI-powered but also secure, scalable, and grounded in real-world needs? In this episode of Tech Talks Daily, I speak with Srinivas Chippagiri, a senior technology leader and author of Building Intelligent Systems with AI and Cloud Technologies. With over a decade of experience spanning Wipro, GE Healthcare, Siemens, and now Tableau at Salesforce, Srinivas offers a practical view into how AI and cloud infrastructure are evolving together. We explore how AI is changing cloud-native development through predictive maintenance, automated DevOps pipelines, and developer co-pilots. But this is not just about technology. Srinivas highlights why responsible AI needs to be part of every system design, sharing examples from his own research into anomaly detection, fuzzy logic, and explainable models that support trust in regulated industries. The conversation also covers the rise of hybrid and edge computing, the real challenges of data fragmentation and compute costs, and how teams are adapting with new skills like prompt engineering and model observability. Srinivas gives a thoughtful view on what ethical AI deployment looks like in practice, from bias audits to AI governance boards. For those looking to break into this space, his advice is refreshingly clear. Start with small, end-to-end projects. Learn by doing. Contribute to open-source communities. And stay curious. Whether you're scaling AI systems, building a career in cloud tech, or just trying to keep pace with fast-moving trends, this episode offers a grounded and insightful guide to where things are heading next. Srinivas's book is available on Amazon under Building Intelligent Systems with AI and Cloud Technologies, and you can connect with him on LinkedIn to continue the conversation.

In this episode of Tech Talks Daily, I speak with Steve Corbesero, Jr., Senior Director of Products and Solutions at MachineQ, a Comcast Company, about the findings from their new Lab of the Future survey. Conducted with Censuswide, the study gathered insights from more than 400 U.S.-based lab professionals, revealing both the opportunities and persistent pain points shaping modern laboratory operations. Steve unpacks why nearly 60% of labs still face unplanned downtime from equipment failures, missed calibration schedules, and asset location issues. We discuss how manual monitoring remains the norm for over half of labs surveyed, and why 14% have no monitoring system in place at all. Despite these challenges, there's a clear appetite for change, with 85% planning to adopt IoT solutions and 87% intending to integrate AI and machine learning into their workflows over the next two years. Our conversation explores the operational impact of disconnected systems, the risks of relying on spreadsheets, and the role of real-time monitoring in preventing costly disruptions. Steve shares practical examples of how IoT and AI are already helping labs shift from reactive to proactive management, from anomaly detection that reduces alert fatigue to intelligent data summaries that give lab managers actionable insights without hours of manual analysis. We also talk about the barriers holding some labs back from adoption, including pilot purgatory, budget constraints, and integration challenges. Steve offers his perspective on how future-ready labs will differentiate themselves—by embracing connected infrastructure, unifying data, and embedding AI into both scientific and operational workflows. If you want to understand what's really happening inside modern labs, and how emerging technology can transform efficiency, productivity, and innovation, this episode offers a clear, data-backed view of the road ahead.

In this episode of Tech Talks Daily, I speak with Annelise Osborne, Chief Business Officer at Kadena, former Wall Street executive, and author of From Hoodies to Suits: Innovating Digital Assets for Traditional Finance. Annelise brings more than two decades of leadership experience in finance, real estate, and digital assets, and she has spent her career bridging the worlds of institutional finance and emerging blockchain technology. Our conversation begins with her personal journey from commercial mortgage-backed securities to the frontlines of blockchain innovation. She shares how a regulatory task force invitation led her to deep-dive into ICOs back in 2017, sparking her fascination with the potential of blockchain to modernize financial markets. That curiosity eventually became a career shift, culminating in her work at Propellr, ARCA Labs, and now Kadena. We explore the key themes of her book, which seeks to break down the language barriers between “hoodies” (tech innovators) and “suits” (traditional finance professionals). Annelise makes the case for clear regulation, continuous education, and interoperability as the three essential pillars for mainstream blockchain adoption. She's candid about the misconceptions that persist in traditional finance and explains why payment solutions, tokenization, and back-office efficiencies are the practical entry points for institutions. Annelise also gives a behind-the-scenes look at Kadena's blockchain infrastructure, from its proof-of-work security model and low gas fees to its plans for EVM compatibility and Web2-like user experiences. She highlights real-world use cases in sports fan engagement, product lifecycle tracking, and on-chain lending, illustrating how DeFi and TradFi can merge under regulated frameworks. Throughout the discussion, one theme is constant: the importance of finding the right partners, speaking each other's language, and staying curious in a fast-changing industry. Whether you're a finance professional, a blockchain developer, or simply interested in where digital assets are headed, Annelise's insights offer a grounded yet forward-looking perspective on the future of finance.

In this episode of Tech Talks Daily, I chat with Andy Wilson, Senior Director at Dropbox, to explore how AI is quietly but fundamentally changing how we work. Andy offers a deep dive into Dropbox Dash, an AI-powered search and knowledge management tool designed to cut through digital noise and reclaim the one thing most professionals are running out of: time. We unpack how Dash is solving the growing problem of content sprawl by integrating with over 60 SaaS platforms, offering AI-driven answers instead of just links. Andy describes it best: the internet lets you search all of human knowledge, but good luck finding that one deck from last quarter in your company's Google Drive. Dash aims to fix that. And it's already doing so for teams like McLaren F1, who use the platform to coordinate high-stakes race weekends with precision and security. We also discuss how Dropbox is adopting AI internally, from the acquisition of Reclaim.ai to enhancing virtual-first collaboration with intelligent scheduling and governance tools. For Dropbox, AI isn't a novelty. It's becoming the backbone of how distributed teams work better together. Andy likens it to having a personalized chief of staff, helping you prioritize, organize, and even remind you when to take a break. Our conversation also touches on Andy's creative roots at the BBC and Aardman, and how those experiences shaped his product thinking today. He shares real examples of how Dropbox supports content creators and knowledge workers alike, including feedback tools like Dropbox Replay and user-generated storytelling workflows powered by simple file request features. If you're wrestling with digital overload, managing hybrid teams, or just wondering how AI can actually help without taking over, this episode is for you. Andy paints a grounded, human picture of the future of work, one where AI supports creativity and restores clarity, not chaos.

Customer service used to be seen as a cost center. Something to manage, streamline, and, if possible, outsource or automate. But what happens when AI shifts that narrative entirely? In this episode of Tech Talks Daily, I sat down with Ryan Peterson, Chief Product Officer at Concentrix, to unpack how customer service is being reimagined as a revenue-driving engine. With 430,000 advisors handling millions of calls for brands across every major industry, Concentrix isn't theorizing about the future. They're building it. Ryan shares how blending human empathy with AI efficiency is creating faster resolutions, stronger loyalty, and in some cases, serious bottom-line results. One example saw upsell revenue rise from $500,000 to $1.6 million per month simply by supporting human agents with smart, context-aware AI assistants. We also talk about the evolution of the agent's role. Far from replacing jobs, AI is creating a new class of specialists called agent engineers. These are people responsible for maintaining, optimizing, and guiding AI systems that now work alongside human teams. This shift is opening doors for deeper personalization, real-time translation, and richer customer engagement across channels and geographies. Ryan also gives us a behind-the-scenes look at Concentrix's award-winning IX...Low Platform, which was recently named Intelligent Personal Assistant of the Year. Supporting over 7,000 AI agents and offering robust security and integration capabilities, the platform is designed for scale and resilience. It's not just handling simple FAQs. From legal contract analysis to proactive service interventions, these AI agents are transforming how enterprise support works. We close with a forward-looking conversation about hyper-personalization, ethical AI integration, and the long-term role of trust in CX strategy. Ryan's optimism is clear, but it's grounded in metrics, use cases, and a deep understanding of what businesses actually need to deliver meaningful customer experiences. If you're curious about what customer service looks like when AI and humans collaborate effectively, or what it takes to move from handling complaints to driving conversion, this is the conversation you'll want to hear.

If you've ever used IntelliJ IDEA, PyCharm, or Rider, you've probably already felt the impact of JetBrains. But what happens when one of the world's most trusted software development toolmakers starts asking whether developers should completely rethink their identity? In this episode of Tech Talks Daily, I caught up with Kirill Skrygan, the CEO of JetBrains. Kirill's story is something many developers will admire. He joined JetBrains as a junior developer back in 2010 and steadily worked his way through the ranks. Along the way, he helped launch new products, led remote development during the pandemic, and is now steering the company into the AI era. This isn't just about adding AI features to tools. Kirill is challenging long-held assumptions about what it means to be a software engineer. He believes we're entering a new chapter where non-technical creators will build their own tools, and where proactive AI agents will help maintain and even update code automatically. It's a bold vision, but one grounded in practical experience and responsibility. JetBrains is used by over 11 million developers, including 88 of the Fortune Global Top 100, so the stakes are high. We explored how AI is lowering the barrier to software creation, what that means for traditional developers, and why Kirill believes the shift won't devalue their skills but rather evolve them. He shared insights into JetBrains' own AI agent, Junie, which is already being used in production environments. He also talked about Kineta, their no-code platform designed for a new generation of creators, including those who want to build apps without a computer science background. There's also an honest discussion around the friction points of this new wave, especially when non-engineers build tools that later need to be secured and maintained. Kirill didn't shy away from the complexity of that challenge, but he's optimistic that the industry can solve it. Toward the end of the conversation, we reflected on JetBrains' role as an independent company that doesn't chase hype or rely on VC funding. That independence gives them the freedom to build what developers actually need, rather than what might look good on a press release. This episode is a thoughtful look at the future of software development, leadership from inside the codebase, and the evolving relationship between humans and AI in one of tech's most foundational professions. If you're a developer, CTO, product manager, or simply curious about how AI is changing the craft of coding, this one's worth your time.