Tech Talks Daily

When building a successful startup, the difference between thriving and failing often lies in understanding the journey itself. Today, I had the pleasure of speaking with Gregory Shepard, the entrepreneur behind "The Startup Lifecycle" and the founder of the Startup Science platform. Gregory's research-driven insights offer a clear and practical roadmap that challenges the myths that have surrounded startup culture for decades. In our conversation, Gregory shared how his five-year research project revealed why so many startups fail and what can be done to reverse that trend. With data showing that 47.1 percent of startups fail within the first 18 months, Gregory highlights the critical importance of getting the earliest decisions right. Overvaluation, misunderstanding capital needs, premature scaling, and neglecting to consider an exit strategy from the start are some common missteps he passionately helps founders avoid. Gregory also discussed the seven stages of the startup lifecycle he created, paying particular attention to the often overlooked stages of standardization and optimization. Rather than rushing from product development to rapid growth, he emphasizes the need to stabilize and streamline operations first to ensure that scaling brings real profitability, not just top-line growth. This mindset shift alone could dramatically alter the success rate of new businesses. Beyond the book, Gregory has built the Startup Science platform, a comprehensive ecosystem designed to give founders access to mentors, investors, grants, classes, and curated resources all in one place. It is not just about reading a book or attending a workshop. It is about systematically embedding success principles into every aspect of the entrepreneurial journey. We also talked about the current startup climate and why economic downturns often lead to a surge in entrepreneurial activity. Gregory's advice is simple yet powerful: bunker down, stay focused, and view this period as an opportunity rather than a barrier. Investors still back good companies even when the broader environment feels uncertain. Throughout our conversation, Gregory's passion for supporting marginalized entrepreneurs and his commitment to the social and environmental impact of startups shone through. His belief that entrepreneurship is a true driver of global progress resonated deeply with me. Every aspiring founder can learn from their structured approach to resilience and success. For those curious about the real factors behind startup success, I highly recommend checking out "The Startup Lifecycle" and exploring the resources available at GregoryShepard.com and StartupScience.io. If you are serious about your entrepreneurial dreams, this is one conversation you cannot afford to miss.

How can computer vision and AI reshape the future of coaching, player development, and fan engagement in sports? In today's episode of Tech Talks Daily, I sit down with Lauren Pedersen, CEO and co-founder of SportAI, to explore how AI brings advanced sports analysis to athletes and coaches everywhere, not just to elite professionals. Lauren shares the inspiring journey that led her from New Zealand to Norway and from NCAA Division 1 tennis player to tech entrepreneur. SportAI is leading a movement to democratize access to professional-grade coaching tools, offering real-time tactical and technical analysis in racket sports like tennis, paddle, and pickleball. Using computer vision to track body movement and ball contact points from video alone without the need for wearables, SportAI delivers data-backed insights directly to coaches and players through integrations with camera-enabled courts and coaching platforms. We also dive into how SportAI's technology serves sports organizations, academies, equipment brands, and broadcasters, providing valuable performance data and creating new revenue streams for local clubs. Lauren talks about the balance between AI and human coaching, how AI enhances but never replaces the coach's role, and why social engagement and player empowerment are at the heart of this sports technology evolution. Lauren's vision stretches beyond racket sports, hinting at future expansions into golf, basketball, and baseball, wherever repetitive motion training can benefit from biomechanical analysis. As the sports world embraces AI and camera technology at scale, what does this mean for the future of training, competition, and how athletes of all levels experience the game? Tune in to learn how SportAI makes advanced sports insights accessible to all and what lies ahead for this exciting intersection of sports and technology.

In this episode of Tech Talks Daily, I'm joined by Sunil Singhvi, Head of Arts & Culture at TriliTech, the London-based blockchain hub helping shape the future of digital experiences through the Tezos ecosystem. Sunil brings a rare blend of deep tech, culture, and media expertise, having held senior roles at Twitter, Instagram, and Rarible before joining Trilitech. His mission? To explore how blockchain isn't just about tokens and ledgers but about real human connection, particularly between creators, brands, and their communities. What stood out in our conversation is how Sunil views blockchain as a vehicle for restoring creative autonomy and rebuilding trust in the creator-fan relationship. Through compelling examples like Manchester United's Fantasy United game and McLaren's collectible-driven fandom, we explore how Tezos enables ownership, co-creation, and authentic engagement that outpaces traditional social platforms and algorithms. We unpack the evolution of NFTs, moving beyond the speculative bubble of the past into more grounded use cases that offer tangible benefits. From supporting emerging artists through royalty-respecting marketplaces like objkt.com to enabling fans to co-create digital artwork through platforms such as editart.xyz, the conversation highlights a meaningful shift in how digital creativity is produced and experienced. Sunil paints a future where fans become collaborators and artists regain long-lost visibility into who their supporters truly are. We also reflect on the power of community, where smaller and more engaged groups increasingly matter more than vast but disengaged audiences. And perhaps most importantly, we explore what happens when creative expression is no longer dictated by opaque systems but driven by transparent, decentralized tools. Could blockchain finally deliver on the promise of a fairer and more inclusive creative economy? And if so, how can artists, brands, and everyday users participate in this movement without repeating the missteps of earlier digital revolutions? Let us know your thoughts. Could Web3 be the reset button creative industries have been waiting for?

In today's episode, I sat down with Mary Hamilton, Global Lead for Accenture's Connected Innovation Centers, to explore how the landscape of artificial intelligence is shifting. As we mark the 25th anniversary of Accenture's Technology Vision report, this year's insights reveal a profound transition into an era of AI-powered autonomy—reshaping how enterprises operate and how people and technology work together. Mary took us inside the key findings from the Tech Vision 2025 report, which is centered on the growing role of AI as a true partner rather than just a tool. From acting as a co-developer to becoming a brand ambassador and even powering robotics in the physical world, AI is on a fast trajectory toward becoming a foundational layer across every business function. However, Mary made it clear that technology alone isn't enough. Without trust in the systems being built, none of this innovation will land as intended. As she shared, building confidence in AI must be both cognitive and emotional—leaders must ensure that AI systems behave in expected, transparent ways and that people feel confident in their interactions with them. We also discussed how enterprises can harness what Accenture calls "cognitive digital brains" through multi-agent systems that enable intent-driven rather than instruction-led technology. Mary unpacked how these architectures, combined with AI platforms like GenWizard and SynOps are already transforming how companies create, operate, and innovate. We explored how brands can differentiate themselves in an AI-first world, where intelligent systems increasingly mediate customer interactions. She explained that one of the most significant risks is that ever sounds sound the same unless companies inject their values and personality into their AI experiences. We also touched on the rise of general-purpose robots, which have gained specialist capabilities and brought flexibility to logistics and manufacturing. Through examples with companies like KION and Schaeffler, Mary described a future where AI-enhanced robots work alongside humans in more agile, adaptive ways Finally, we tackled the human side of adoption. Mary shared why upskilling employees, giving them time to experiment, and aligning culture with AI goals are vital for lasting impact. Measuring success in this space requires more than cost savings or productivity gains. Ethical compliance, trust-building, and workforce empowerment are also essential signals that businesses are moving in the right direction. So, what does it take to turn AI from a buzzword into a practical driver of reinvention? How can leaders build a digital foundation ready for a future defined by autonomy and intelligence? Tune in to hear how Accenture is answering those questions—and helping the enterprise world do the same.

What does it mean to be a digitally engaged customer in 2025? That question sits at the heart of my conversation with Kim Storin, Chief Marketing Officer at Zoom. Just two days into her role, Kim brings a fresh perspective shaped by decades of experience and a track record of building and transforming iconic brands. She joins me to discuss the evolution of Zoom, the changing expectations of modern customers, and how the CMO role is being redefined in an era of AI-powered transformation. In this episode, Kim shares how Zoom is expanding far beyond meetings. Most people know Zoom for its video conferencing, but the platform now includes capabilities across events, webinars, contact center, email, scheduling, and employee engagement. Zoom is evolving into a complete communications and collaboration platform, and Kim offers insight into how her team will help shift perception while staying laser-focused on customer outcomes. We explore the shift from performance-heavy marketing to a more balanced approach that re-centers brand, storytelling, and product alignment. Kim emphasizes how the modern customer prefers to research independently, often completing most of their journey before ever engaging with a salesperson. This makes marketing more critical than ever, requiring clear, relevant messaging across every touchpoint. She also highlights the need to improve self-service experiences, especially as more enterprises seek the right balance between automation and human connection. Kim offers thoughtful insights on integrating AI in marketing, not as a replacement, but as a superpower. From content development and competitive analysis to strategic planning, she shares how her teams are already using generative tools to enhance productivity and creativity. This episode is packed with real-world observations on digital transformation, customer engagement, and the changing dynamics of marketing leadership. Whether you're a founder, marketer, or tech leader navigating the future of work, this conversation with Zoom's new CMO will give you ideas to reflect on and strategies to explore. How are you evolving your approach to marketing in a digital-first world?

What does it really take to modernize an enterprise in a world of constant disruption, increasing AI capabilities, and evolving customer expectations? In this episode of Tech Talks Daily, I sit down with Rajsekhar Datta Roy, Chief Technology Officer at Sonata Software, to explore how modernization engineering and responsible AI adoption are reshaping business transformation strategies. Raj brings decades of experience to the conversation, guiding organizations through the complexities of aligning technology with business value. We begin by unpacking what modernization truly means in today's environment. Rather than a single event, Raj explains how modernization is a continuous process that blends operational efficiency with agile frameworks and a readiness to adapt to future technologies like AI. My guest shares Sonata Software's structured approach to modernization, designed to generate efficiency from existing systems and redirect those savings into smarter, faster innovation cycles. We also explore the growing role of generative AI in digital transformation. Raj outlines the importance of moving beyond surface-level applications, advocating for a deeper integration of AI into reimagined business processes. He discusses Sonata's responsible-first approach to AI, including its governance framework and platform-level deployment strategy that ensures secure and ethical implementation. The result is not only a future-ready enterprise, but one that can deliver measurable value through better customer experiences, faster decision-making, and scalable AI adoption. As we zoom out, Raj highlights key ecosystem shifts, such as the growing importance of cross-industry collaboration and transforming customer expectations in the age of intelligent agents. He also offers advice on how to modernize without disrupting core systems, emphasizing the value of continuous learning, hands-on experimentation, and practical frameworks that reduce time to impact. If your organization is navigating digital transformation or exploring responsible AI deployment, this conversation offers both a strategic lens and real-world examples to help you move forward with clarity. How are you preparing your technology stack and business processes for what comes next? Let's continue the conversation.

With over 100 million packages recycled since its launch in 2019, Bower has proven that incentivizing people with real-world rewards can significantly increase recycling rates without building new infrastructure. From barcode scanning to AI-powered image recognition, the Bower app empowers users to recycle all types of packaging and earn rewards simply by dropping items into ordinary recycling bins. It's simple, scalable, and working across more than 170 countries. Berfin Mert, co-founder and COO of Bower, explains how their latest innovations now detect items without barcodes, such as coffee cups, cigarette butts, and batteries. She shares how AI-driven guidance has led to a 32% improvement in sorting rates, and why location-based data is key to building smarter, more responsive recycling systems. We also discuss the realities of building a circular economy, the growing role of brands like Nestlé and Varta, and why a purely sustainable pitch isn't always enough to bring companies on board. Berfin's perspective on bridging environmental goals with business realities makes this conversation stand out. She talks openly about expanding their value proposition to include marketing insights and loyalty tools, making the platform attractive to both eco-conscious users and revenue-driven brands. Toward the end of our chat, Berfin opens up about her own journey, crediting her brother and co-founder as the person who inspired her to take the leap into entrepreneurship. It's a grounded, honest look at innovation, impact, and the people who help bring both to life. This episode offers a fresh, practical perspective if you've ever wondered how small tech-driven actions can influence global sustainability. Could your packaging be worth something more? Let's find out together.

Here's the thing: we all heard Sundar Pichai say that the easy wins in AI have faded and that we may see fewer headline‑grabbing releases from the big players over the next year. That comment feels like a red flag for momentum, but I see it as a green light for action. In this episode, I chatted with Rahul Pradhan, VP of Product and Strategy at Couchbase, about how teams can take advantage of this pause to move projects from simple experiments into solid, production‑ready services. I ask why many organizations hesitate to send their data to public AI endpoints. Rahul explains that when you've invested years building data platforms, handing over your proprietary information—even in encrypted form—can feel like handing over the keys to your kingdom. He walks us through how running models inside your security perimeter keeps private data safe and brings up model accuracy since you can tailor inputs and scrub out noise before it ever reaches the inference engine. Next, we tackle the question of stability. Companies often assume that the path to a live service is straightforward once a pilot works. Rahul warns that managing GPUs, orchestrating models, and serving them at low latency all require skill sets that live at the crossroads of ML engineering and traditional software development. We round out our conversation by shifting focus from tools to teams. Technology alone cannot carry an AI initiative. We need leaders who set a clear vision, data stewards who govern every data flow, and developers who feel as comfortable writing database queries as they define training pipelines. Rahul offers thoughtful advice on building that culture and shares examples of industries—healthcare, financial services, and retail—where the most far‑reaching uses of AI are taking root. If you're wondering how to push your proof of concept into a robust service that customers depend on, this episode is for you. I promise you'll come away with ideas you can apply tomorrow and a fresh view of why a little breathing room in AI releases can become the launch pad for your subsequent big success.

In this episode of Tech Talks Daily, recorded live at Team '25 in Anaheim, I sit down with Jamil Valliani, Head of AI Products at Atlassian, to unpack the momentum behind Rovo, Atlassian's bold move to reimagine collaboration through generative AI. But this conversation goes far beyond product features. It offers a glimpse into how AI is reshaping teamwork, decision-making, and even company culture. Jamil explains how Rovo brings together enterprise-grade search, secure contextual chat, and a new Agent Studio designed to help anyone, from engineers to HR teams, build their own AI teammates. Perhaps most notably, all of this is being rolled out at no additional cost to Atlassian's paid users. That shift in accessibility marks a clear intent to drive meaningful adoption, not just feature excitement. We explore why 2025 is being tipped as the year of the AI agent, and how Atlassian is helping businesses move beyond overwhelm and into action. What stands out is how teams are using Rovo not just to save time but to remove the friction that clogs up workdays. Think triaging support tickets, updating status reports, or turning customer insights into ready-to-execute tasks. These are no longer chores left to team members; they are responsibilities shared with intelligent, learning agents that work alongside them. Jamil also shares some revealing stats. Customers are already seeing up to 2x return on investment, saving over 100 minutes a day, and 85 percent say the quality of their work has improved. That time and mental clarity is giving teams space to experiment, adapt, and create. So, where should you begin if you're starting your AI journey? And what does it take to build a culture where AI is embraced not just as a tool, but as a catalyst for better work? Tune in, and let us know what your AI-powered future looks like.

What does it take to lead with empathy in a world where AI transforms our work? In this episode, I sit down with Avani Prabhakar, Atlassian's Chief People Officer, to discuss how the company is creating a people-first culture while embracing rapid innovation. Avani shares how Atlassian is approaching AI not just as a technology shift, but as a mindset shift. When teams see AI as a collaborator instead of a task bot, 90 percent say it improves the quality of their work. That's not a statistic about productivity. It's a signal that mindset makes a measurable difference. We explore how leaders can support that shift. It starts with putting people first and using AI to free up time for creativity and deeper thinking. It also means giving teams permission to experiment, learn from failure, and figure out how these tools fit into their day-to-day work. And it includes being transparent about your own journey. What are you using? What's working? What lessons can others borrow? Avani also gives us a look at how Atlassian is rethinking performance and growth in a distributed world. Flexibility, trust, and curiosity are the new foundation for high performance, and the people function is now more connected than ever to the wider business strategy. If AI is going to be a part of every team's toolkit, how do we help people feel confident using it? And what kind of leadership does this moment call for? Join the conversation and let us know what you think.

What happens when tools like Jira, Confluence, Loom, and AI-powered agents come together under one unified strategy? At Team 25 in Anaheim, I sat down with Sanchan Saxena, Atlassian's Head of Product for Work Management, to explore the company's new Teamwork Collection and what it means for the evolving nature of collaboration. With leadership experience at Coinbase, Airbnb, Instagram, and Microsoft, Sanchan brings a pragmatic lens to building products that meet teams where they are. In our conversation, we unpack the thinking behind the Teamwork Collection, a curated set of Atlassian tools designed to help teams work more seamlessly while delivering real, measurable outcomes. This isn't about adding more tools to the stack. It's about reducing the noise and giving teams a single, integrated space to plan, document, and communicate with clarity. We also explore how AI is being used to reduce manual overhead, surface relevant information faster, and make daily tasks feel less like busywork. Sanchan shares practical examples of how companies are already using these tools to boost productivity, make meetings more actionable, and give teams back valuable time. For leaders focused on change management or wrestling with tool adoption, there are actionable insights here on overcoming cultural friction and designing for long-term success. Recorded live at Team 25, this conversation reflects a broader shift in how work is organized and supported. Whether you're in IT, product, operations, or leadership, this episode offers a look at how Atlassian is building for the future of work—one where humans and AI collaborate without the chaos. How are you designing your workflows to stay ahead of that curve? Let's continue the conversation.

What does it really take to build a software startup that doesn't crash before it can fly? In this episode of Tech Talks Daily, I sit down with David Hirschfeld, founder of Tekyz Inc., a software veteran who's spent over 35 years working across more than 90 startups. From his early days studying physics at UCLA to becoming the top national salesperson at Computer Associates, and later founding and selling his own successful software company, David has seen the full arc of startup life—success, failure, and the lessons in between. In our conversation, David unpacks the patterns he's observed over decades in the field and the epiphany that led him to create the "Launch 1st Method." Rather than falling into the trap of building first and validating later, David's approach challenges founders to prove product-market fit and generate real revenue before a single line of production code is written. He shares how this model not only reduces time, cost, and reliance on outside investment, but also offers a better chance of startup survival by confronting real-world customer demand from day one. We also explore how generative AI is reshaping software development, both in terms of speed and in shifting user expectations. David explains which areas of software development are accelerating most, where AI still struggles, and why even the best tools can't substitute for deep customer insight and thoughtful architecture. He also breaks down the artifacts that distinguish exceptional development teams—from weekly status reports to estimation accuracy—and how these practices shape delivery quality and team alignment. But perhaps most importantly, David offers a grounded look at what makes founders succeed. He emphasizes the value of falling in love with a problem, not a product idea, and staying relentlessly focused on understanding customers and their willingness to pay. Whether you're just starting out or rethinking your strategy, this episode delivers practical insights on how to derisk innovation, build smarter, and stay resilient in a fast-moving AI era. Are you building what people need, or what you hope they want? Let's explore that further.

What happens when one of the world's most loved productivity tools decides to reinvent itself for the age of AI? At Team 25 in Anaheim, I sat down with Gaurav Kataria, Head of Product for Trello at Atlassian, to unpack the biggest release in Trello's history and what it means for individuals and teams navigating the chaos of modern work. Gaurav describes the new Trello as "an AI-powered to-do list," built not to replace project management tools like Jira but to complement them—especially for those personal tasks, scattered action items, and mental notes that get lost in a sea of email, Slack messages, and SaaS app notifications. With half a million users opting into the beta within 48 hours of launch, it's clear that the new direction is resonating. In our conversation, we explore how Atlassian is using AI to enhance, not overwhelm, individual productivity—by capturing inputs from everywhere, organizing them intelligently, and helping users block time visually with integrations into Google and Microsoft calendars. This isn't about automating your life; it's about giving you clarity and control without friction. We also talk about how Trello remains deeply personal. From list colors to card covers and mobile widgets, the design philosophy centers on reducing cognitive load and sparking focus. Trello isn't trying to be a super app. It's trying to be the app that respects your mental model, works the way your brain works, and empowers you to get meaningful work done on your own terms. If you're overwhelmed by task sprawl or skeptical of AI's growing role in daily workflows, this episode offers a grounded look at what thoughtful, user-centered innovation looks like in action. How do you strike the balance between simplicity, automation, and human creativity? Let's explore that together.

What happens when four decades of hands-on engineering experience meet today's fast-moving AI and open-source ecosystem? In this episode of Tech Talks Daily, I sit down with Paula Paul, Founder and Distinguished Engineer at Greyshore, to explore that intersection. Paula began her tech career in the early 1980s writing code for IBM mainframes and has since become a trusted voice in enterprise modernization, cloud adoption, and open-source governance. Today, she advises organizations on how to build with confidence in an era defined by complex software supply chains, generative AI, and evolving SaaS models. We recorded this conversation during a time when many organizations are feeling the pressure to adopt AI and modernize legacy systems, but struggle with where to begin. Paula offers grounded insights on how to break down replatforming into value-driven streams and why a "big bang" transformation approach is often more risk than reward. She also talks about the critical role of open source in business today—not just from a tooling standpoint, but in terms of responsibility, transparency, and community. Paula's perspective is refreshingly practical. She believes AI is a natural evolution of decades of computing and storage expansion but urges companies to start with targeted experiments and thoughtful team collaboration. She also shares her experiences as a woman in tech since the 1980s, reflecting on what's changed and what hasn't and how leadership dynamics continue to shape opportunities for women in the industry. Beyond the code, Paula draws a fascinating parallel between music and technology. As a board member of the Brookline Music School and an oboe and English horn student, she explores how musical thinking can enhance software development's rhythm, structure, and leadership. If you're navigating modernization, curious about AI's role in development, or wondering how to make open source work for your organization—technically and strategically—this episode has something for you. How are you balancing technical ambition with long-term value? Let's continue the conversation.

What does it really mean to build software with joy? At the Team 25 event in Anaheim, I had the opportunity to sit down with Rajeev Rajan, CTO of Atlassian, to explore how one of the world's most influential engineering organizations is redefining developer experience from the ground up. Rajeev shares how developer joy became a guiding principle for Atlassian, not as a feel-good initiative but as a core driver of performance and innovation. Rather than focusing solely on velocity or throughput, Atlassian measured how productive developers felt in their codebases. That metric has now improved from 49 percent to 75 percent, thanks to a deliberate strategy built on three pillars: better tools, stronger engineering culture, and empowered teams. We also dive into how this cultural shift helped accelerate the delivery of Rovo, Atlassian's most ambitious AI product to date. Built-in record time, Rovo didn't emerge from a top-down push but from an environment where engineers were supported to move fast without cutting corners. That includes training internal teams through AI School, rolling out dev agents, and prioritizing transparency over automation for automation's sake. Rajeev also reflects on how India has become a global engine for AI and software development and why Atlassian invests in its global teams with the same level of trust and ownership as any other location. From ship-it hackathons to hands-on leadership and a grounded view of where AI helps and where it still falls short, this conversation highlights what it takes to build modern engineering teams that are both productive and fulfilled. So, if you're building AI strategies, leading engineering teams, or rethinking how to scale innovation responsibly, what would change if developer happiness were your benchmark?

What if most product launches fail not because of bad ideas—but because of broken processes? In today's episode of Tech Talks Daily, I'm joined by Stuart Jackson, Vice Chair of L.E.K. Consulting and co-author of the forthcoming book Predictable Winners (Stanford University Press, 2025). Stuart brings nearly four decades of experience in strategic growth and innovation, and his insights offer a much-needed reframe for businesses navigating the high-stakes world of new product and service development. We sat down to explore a topic many leaders shy away from: why 70–90% of product launches still miss the mark. Stuart breaks down the structural weaknesses that often derail innovation and explains why relying on gut instinct is no longer enough. Instead, we discuss how a rigorous, data-backed approach—augmented by AI—can dramatically reduce the risk profile of innovation while improving speed, accuracy, and return on investment. Stuart shares how leading organizations are integrating AI into every phase of their innovation pipeline—from idea screening and predictive analytics to launch planning and ongoing iteration. He outlines the rise of long-horizon thinking and how AI is enabling companies to identify emerging demand signals well before the competition. What I found particularly refreshing was Stuart's take on what top innovators do differently. It's not just about having better ideas—it's about building the right systems. That means empowering cross-functional teams, systematically disaggregating risk, and knowing when to pivot versus when to persevere. This conversation isn't about theory. It's a pragmatic look at how to move from product guesswork to predictable success—whether you're building in-house or buying through M&A. For founders, product leaders, and anyone trying to modernize their innovation model, this episode offers grounded advice and a clear framework that you can start applying today. How are you thinking about AI as a tool for risk reduction in innovation? Are your product strategies built for speed or sustainability—or both? Let me know what you think.

At Team '25 in Anaheim, I had the unique opportunity to sit down with Stan Shepard, General Counsel at Atlassian, for a conversation that pulled back the curtain on how legal and technology are intersecting in the age of AI. Stan's journey from journalism to law to shaping legal operations at one of the world's most forward-thinking companies is as fascinating as it is relevant. What emerged from our discussion is a clear signal that legal teams are no longer trailing behind innovation—they're often at the front of it. Stan shared how Atlassian's legal function achieved 85 percent daily usage of AI tools, including the company's in-house assistant, Rovo. This is remarkable when compared to the industry norm, where legal teams typically lag in AI adoption. Instead of resisting change, Stan's team leaned into it, focusing on automation for repetitive tasks while reserving high-value thinking for their legal experts. We explore Atlassian's responsible tech framework, their principles around transparency and accountability, and how these inform product development from day one. Stan also walked me through how Atlassian is navigating the emerging global regulatory landscape, from the EU AI Act to evolving compliance in the US. His insights on embedding legal counsel directly into product teams, rather than operating on the sidelines, reveal a model of collaboration that turns risk management into a growth enabler. For legal professionals, compliance leaders, and tech decision-makers wrestling with how to integrate AI responsibly, this episode offers a grounded, real-world blueprint. It's not just about mitigating risk—it's about building trust, preserving human judgment, and future-proofing your operations. If you're wondering what responsible AI adoption looks like at scale, you'll want to hear this one. So how are you preparing your legal and compliance strategy for the AI-powered workplace? Let's keep the conversation going.

What if cloud storage could be simple, transparent, and genuinely affordable? In this episode of Tech Talks Daily, I sit down with Tommi Kannisto, founder of Storadera a company based in Estonia that's redefining the way businesses approach object storage. I first met Tommi during the IT Press Tour in London, where Storadera's fresh perspective on S3-compatible cloud storage stood out for all the right reasons. In our conversation, Tommi shares the journey behind building a hyper-converged cloud storage platform that challenges conventional thinking. From eliminating hidden fees to maximizing performance on traditional spinning disks, Storadera is built around an ethos of doing more with less. The platform's architectural simplicity allows for efficient scaling, reliable performance with small files, and an operational model that avoids complexity by design. Tommi also walks us through how Storadera handles everything from data durability to sovereignty, with data centers already operating in Estonia and the Netherlands. With growing demand from regions focused on local control of data, we explore the opportunities emerging from geopolitical shifts and increasing global focus on sovereignty. Estonia's digital-first culture and its thriving startup ecosystem form the backdrop to this innovation, and we discuss how a small country has produced more than its share of tech unicorns. As we look to the road ahead, Tommi explains how AI might soon play a role in optimizing read and delete operations to push storage efficiency even further. He also touches on the growing interest in Storadera from companies seeking alternatives to US-based hyperscalers and how demand from across Europe is shaping their expansion plans. If you're exploring options beyond the cloud giants or curious about what's brewing in Europe's fast-growing tech scene, this episode offers a fresh, founder-led view of the storage market. Let me know what resonates with you. Are you considering new storage strategies in light of data locality or cost pressures? I'd love to hear your thoughts.

What if managing databases on Kubernetes didn't require a team of specialists or endless configuration? In this episode of Tech Talks Daily, I sit down with Tamal Saha, founder and CEO of AppsCode, to explore how his team is building a more intuitive, scalable, and enterprise-ready approach to Kubernetes-native data management. Recorded during the IT Press Tour in London, this conversation traces Tamal's journey from Bangladesh to Google, and ultimately to launching AppsCode in 2016. He shares how early experiences with Google's internal systems helped shape his vision for a cloud-native data platform built for modern application environments. What began as an open-source passion project has evolved into a comprehensive enterprise suite that includes solutions like KubeDB, Stash, Voyager, and KubeVault. We discuss the operational realities of managing databases in Kubernetes—from simplifying provisioning and backups to solving problems around TLS management, multi-tenancy, and even secret rotation. Tamal outlines the benefits of a Kubernetes-native architecture for platform engineers, DevOps teams, and developers who want to deploy faster, automate more, and keep full control over their environments. With real-world insights from enterprise deployments, including large-scale telcos modernizing their infrastructure, Tamal explains how AppsCode is helping organizations move from ticket-based database provisioning to true self-service. He also looks ahead to what's coming next, including support for vector databases, AI-powered provisioning interfaces, and deeper integrations with open telemetry and observability tools. Whether you're running stateful workloads in Kubernetes today or exploring how to modernize your data layer, this episode is packed with insight into building platforms that work with developers, not against them. So, is it time to rethink your approach to data in the cloud-native era? Let me know what you think.

What happens when the need for rapid AI innovation runs up against the growing pressure for trust, accountability, and compliance? In this episode of Tech Talks Daily, I sit down with Mrinal Manohar, CEO of Prove AI, to explore how risk management can accelerate rather than hinder AI deployment. Mrinal shares how Prove AI is helping organizations build trust into their AI systems from the start. At a time when businesses are moving AI models into production, yet often lack visibility or safeguards, Prove AI offers a solution grounded in transparency and automation. Their approach uses distributed ledger technology to create tamper-proof audit trails for AI models. This allows teams to focus on innovation while having the infrastructure in place to meet evolving standards and regulatory demands. We discuss why traditional monitoring techniques fall short in an AI context, especially as models become more complex and decisions happen in real time. Prove AI's infrastructure is designed to support continuous risk mitigation. By recording every event and decision with cryptographic certainty, they make it possible to prove safety, compliance, and responsible use without relying on labor-intensive manual audits. Mrinal also explains how Prove AI's upcoming GRC product aligns with ISO 42001 and helps companies stay ahead of regulatory expectations. Whether you're deploying AI in customer service, manufacturing, or high-risk environments, the platform ensures clear oversight without disrupting speed or agility. This conversation covers practical examples of AI risk in action, from automated railway inspections to drive-through ordering systems. We also explore how distributed ledger technology is helping redefine AI governance, offering companies a way to move fast with confidence. If you're scaling AI and wrestling with risk, compliance, or trust, this episode will give you a fresh perspective on how to build guardrails that support growth—not slow it down.

What if the way we work could finally match the way we want to work? At Atlassian's Team '25, that vision is no longer a distant ideal. In this special episode recorded live from the event, I sit down with Anu Bharadwaj, President of Atlassian, for an in-depth conversation about the future of collaboration and the company's newly formalized System of Work. Anu offers a behind-the-scenes look at how Atlassian is rethinking productivity through a new lens. We discuss how the System of Work unifies teams, tools, and data to drive meaningful outcomes instead of isolated wins. Anu explains how this framework was designed to move beyond conventional work management tools, helping teams focus not just on doing more, but on achieving more together. One of the standout innovations is the Teamwork Graph. Built to provide context across tools and departments, it connects strategy to execution with clarity. We explore how this visibility allows leaders to uncover bottlenecks, align resources, and connect the dots between business goals and day-to-day work. It's about making the invisible work visible and measurable. We also dive into Rovo, Atlassian's new AI teammate designed to elevate rather than replace human contribution. Anu shares how AI tools are being developed to reduce cognitive load, eliminate friction, and give people more time to focus on what truly matters. By embedding intelligence directly into the workflow, Atlassian is helping organizations reduce the time lost searching for answers and navigating silos. For leaders looking to modernize their operations, Anu outlines where to start and what to watch out for. Whether you are overseeing enterprise transformation or leading a fast-moving team, this conversation provides a practical view into how the Atlassian platform is helping organizations unlock better outcomes. What resonated most for me was the shift from chasing productivity to enabling performance. Atlassian is not just enhancing collaboration—it's helping reshape how teams think, operate, and scale. If you're curious about the System of Work, the Teamwork Collection, or what was unveiled at Team '25, this episode is for you. It's a glimpse into the future of work that prioritizes people, aligns efforts, and enables continuous learning. Let me know what you think. How are you planning to turn insights into action within your team?

In this episode of Tech Talks Daily, I sit down with James Smith, who leads ThoughtSpot's business across EMEA. With over 15 years in the analytics space, James shares how AI is shifting the way organizations use data, and why that change is not just about technology, but also about mindset and culture. James explains how ThoughtSpot is helping businesses move toward a more autonomous model, where AI-powered tools handle repetitive queries and free up analysts for more strategic work. He shares how ThoughtSpot's "Spotter" tool enables business users to ask and answer their own data questions, helping to reduce the bottlenecks that many central data teams face. But this isn't about removing people from the process. It's about enabling better collaboration between AI and human decision-makers, where transparency and context guide smarter actions. We also talk about ThoughtSpot's internal motto, "2% done," and how that mentality drives continuous innovation. In a world that's changing rapidly, it's a reminder that staying curious, challenging assumptions, and building from first principles can unlock new levels of performance. As demand for AI-powered insights increases, James highlights the growing importance of strong data foundations. It's not enough to just add AI on top. Organizations need to invest in data quality, governance, and flexible platforms that support users at every level of maturity. From enabling better business decisions to giving non-technical users easier access to insights, James offers a grounded view of what AI can really deliver today. If you're working to build a data-driven culture, or looking to put more power in the hands of your teams, this conversation offers practical ideas to guide that transformation. How are you preparing your business for this shift in analytics? Let me know.

In this episode of Tech Talks Daily, I sit down with Marc Lueck from Zscaler to explore a security mindset shift that more businesses are beginning to embrace. The conversation revolves around the "Resilient by Design" principle, which encourages organizations to stop relying on reactive threat detection and start building systems that anticipate risk and limit impact from the outset. Marc explains how today's cyber landscape demands more than traditional firewalls and legacy systems. He breaks down why Zero Trust should no longer be seen only as a remote access solution, but as a consistent, context-driven access model for all environments. From on-premises communication to lateral traffic between applications, Marc outlines how this model helps reduce vulnerabilities and prevent attacker movement inside the network. We also dive into the challenges posed by AI-driven attacks, where phishing, malware, and reconnaissance are increasingly automated and customized to each target. With these tactics becoming more advanced, Marc stresses the importance of shifting away from pattern-based detection toward a strategy based on real-time context and intent. He shares insights into Continuous Threat and Exposure Management (CTEM), a new class of tools that help security teams understand where problems are likely to occur before they happen. This proactive focus is key to designing systems that are resilient under pressure, rather than relying on alerts after the fact. From his analogies of planning for hurricanes rather than rainstorms, to his thoughts on legacy systems and the future role of automation in threat response, Marc offers a practical look at what resilient infrastructure truly involves. So the question is, are your systems designed to recover and continue when something breaks, or are they waiting for the next emergency to arrive? Let's find out.

What if the internet could run fully encrypted computations without sacrificing performance or control? In this episode of Tech Talks Daily, I sit down with Yannik Schrade, CEO and Co-Founder of Arcium, to explore how confidential computing is reshaping the future of digital infrastructure. Arcium is building what Yannik describes as an encrypted supercomputer, a decentralized network that allows data to stay encrypted even during processing. This approach gives developers and organizations a way to build privacy-first applications across sectors like healthcare, finance, artificial intelligence, and government services. We talk through how Arcium leverages secure multi-party computation to make this possible and why that matters in a world where sensitive data is often a liability. Yannik explains how Arcium enables companies to collaborate without revealing proprietary data, and how it allows for mathematically provable trust in digital processes. From private order books in financial systems to AI models that train on encrypted health data, the scope of this technology is already expanding into real-world use cases. We also explore the importance of decentralization, not just as a technical feature, but as a way to reframe the conversation around digital sovereignty, compliance, and individual freedom. Yannik reflects on his own journey from app developer to cryptography leader, and how his background in computer science, mathematics, and law helped shape his vision for Arcium. If you're navigating challenges around data privacy, regulation, or AI ethics, or if you're curious about what confidential computing can unlock, this is a conversation that brings clarity to an area often clouded by hype. What would your organization build if privacy was no longer a limitation but a default capability? Let me know after you've listened.

I sit down with Chris Hewish, Chief Strategy and Communications Officer at Xsolla, and Lee Jacobson, Senior Vice President of Business Development for Web3 at the same company. Together, they share how Xsolla is helping game developers adapt to the rapidly shifting digital economy by bridging blockchain innovation with proven business models in the gaming world. Xsolla is no stranger to transformation. With over two decades of experience and more than 2,500 games monetized through its platform, the company is once again stepping into a leadership role—this time at the intersection of Web3 and gaming commerce. One of the headline announcements we discuss is the launch of Xsolla ZK, a new blockchain-powered solution built on ZKsync technology. It's designed to scale Web3 experiences in a way that's secure, accessible, and meaningful for developers and players alike. We explore the "digital backpack" concept that sits at the core of this initiative. This isn't just a marketing buzzword—it's a player-owned inventory system that gives gamers real control over their in-game assets. Whether it's transferring gear between games or monetizing collectibles in ways previously restricted by walled gardens, this feature signals a shift toward deeper engagement and lasting value. Chris and Lee also offer a behind-the-scenes look at how direct-to-consumer models like Xsolla's Web Shop are unlocking new revenue channels for developers. With a fee structure significantly lower than traditional app stores and tools for customized experiences, these platforms are helping studios build stronger relationships with their communities while boosting margins. Security, transparency, and compliance remain central to the conversation, especially as blockchain adoption grows. We also touch on identity protection through zero-knowledge proofs and what interoperability might look like in a future where players and creators collaborate across an increasingly open ecosystem. From creator monetization to the evolution of in-game economies, this episode is a must-listen for anyone watching the convergence of Web3, blockchain, and gaming.

What does it take to simplify the chaos of multi-vendor data protection while keeping sovereignty, scalability, and automation firmly in sight? In this episode, I'm joined by Thomas Bak, CEO of Auwau, to explore how his company's Cloud Utility platform is helping managed service providers and enterprise IT teams redefine control and efficiency. I had the pleasure of meeting Thomas at the IT Press Tour, where he shared not only the story behind Cloud Utility but also how Auwau is supporting white-labeling, API-first workflows, and fully integrated billing automation. This isn't about adding yet another tool to the tech stack. It's about building a self-service-first platform that acts as a single control point for complex, multi-tenant environments. Cloud Utility enables service providers and internal IT departments to operate with greater transparency and agility, from backup and object storage to role-based access and recurring billing. Thomas also opens up about why many customers still demand on-prem deployments, especially in sectors where data residency and control are non-negotiable. His perspective on how service providers can offer branded experiences for resellers while maintaining central governance is especially relevant in today's compliance-driven climate. We also discuss how Auwau's background as an MSP shaped its customer-centric approach to product development, and why flexibility across technologies like IBM Storage Protect, Rubrik, and Cohesity is baked into the product's core. If your business is struggling to scale its data protection offerings or looking for better ways to serve distributed teams and clients, this is a conversation you won't want to miss. How are you future-proofing your infrastructure without losing visibility or control? Let's explore that together.

What does it really take to expose the criminal underworld operating in the hidden corners of the internet? In this episode, I sit down with Dr. Gareth Owenson, Co-Founder and CTO of Searchlight Cyber, to uncover what's really happening on the dark web and how organizations can take action before threats escalate. Gareth has spent more than a decade researching the Tor network and advising governments, law enforcement, and the military on how to track criminal activity online. His work has moved from academia into frontline cybersecurity operations, leading to major breakthroughs including the takedown of a hacker group targeting a national government. We explore what makes the dark web attractive to criminal networks, how threat actors are evolving, and what defenders can do with early signals from hidden forums, marketplaces, and anonymized networks. Gareth explains how criminals are using Tor to traffic malware, trade stolen data, and build ransomware businesses, and why many organizations still overlook this part of the internet. Gareth also shares how Searchlight Cyber uses proprietary tools and research to monitor the deep and dark web, turning obscure activity into actionable intelligence for security teams and law enforcement. If you're responsible for protecting digital infrastructure and you're not factoring in the dark web, you're missing critical context. So how do you turn unseen risks into visible signals before they become full-blown attacks? Let's find out.

What happens when blockchain meets AI infrastructure at scale? In today's episode, I sit down with Gaurav Sharma from io.net to explore how a decentralized GPU network could reshape the future of machine learning, AI development, and compute accessibility. io.net has grown rapidly over the past year. With more than 325,000 verified GPUs already in its decentralized network, it's offering an alternative to the high costs and limitations of traditional cloud compute. What caught my attention is the platform's ability to reduce GPU costs by up to 90 percent, giving startups and researchers access to performance that would otherwise be out of reach. In fact, over 73 partners have already integrated io.net's infrastructure, helping drive month-over-month network earnings growth of nearly 60 percent. But this conversation goes far deeper than computing. Gaurav walks me through the vision of a more transparent, open, and incentive-driven AI development ecosystem. From its collaboration with OKX to power Web3 infrastructure for AI developers to enabling real-world applications like Zerebro AI agents, io.net is building a new paradigm for how infrastructure should work in the era of intelligent systems. We also explore the convergence of blockchain and AI and why this isn't just a niche Web3 experiment. It's about creating real incentives for data sharing, enabling collaboration across models, and removing bottlenecks in how builders access the tools they need. Gaurav also shares how the company is evolving from a computing network into a full-stack AI development platform, including tools for no-code agent creation. So, what will the next generation of AI applications look like when they're powered by a global, decentralized network instead of a handful of cloud giants? And how can developers take advantage of this shift today?

What happens when AI meets the human side of hiring? In this episode, I sit down with Rebecca Carr, CEO of SmartRecruiters, to unpack the shifting role of HR in a rapidly evolving talent landscape. With new research showing that 56 percent of leaders say talent acquisition has become significantly more challenging over the past five years, Rebecca offers a timely and thought-provoking perspective on how AI can help – and where it can't. We explore the tension between automation and human connection, and how organizations can strike the right balance to create meaningful candidate experiences without sacrificing speed or scalability. From improving candidate discovery and reducing administrative overhead to using AI to flag unconscious bias in job descriptions, Rebecca shares how SmartRecruiters is pushing the boundaries of what recruiting platforms can do. We also touch on the implications of generative AI, the importance of explainability in AI-driven decisions, and how HR teams can move from being transactional to truly strategic partners in business. As companies demand more from their hiring processes and the competition for top talent intensifies, the need for smarter tools – and smarter strategies – has never been greater. If you're in HR, talent acquisition, or simply curious about how AI is transforming the way companies hire, this episode offers both practical guidance and a look at what's next. What does it take to hire smarter, faster, and more fairly in 2025? Let's find out.

What happens when the hype around generative AI starts to mature, and businesses begin asking harder questions about performance, risk, and long-term value? In today's episode, I'm joined by Mike Mason, Chief AI Officer at Thoughtworks, to explore how 2025 is shaping up across the enterprise AI landscape—from the rise of intelligent agents to the growing traction of small, nimble models that prioritize security and specificity. Mike brings a deep, practical perspective on the evolution of AI inside complex organizations. He unpacks how AI agents are moving well beyond basic chatbots and starting to integrate into actual business workflows—performing as teammates that can reason, adapt, and even collaborate with other agents. We dig into examples like Klarna's workforce transformation and examine how this shift could play out across customer service, internal ops, and software development. We also look at what's fueling the boom in open source AI and how companies are navigating the balance between transparency, IP protection, and regulatory readiness. Mike shares why some financial services firms are turning to in-house fine-tuned models for greater control, and how open-weight and fully open-source models are starting to gain real ground. Another key theme is the momentum behind small language models. Mike explains why bigger isn't always better—especially when it comes to data privacy, edge deployment, and resource efficiency. He outlines where SLMs can outperform their larger counterparts and what that means for companies optimizing for security and speed rather than brute force compute. We also discuss Thoughtworks' forthcoming global survey, which reveals a growing divide in generative AI adoption. While mature players are building in bias detection and robust compliance frameworks, newer entrants are leaning toward fast operational gains and interpretability. This gap is shaping how GenAI projects are prioritized across industries and geographies, and Mike offers his take on how leaders can navigate both speed and safety. So, what role will explainability, regulation, and open ecosystems play in shaping the AI tools of tomorrow—and what should business and tech leaders be planning for now? Let's find out in this wide-ranging conversation with Thoughtworks.

What does it really take to implement generative AI in a way that balances innovation, governance, and long-term value? In today's episode, , I'm joined by Emma Irwin, Director of Sales Engineering at Dataiku. With a deep background in enterprise AI and experience supporting major organizations like AVIVA and the NHS, Emma brings a grounded, real-world perspective to one of the most hyped areas in tech today. While most businesses are ramping up GenAI investments, few have the processes, controls, or workforce skill sets needed to scale safely and effectively. Emma and I dive straight into the challenges that IT leaders are facing right now—from managing LLM usage and controlling cost, to building secure frameworks that actually reduce risk rather than amplify it. Emma unpacks the three key pillars every organization needs for sustainable GenAI success: access controls that keep your stack flexible, robust discovery mechanisms to document LLM usage across the enterprise, and value quantification to show the real return on AI initiatives. But what really stood out is the need for diverse teams and strong governance models to address bias in AI development. From sentiment analysis to internal chatbots and large-scale summarization use cases, Emma brings a mix of strategy and execution to the conversation. We also explore the importance of secure sandbox environments, the value of audit-readiness through documentation automation, and why it's time for every business to move beyond experimentation into a more structured, responsible phase of AI maturity. Emma is also a vocal advocate for women in tech and AI, and shares how mentorship, representation, and inclusive leadership can help shape a more equitable future for the industry. So what guardrails do you have in place for GenAI? Are you really ready to move from pilot projects to enterprise-scale implementations? This episode is packed with insights for anyone building, managing, or scaling AI across the enterprise.

What if your mobile app could detect bugs, fix UI inconsistencies, and spot user frustration before a user ever reports it? In today's episode, I sit down with Kenny Johnston, Chief Product Officer at Instabug, to explore how AI is reshaping the way developers build, test, and maintain mobile apps. Instabug is taking mobile observability to an entirely new level by developing what Kenny describes as "zero maintenance apps." Powered by on-device AI models, their platform can now detect subtle UX breakdowns, visual design flaws, and even frustration signals that wouldn't normally trigger crash reports. Whether it's an unresponsive button, a layout shift, or a broken navigation path, Instabug flags the issue, often before a user ever notices. Kenny shares how Instabug's approach to AI is helping development teams move faster and smarter, particularly in high-stakes environments like retail and e-commerce where performance peaks during events like Black Friday or Valentine's Day. Through real-time crash reporting, automated UI analysis, and deep session insights, developers can spot and solve problems that would otherwise get lost in a backlog or surface in app store reviews. We also explore the unique pressures of mobile development. With no quick rollbacks and high user expectations, developers need tools tailored to the realities of app store approvals, device fragmentation, and version-specific bugs. Instabug's platform brings together observability, feedback, and issue reproduction in a way that simplifies the mobile stack and accelerates release cycles. Kenny draws on his experience at GitLab to reflect on the need to consolidate tools and workflows in mobile development. He offers valuable insights for product leaders and mobile engineers on how to navigate change, evolve their approach, and stay curious in the face of constant technical demands. So how can your team shift from reactive debugging to proactive experience design? And are you really seeing all the issues your users encounter or just the ones they report? It's time to find out.

What happens when Microsoft joins forces with IGEL to reimagine the future of endpoint computing? In today's episode, recorded live at IGEL's Now & Next 2025 in Miami, I sit down with Scott Manchester, Vice President of Windows 365 and Azure Virtual Desktop at Microsoft. With decades of experience at the helm of virtualization and cloud innovation, Scott brings a grounded yet forward-looking view of how Microsoft is enabling businesses to adapt to the evolving demands of work. Our conversation explores how Microsoft and IGEL are working together to address real enterprise challenges—from simplifying endpoint management to ensuring high-performance, secure digital workspaces. We look at how Windows 365 Cloud PC and Azure Virtual Desktop are helping businesses embrace the cloud while navigating the transition to Windows 11. And we discuss the real-world implications of this shift, from extending the lifecycle of devices to increasing flexibility for IT teams and remote users alike. Scott also opens up about the industries that are leading in cloud workspace adoption—from healthcare systems like Baptist Medical Center to federal agencies and financial services—and how Microsoft is shaping its offerings to meet the distinct needs of these sectors. We unpack the unique advantages of IGEL's Linux-based OS, the growing role of zero trust architecture, and why seamless user experiences are no longer optional in the hybrid era. With new licensing models like Windows 365 Frontline Shared and deeper integration between Microsoft and IGEL, it's clear this partnership is more than technical alignment—it's a shared strategy aimed at delivering resilient, secure, and scalable digital environments. Whether you're planning your Windows 11 migration or just exploring cloud PCs as part of your future roadmap, this episode is packed with strategic insights from a tech leader who knows how to deliver results. What role will the cloud desktop play in your 2025 strategy?

What does bringing clarity and control to today's fragmented digital work environments take? In this episode, recorded live at IGEL Now & Next 2025, I sit down with Tommy Walker, Partner CTO at Omnissa, to explore the intersection of user experience, security, and operational simplicity in modern enterprise IT. With career-spanning roles at VMware, Citrix, and Cisco, Tommy offers a real-world perspective on navigating complexity while building meaningful solutions that work at scale. This is a conversation grounded in reality. We discuss how organizations can move beyond legacy infrastructure and simplify their digital workspace strategy without overwhelming users or IT teams. Tommy shares how Omnissa is helping enterprises shift from scattered tools and outdated workflows to unified, AI-informed platforms that boost both productivity and resilience. We also unpack the practical steps for tackling challenges like technical debt, the Windows 10 end-of-life transition, and rising pressure on IT to deliver more with fewer resources. Throughout the discussion, Tommy emphasizes the importance of partnerships—not just between vendors, but within the entire IT ecosystem—to deliver outcomes that matter. And yes, there's also room for a few lighter moments involving drones, endpoint telemetry, and the occasional geek-out over infrastructure design. But at the core of this conversation is a clear message: modern IT is about enabling users without compromising security and simplifying operations without losing flexibility. If you're rethinking your endpoint strategy, evaluating your hybrid work approach, or just trying to bring a little more order to the chaos, this episode will leave you with practical insights and maybe even a few new ideas for your roadmap. Are you ready to build a digital workspace strategy that actually works? Let's get into it.

What does it truly take to secure the edge of the enterprise in a multi-cloud, AI-driven world? At IGEL Now & Next 2025 in Miami, I sat down with Marissa Schmidt, Senior Director Analyst at Gartner, to unpack the future of endpoint computing and cybersecurity from a perspective rooted in deep research, hands-on insight, and strategic clarity. As hybrid work continues to scale and the cloud cements itself as the core of modern infrastructure, new demands are being placed on endpoint operating systems, access frameworks, and cloud security models. Marissa brings a clear-eyed view of what's working, what's changing, and what IT leaders need to start doing differently. In this conversation, we explore how AI is reshaping both attack and defense strategies, why the OS layer has become a strategic asset, and what Gartner is seeing in terms of the biggest shifts in cloud networking and endpoint security in 2025. We also dig into the principles behind zero trust, the realities of managing dozens of overlapping security tools, and how businesses can begin building more resilient, adaptive architectures—starting today. Marissa also shares insights from her keynote and the Women in Tech panel at IGEL Now & Next, including the importance of authentic leadership, being a continuous learner, and building a strategy that connects real-world data with future-ready infrastructure. Whether you're navigating cloud transformation, rethinking your endpoint strategy, or trying to make sense of the security demands brought on by AI, this episode offers a sharp, actionable look at where things are heading—and how to stay in front of it. Are your cloud and endpoint strategies built for what's next? Let me know your thoughts.

What does it really take to reimagine the future of endpoint computing? In this special episode recorded live from IGEL's Now and Next 2025 event in Miami, I sit down with Klaus Oestermann, CEO of IGEL, to explore how cybersecurity, digital workspaces, and user experience are being transformed at the edge. Klaus is no stranger to innovation, having spent decades in high-assurance security across critical industries, and now leading IGEL's mission to simplify, secure, and modernize how enterprises manage endpoints. Our conversation starts by unpacking the shift from traditional perimeter-based security models to a new way of thinking rooted in prevention. Klaus explains how IGEL's Preventative Security Model addresses modern threats by dramatically reducing the attack surface at the endpoint and flipping the conversation from detection and response to control and containment. With more organizations relying on hybrid work and SaaS-based applications, the endpoint has never been more critical—or more vulnerable. Klaus also outlines how IGEL OS is supporting everything from virtual desktop infrastructure to secure browsing, while enabling consistent user experiences across cloud, on-prem, and edge environments. But this episode isn't just about technology. It's about strategy. Klaus shares how IGEL is creating meaningful impact by extending device life cycles, cutting hardware replacement costs, and supporting sustainability goals. With Windows 11 upgrades looming and endpoint refresh cycles under pressure, IGEL presents a compelling alternative that balances performance with responsibility. We also dive into the role of AI, how it's reshaping device requirements, and what it means for endpoint security moving forward. And as IGEL expands its ecosystem and reveals over 20 new announcements at this year's event, Klaus offers a candid look into what's resonating with customers—and where the industry is headed next. So what will define your endpoint strategy in 2025? And is your organization ready to lead from the edge?

What's the return on your AI investment? In today's episode, I'm joined by Varun Bijlani, Global Managing Partner for Hybrid Cloud Services at IBM Consulting, to explore why 2025 is shaping up to be a pivotal year for IT leaders under pressure to deliver stronger, measurable outcomes from technology investments. While many IT projects have historically delivered modest returns, expectations are rising. With a growing number of executives focused on increasing ROI by 25 percent or more, the ability to connect AI efforts to real business value is becoming non-negotiable. Drawing on insights from IBM Consulting's latest book, The Great Tech Reset, Varun outlines how the shift from experimental AI projects to production-level deployment is exposing the cracks in outdated infrastructure strategies. He explains why many businesses are trapped in what he calls a hybrid by default architecture, and how that limits the potential of generative AI. Instead, he advocates for a hybrid by design approach, one that aligns cloud infrastructure with AI goals from the outset. We discuss the organizational mindset shifts needed to move from fragmented systems to intentionally built environments that scale with innovation. Varun also shares real-world examples of companies achieving returns as high as 3.3 times their investment through more intentional planning and execution. As IT leaders look to reset priorities for the year ahead, how can they build the kind of foundation that allows AI to thrive? And what steps can they take today to ensure their technology choices drive value, not just cost?

What can the UK learn from the Nordic approach to manufacturing—and how can technology play a central role in revitalising the sector? This week on Tech Talks Daily, I sat down with Simon Ranyard, Managing Director for Northwest Europe at Orange Business, to explore the strategic differences between two regions facing similar challenges but moving in very different directions. Simon brings a unique cross-regional view, overseeing Orange Business operations across the UK, Ireland, and the Nordics. While labour shortages and productivity declines are shared concerns, Simon explains why Nordic manufacturers have responded with long-term investments in digitisation and automation, creating not just gains in efficiency but also a rise in high-skill employment. In contrast, many UK firms are still defaulting to short-term headcount increases, missing the bigger opportunity. We discuss the data behind the divergence, including why Sweden has three times the robot density of the UK, and what that means for output and workforce transformation. Simon highlights how automation isn't about job replacement, but role elevation—moving people away from repetitive tasks and into positions that require critical thinking and collaboration with advanced tools. He also shares practical insight into how technologies like 5G, AR, and IoT are reshaping production environments, lowering operational costs, and helping companies stay competitive globally. With government-backed reskilling initiatives and AI now moving from theory to application, Simon makes the case for UK manufacturers to adopt a more strategic, future-facing mindset. If you work in manufacturing, policy, or are simply curious about how different regions are using tech to solve shared problems, this episode offers real-world perspective and tactical advice. What kind of investment decisions will define the next decade of UK industry—and can a mindset shift help close the productivity gap?

How do you turn AI investment into measurable outcomes, not just inflated expectations? In this episode, I'm joined by Dennis Woodside, CEO of Freshworks, to unpack how mid-sized businesses can move fast with AI, show results quickly, and stay competitive without enterprise-level complexity or pricing. Dennis shares how Freshworks is helping companies achieve real productivity gains and customer support improvements through accessible, enterprise-grade AI tools. With solutions that boost agent performance, reduce repetitive tickets, and deliver useful insights to managers, Freshworks is proving that you don't need to be a tech giant to see value from AI. We also explore the challenges that hold mid-market businesses back from adopting AI, and how Freshworks is helping them overcome barriers with tools that are fast to implement, easy to evaluate, and flexible enough to grow with the business. Dennis also reflects on what the industry can learn from customer case studies, including how one company achieved over 250 percent ROI and saved $100,000 annually by streamlining support with AI. If your business is exploring how to make AI work without long timelines or runaway budgets, this conversation offers a grounded view into what's working—and why. Are you measuring real return on AI in your organization, or just chasing the trend?

Why do so many businesses struggle to turn insight into impact? At the X4 Summit in Salt Lake City, I sat down with Adam Hagerman, UX Research Director at Indeed, for a refreshingly candid conversation about how his team has helped reshape the company's approach to research, collaboration, and decision-making. In a tech culture that values autonomy and individualism, aligning people around a shared understanding of user needs is no small feat—but it's exactly what Adam has been working on. In this episode, we unpack how Indeed built a shared research framework that breaks down silos, creates a common language, and encourages teams across the business to talk to one another in more meaningful ways. Adam shares how his team tackles the challenge of information overload by focusing on relevance over volume—and how measurement itself becomes a shared system of accountability across functions. We also discuss the evolving role of AI in research, including how Adam's team uses it to reduce cognitive overhead, accelerate workflows, and spark better questions. But perhaps most importantly, Adam talks about the mindset shift needed in times of rapid change—and why embracing uncertainty and remaining curious is more productive than clinging to old ways of working. Whether you're a UX leader, researcher, or business decision-maker looking to get more from your data, there's plenty here to reflect on. How do you ensure your insights aren't just collected, but acted on? How do you build trust in research across teams? And how can we all get better at asking, "What problem are we actually trying to solve?" Let me know what resonated with you. What challenges have you faced in translating research into action within your own organisation? I'd love to hear your thoughts.

How do we build high-performing teams in a world where colleagues might never meet face to face? At the X4 Summit in Salt Lake City, I caught up with two standout voices from Atlassian—Molly Sands, Head of the Teamwork Lab, and Emma Crockett, Head of People Insights. Together, they bring a rich mix of behavioral science, experimentation, and data-driven strategy to the future of work. In this episode, we unpack what it really takes to design distributed work environments that foster both productivity and connection. Molly shares how her team studies internal and external teams to understand what drives collaboration in a hybrid world, while Emma reveals how Atlassian turns insights into action by grounding people strategies in measurable outcomes. We talk about clear goal setting, the power of asynchronous communication, and how the physical workspace itself can evolve to support a flexible, purposeful culture. But this isn't just about metrics and models—it's about human connection. From a delightful experiment involving "Chief Vibes Officers" and quirky team questions, to Atlassian's scrappy and iterative approach to designing new ways of working, this episode offers real-world ideas for reimagining how teams collaborate. We also explore the pitfalls of defaulting to old habits like Zoom fatigue and information silos, and what it takes to fix them. As we touch on people analytics, the role of trust, and the impact of thoughtful measurement, Molly and Emma remind us that even with AI and automation in the mix, work is still about people. So, if your team is struggling with how to work better together—whether you're all remote, hybrid, or co-located—what lessons could you take from Atlassian's approach? Let us know your thoughts. How is your organisation adapting to the realities of modern teamwork?

What does it take to keep a 40-year-old brand rooted in nostalgia relevant in a rapidly evolving, tech-driven world? In this special episode recorded live from the X4 Summit in Salt Lake City, I sit down with Maggie Stafford, Vice President of People Insights at Hagerty, to explore how a company best known for classic car insurance has become a technology-enabled, community-powered lifestyle brand for auto enthusiasts. From cloud-based transformation to one-on-one customer experiences, Maggie shares how Hagerty is modernizing its approach to customer and employee engagement—while staying true to its mission to "save driving." We discuss the evolution of Hagerty's digital experience, including their $20 million investment into a modern tech stack, designed not only to improve operational efficiency but also to meet growing member expectations. Maggie also gives a behind-the-scenes look at how the brand's culture—one where employees learn to drive stick and take collector cars for a spin—shapes everything from customer service to product development. You'll hear how community remains the beating heart of the business, with more than 850,000 Hagerty Drivers Club members connecting at grassroots events and exclusive experiences like the Festival of the Unexceptional and Amelia Island Concours. We also explore how Hagerty is using data and insights to prepare for the future of car culture, at a time when automation, electrification, and driverless vehicles are becoming the new norm. So how does a brand that celebrates the visceral joy of driving stay relevant in an era of AI and autonomy? And what can other businesses—especially those outside the traditional tech space—learn from Hagerty's approach to transformation and loyalty? Tune in to find out, and don't forget to share your thoughts: how do you balance tradition with innovation in your business?

Can AI truly revolutionize customer experience, or is it just another overhyped tech trend? While most organizations recognize AI's potential, many are still struggling to scale AI beyond pilot projects. So, what's holding them back? In this episode, recorded live at the X4 Summit in Salt Lake City, I sit down with Isabelle Zdatny, Head of Thought Leadership at Qualtrics XM Institute, to explore the $860 billion opportunity AI presents for customer experience. We discuss why only 12% of organizations have a company-wide AI strategy, the disconnect between AI ambition and execution, and how companies can break free from what she calls "pilot purgatory." Key topics include: The three biggest ways AI will unlock business value—from productivity gains to revenue growth and operational efficiency. Why AI needs to be top-down and outcome-focused—not just a shiny tech experiment. The rise of Agentic AI—AI that doesn't just assist but autonomously manages entire workflows. How leading companies are using AI to predict and prevent customer churn, personalize interactions, and optimize operations. The biggest myths about AI in CX—and why you don't need perfect data to get started. As AI reshapes how businesses engage with customers, companies that act decisively and strategically will gain a significant competitive advantage. But will they move fast enough? Tune in to hear real-world insights, case studies, and expert advice from Isabelle on how businesses can turn AI potential into real impact—before their competitors do.

Many businesses have embraced automation, but disconnected systems and fragmented workflows still create inefficiencies. In this episode, I sit down with Charles Crouchman, Chief Product Officer at Redwood Software, to explore how organizations can build an automation fabric. a unified approach that connects processes across legacy infrastructure and modern cloud environments. Charles explains why automation fabrics matter, how businesses can identify the best processes to automate, and why a well-structured roadmap is crucial for long-term success. He also shares insights on industry trends, including the growing role of AI in automation and how Redwood's approach enables enterprises to scale with confidence. With Redwood's recent acquisition by Vista Equity Partners and Warburg Pincus, the company is poised for even greater innovation and expansion. We also dive into the future of automation, the balance between AI-driven decision-making and human oversight, and what businesses should consider when integrating automation across departments. Whether you're just beginning your automation journey or looking to refine your strategy, this conversation provides a practical guide to building a resilient, scalable automation framework. Could automation fabrics be the missing piece in your digital strategy? Tune in to find out.

When a cyber crisis strikes, leaders face intense pressure to make rapid decisions that can determine the fate of their organizations. In this episode, I sit down with Dan Potter, Senior Director of Operational Resilience at Immersive, to explore how leaders can effectively manage high-stakes cyber incidents. From major crises like MOVEit and Log4J to the evolving landscape of AI-driven threats, Dan shares practical insights on what businesses can learn from past events to strengthen their response strategies. We discuss the key components of a well-structured decision-making framework, how to maintain strategic focus under pressure, and why trust and psychological safety within teams are essential during a crisis. Dan also walks us through a checklist for effective leadership before, during, and after a cyber event, emphasizing the importance of continuous, hands-on training to build organizational resilience. With cyber threats becoming more sophisticated and unavoidable, organizations need more than just technical defenses—they need leaders who can navigate uncertainty and execute decisive action. Tune in to learn how to transform crisis management from a reactive scramble into a well-prepared, strategic response. Are today's business leaders truly ready for the next cyber crisis? Let's find out.

Online reviews shape consumer trust, but what happens when those reviews can't be trusted? In this episode, I sit down with Anoop Joshi, Chief Trust Officer at Trustpilot, to discuss the ongoing battle against fake reviews and the role of AI in both creating and detecting fraudulent content. With over 300 million reviews on its platform, Trustpilot has been at the forefront of combating fake reviews, recently winning 10 legal cases in the UK against bad actors. As the FTC cracks down on deceptive review practices with fines of up to $50,000 per violation, businesses must rethink their approach to online credibility. Anoop shares insights on what this regulatory shift means for companies and how Trustpilot's AI-driven approach is evolving to stay ahead of generative AI-generated fake reviews. We explore how Trustpilot's transparency efforts led to the removal of 3.3 million fake reviews last year alone and why a combination of AI, metadata analysis, and human oversight is critical for maintaining trust online. As AI-generated content becomes more sophisticated, Anoop also sheds light on emerging trends and the growing need for regulatory adaptability. If online reputation matters to your business—or if you've ever wondered how review platforms separate real feedback from deception—this episode is packed with insights you won't want to miss. Could AI ever be trusted to fully police itself, or will human intervention always be required to maintain trust?

The future of medicine is being shaped by technology, and few companies are pushing the boundaries like GSK. In this episode, I sit down with Christopher Austin, Head of Research Technologies at GSK, to explore how AI, data science, and cutting-edge digital capabilities are revolutionizing drug discovery and development. Chris shares how GSK is harnessing vast datasets, AI-driven insights, and genetic validation to speed up the identification of promising drug targets. We discuss how computational biology and machine learning are dramatically reducing the time it takes to develop new treatments—sometimes cutting discovery timelines in half. From selecting the right molecular designs to improving patient identification for clinical trials, technology is streamlining the entire R&D process, increasing success rates, and ultimately bringing life-saving medicines to patients faster. We also dive into the role of generative AI in modeling diseases, designing antibodies, and optimizing clinical trials. With AI now shaping everything from drug formulation to patient recruitment, we explore what this means for the future of medicine and the ethical considerations that come with such rapid advancements. How will AI-driven drug discovery change the pharmaceutical industry in the next decade? What challenges remain in integrating these new technologies into traditional research models? And what does all of this mean for patients and the future of healthcare? Tune in to hear how GSK is leading the charge in transforming medicine through technology.

AI is transforming the way we experience storytelling, and few people understand this shift better than Geoff Thatcher. As the Creative Director behind the GAME ON! AI Experience at the College Football Hall of Fame, Geoff is pioneering how AI can place visitors at the heart of an attraction—turning spectators into active participants. In this episode, we explore the intersection of AI, immersive storytelling, and the evolving expectations of audiences. Geoff shares how AI-powered personalization is reshaping museums, theme parks, and live experiences, making guests part of the narrative rather than just observers. From scanning faces to seamlessly integrating visitors into game-day experiences, he explains how technology is allowing brands and institutions to scale engagement like never before. But as AI deepens immersion, it also raises questions—how far will audiences expect personalization to go? Will simply watching a story unfold ever be enough again? And what ethical and creative challenges come with placing visitors inside historical exhibits, theme park rides, or even feature films? We also dive into the economics of AI-driven experiences. How does AI influence the way attractions are designed, priced, and operated? Can small museums and local attractions afford to implement these innovations, or will personalization remain an exclusive luxury for major brands? Geoff brings his extensive experience in experiential design to shed light on how AI can be a tool to connect people through storytelling—when used thoughtfully. If you've ever wondered about the future of immersive entertainment, AI in storytelling, or how technology is redefining guest engagement, this episode is one you won't want to miss. Will the experiences of tomorrow demand that we step inside the story? Tune in to find out.

In this episode of Tech Talks Daily, I sit down with Cerisse Velasco, Director of Midwest and Retail Media Brand Partnerships at Zynga, to explore how mobile gaming is reshaping digital advertising and brand engagement. While gaming has long been associated with teenage boys in basements, the reality is quite different—Zynga's audience is predominantly Millennial and Gen X women, a demographic that's often overlooked in marketing strategies. With mobile games like Words with Friends, Game of Thrones: Legends, and Match Factory, Zynga has built a massive entertainment platform where brands can authentically connect with engaged consumers. We discuss how mobile gaming offers a "leaned-in" advertising experience, with players actively engaging rather than passively scrolling. From rewarded video and interactive formats to in-game integrations, Zynga is pioneering innovative ad strategies that feel natural within the gameplay, rather than interrupting it. A recent partnership with The Real Housewives is a perfect example of how brands are rethinking their approach to mobile gaming, tapping into a highly influential and purchase-driven audience. Beyond traditional advertising, we also explore the future of gamified brand experiences, AI-powered personalization, and retail media integrations within gaming. As mobile gaming continues to dominate screen time, brands that embrace these new engagement models will have a significant edge in the evolving digital marketing landscape. How can brands create authentic connections with audiences in gaming environments? And what does the future hold for advertising in mobile entertainment? Tune in to hear Cerisse Velasco's insights on the changing face of digital engagement.

AI is transforming businesses' operations, but are executives ready to lead this revolution? In this episode, I sit down with Greg Shove, CEO of Section, to discuss the most significant mistakes leaders make when adopting AI and why many companies are falling behind despite all the hype. Greg, a seasoned entrepreneur and AI strategist, shares why leaders must go beyond buzzwords and get hands-on with AI to drive real impact. He explains how organizations can build a scrappy but effective AI strategy, why CFOs increasingly embrace AI-driven efficiency, and what that means for future jobs. We also discuss how AI reshapes everyday decision-making, from the workplace to personal productivity. Beyond the corporate world, Greg highlights a more significant concern—Big Tech's control over AI. Drawing from past experiences in Silicon Valley, he warns that AI might follow the same playbook as social media and cloud computing: get everyone hooked, then raise the price. If AI becomes indispensable, are businesses at risk of outsourcing too much cognition to just a few dominant players? From AI's impact on job security to how leaders can create an AI-powered workforce, this conversation challenges conventional thinking on AI adoption. Whether you're an executive looking to integrate AI into your strategy or an employee navigating the shift, this episode is packed with insights to help you stay ahead. Is AI genuinely democratizing knowledge, or are we just making ourselves more dependent on a handful of companies? And how can leaders ensure they're leveraging AI as a strategic asset rather than just another tool? Tune in to find out.