Tech Talks Daily

In today’s episode of Tech Talks Daily, I sit down with Prashanth Chandrasekar, CEO of Stack Overflow, to explore how the rise of AI is reshaping the future of software development and the evolving role of community-driven platforms. Prashanth offers a grounded view of what is happening behind the headlines as the tech world moves into the third year of widespread AI adoption. We begin by unpacking how AI is already transforming the way developers work, automating routine coding tasks, while still falling short when it comes to complexity and trustworthiness. Prashanth explains why Stack Overflow is positioning itself as a community and a vital "Knowledge as a Service" platform, integrating with AI tools to maintain trusted knowledge in an age where data quality and source attribution have never been more important. Our conversation also delves into the growing concern of "LLM brain drain" and the broader data crisis facing AI innovation. Prashanth highlights the importance of human-generated content, even as synthetic data technologies advance. He shares why Stack Overflow's continued investment in community-driven knowledge, responsible AI use, and strategic partnerships with major AI players is critical to maintaining a healthy ecosystem for developers and enterprises. We also look ahead to Stack Overflow's strategic priorities, including expanding content types, integrating AI into both the public platform and Stack Overflow for Teams, and moving toward a seamless user experience across the tools developers already use every day. How can businesses balance automation with human insight in their AI strategies? Why is data scarcity a looming issue for AI development? And how is Stack Overflow preparing to lead community and enterprise solutions into the next era of innovation? Let's find out.

How do businesses untangle years of legacy technology without risking everything they have built? Today on Tech Talks Daily, I sat down with Jacek Migdał, founder and CEO of Quesma, to explore this question and discover how his company offers a fresh and pragmatic approach to database migration and optimization. Jacek shared the story behind Quesma's creation, shaped by his early exposure to databases through his father's work and his own experiences in Silicon Valley. Through extensive research, he identified a widespread frustration among businesses trying to modernize their legacy systems, often facing high costs, licensing nightmares, and failed migrations. Rather than tearing everything down and starting from scratch, Quesma offers a database gateway that acts as a middle layer, allowing gradual migrations with far less risk. I learn more about how this technology enables companies to test new systems alongside their old ones, helping to avoid the costly mistakes that have historically derailed so many modernization projects. We discussed how Quesma is addressing complex challenges across industries like telecom and travel. Their solution is already providing companies with ten times faster performance while significantly lowering operational costs, all without forcing disruptive system changes. Jacek also gave a sneak peek into two exciting new products launching soon. SQL extensions with pipe syntax will enrich data directly inside databases, while a feature called "smart charts" will offer AI-powered visualizations for faster, clearer insights. What makes Quesma truly stand out is its unapologetically pragmatic approach. Rather than assuming a clean, cloud-native environment, Quesma embraces most businesses' messy realities. Their clever use of AI enhances migration processes without relying solely on black box systems, striking a unique balance between speed, reliability, and cost efficiency. As we look toward the future, Jacek shared how Quesma is pushing forward with open-source initiatives, observability pipelines, and forming consortiums with major players in the tech industry. With upcoming appearances at major conferences in the United States and Europe, it is clear that Quesma is carving a new path for database modernization. How could a smarter approach to data migrations change how your organization adapts and grows in a data-driven world?

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 Sport AI, 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. Sport AI 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, Sport AI delivers data-backed insights directly to coaches and players through integrations with camera-enabled courts and coaching platforms. We also dive into how Sport AI'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 Sport AI 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.

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 Shepherd, 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 StoreEra, 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 StoreEra’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, StoreEra 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 StoreEra 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 gives insight into 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 StoreEra 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.