Tech Talks Daily

When we talk about the future of technology, it is easy to focus on the tools, trends, and innovations that dominate headlines. But behind every breakthrough is a human story, and behind every system are individuals navigating an industry that has not always welcomed them equally. That is why I sat down with Sue Harnett, founder and CEO of Rewriting the Code, to learn more about the real work being done to support and elevate women in technology. What followed was a wide-ranging conversation that brings clarity to an often-overlooked challenge and offers insight into what real change looks like. Rewriting the Code is more than a community. It is a global network of over 35,000 women who are united by shared goals and driven by the ambition to create a more inclusive tech industry. Sue shared the origin of the organization, born from her own experiences of feeling out of place in elite academic environments, and how that shaped her commitment to building a culture where young women could grow, thrive, and most importantly, feel like they belong. Today, RTC is impacting lives across the globe with programs that span mentorship, career development, technical education, and real-world support. What stood out was the way RTC moves beyond symbolic gestures and instead provides practical pathways. We explored the launch of targeted initiatives like Rewrite AI and Rewrite Cybersecurity, which aim to prepare women for high-demand areas in the industry. We also discussed the Black Wings program, built specifically for Black women in tech, who represent just two percent of the industry workforce. Through focused community-building and peer support, these programs help dismantle systemic barriers that often go unaddressed. In a time where many companies are retreating from public conversations about diversity due to political pressure, Sue's work feels more relevant than ever. She spoke candidly about the fear she's seeing in boardrooms, the erosion of public DEI commitments, and the quiet but continued support from leaders who still believe in building inclusive workplaces. Her message to companies was simple: inclusion must be intentional, visible, and connected to the lived experience of the people it is meant to support. What this episode reveals is not only the importance of creating opportunities, but also the power of belief. The belief that women belong in every corner of the tech world, and that with the right community, mentorship, and visibility, they can redefine what leadership looks like. So how is your organization showing up for underrepresented talent in tech, and what will it take to turn good intentions into lasting impact?

When we talk about the future of IT services, the conversation often revolves around the potential of AI and automation. But what does that really mean when applied at scale, across legacy infrastructure, evolving customer expectations, and real-world operational challenges? In today's episode, I sat down with Manish Tandon, CEO of Zensar Technologies, to explore that very question. What emerged was a refreshingly pragmatic take on a space often overwhelmed by buzzwords. Manish leads a global organisation that's helping some of the UK's biggest businesses not just integrate AI, but rethink the foundation of their IT strategies. We discussed how Zensar is combining automation with a philosophy they call "experience-led everything," a human-centric approach that puts users, not systems, at the centre of transformation. Through this lens, he explained how seemingly simple shifts like applying AI to reduce technical debt or drive internal engagement can lead to significant performance gains and improved outcomes across entire organisations. What I found particularly powerful was how Manish challenges the language around AI. He sees today's wave of generative and agentic AI as an evolution of long-standing automation principles, not a reinvention. That mindset is helping clients cut through the noise and focus on impact, such as faster delivery cycles, measurable productivity boosts, and tools that empower rather than replace human potential. We also touched on the ethical implications of AI, the nuances of implementation across different geographies, and the value of responsible AI governance at the application level, not just in principle. If your business is looking to adopt AI in a way that scales sensibly while delivering lasting value, this episode offers insights you won't want to miss. So how are you preparing to balance automation with empathy in your IT strategy, and are you building for systems or for people?

What happens when automation grows and learns to think, reason, and adapt? That is precisely what I explored in today's episode with Bennet Kumar, Executive Vice President and Global Head of Business Process Services at Hexaware Technologies. As the enterprise world braces for rapid AI-driven change, Bennet joined me to unpack how agentic AI quietly transforms customer experience from the ground up. Bennet explains how agentic AI is fundamentally different from earlier forms of automation. We go beyond the buzzwords to explore how these intelligent systems retain business context, plan and execute tasks with autonomy, and collaborate with other agents to deliver meaningful outcomes. This isn't just a new toolset for organizations focused on ROI, customer satisfaction, and operational efficiency. It is a new way of working. One of the most compelling parts of our conversation centered around AI-powered voice translation. Bennet clearly shows what happens when language ceases to be a barrier. Service agents are no longer required to be fluent in dozens of languages. Instead, they can focus on empathy, listening, and resolution while AI handles translation in real time. We also explore how these technologies reduce stress on customer service staff, giving them more meaningful roles and the tools to thrive. Of course, no digital transformation is complete without understanding the people behind it. Bennet shares thoughtful insights on change management, addressing customer trust and employee concerns. We discuss how AI can empower rather than replace, and why organizations must be intentional about communication, leadership development, and cultural shift. From multilingual support to hyper-personalized customer journeys, and AI assistants to back-end process orchestration, agentic AI is no longer a future concept. It is already here. But are enterprises prepared for a world where customers and AI agents interact seamlessly, at scale, daily? What does the rise of intelligent agents mean for your business?

What happens when access to advanced AI models is no longer the real differentiator, and the true advantage lies in how businesses leverage their own data? At the AWS Summit in London, I sat down with Rahul Pathak, Vice President of Data and AI Go-to-Market at AWS, to unpack this question and explore how organisations are moving beyond experimentation and into large-scale generative AI adoption. Recorded live on the show floor, this conversation explores how AWS is supporting customers at every layer of their AI journey. From custom silicon innovations like Trainium and Inferentia to scalable services like Bedrock, Q Developer, and SageMaker, AWS is giving businesses the infrastructure, tools, and flexibility to innovate with confidence. Rahul shared how leading organisations such as BT Group, SAP, and Lonely Planet are already applying these tools to reduce costs, speed up development cycles, and deliver tailored experiences that would have been unthinkable just a few years ago. A key theme that emerged in our discussion is that data, not just models, is the true foundation of effective AI. Rahul explained why unifying data across silos is critical and how AWS is helping companies create more intelligent applications by connecting what they uniquely know about their business to powerful AI capabilities. We also addressed the operational realities of AI deployment. From moving proof-of-concept projects into production to meeting the growing demand for responsible AI, the challenges are shifting. Organisations are now focused on trust, security, transparency, and measurable value. If you're leading digital transformation and wondering how to scale AI solutions that deliver on business outcomes, this episode provides practical insight from someone at the center of the industry. How will your business stand out in a world where every company has access to AI models, but only a few know how to apply them with purpose?

In today's episode of Tech Talks Daily, I sit down with Christian Reilly, Field CTO for EMEA at Cloudflare, the Connectivity Cloud company, to examine the latest findings from their cybersecurity research and what they reveal about how prepared different industries really are. While sectors like IT, gaming, and financial services have seen a higher volume of cyberattacks, they also report greater readiness and resilience. In contrast, industries like education and healthcare, although less frequently targeted, remain far less prepared to defend against growing threats. This gap raises important questions about how organizations approach security depending on their legacy systems, revenue models, and digital maturity. Christian brings years of frontline experience to the discussion and shares actionable insights into how companies can build cybersecurity strategies that not only protect but also improve performance. From the shift toward zero trust architecture to the critical role of board-level engagement, we explore how forward-thinking organizations are rethinking the role of cybersecurity in modern digital operations. He explains why simplicity often beats complexity, and how reducing friction for end users is key to long-term resilience. We also look ahead to some of the key trends shaping the future of security. Christian dives into the challenges posed by emerging technologies such as quantum computing, AI, and the explosion of data generated by IoT and smart infrastructure. He stresses the importance of preparing now for scenarios like Harvest Now, Decrypt Later, and why organizations need to begin thinking seriously about post-quantum cryptography. On the human side, Christian outlines what effective training looks like today and how to shift employee culture from compliance to awareness. If you're wondering how to stay one step ahead of evolving threats, this conversation offers a wealth of insight from the heart of the Connectivity Cloud. How is your organization preparing for what's coming next?

In today's episode of Tech Talks Daily, I reconnect with Abnormal AI's CIO, Mike Britton, to explore one of the most pressing topics in the tech world—AI regulation and cybersecurity. Speaking from his base near Dallas, Mike brings a pragmatic perspective shaped by decades of experience at the intersection of enterprise technology and security. As the debate around artificial intelligence evolves, we examine the growing divide between the United States and Europe on regulatory approaches and what business leaders can learn from each side. While Europe takes a more cohesive, application-based approach, the US remains fragmented, relying on state-by-state policies and sector-specific laws. Mike unpacks why this patchwork complicates global alignment and what an effective risk-based, standardized framework might look like. He argues that regulation must focus on how AI is applied, not just its scale, especially as the technology becomes embedded in everything from healthcare to email automation. We also touch on the unintended consequences of overregulation, including the risk of pushing innovation into regions with fewer safeguards. As Abnormal Security works with some of the world's largest brands, Mike offers a frontline view into how threat actors are already leveraging AI to outpace traditional defenses. His insights reinforce the need for transparency, human oversight, and "kill switches" to ensure AI remains a tool for good, not a liability. From real-world examples to strategic recommendations, Mike outlines what CIOs and CISOs need to know now. His advice is clear, grounded, and actionable, whether embracing regulatory sandboxes, staying alert to geopolitical nuances in AI models, or maintaining continuous learning in a fast-moving space. So, how do we keep innovation ethical and secure in a world where AI is moving faster than ever? And what steps should technology leaders take to avoid falling behind or losing control of the tools meant to drive progress?

As artificial intelligence continues to reshape how we work, lead, and interact, the need for emotionally intelligent and human-centered leadership has never been more urgent. In this episode of Tech Talks Daily, I sit down with Jen Croneberger, the Founder and Chief Inspiration Officer at The Human Leadership Institute, to explore how relational leadership guides organizations through the noise and complexity of rapid AI adoption. With a background in sports and performance psychology and a career that spans working with elite athletes, government agencies, and global brands like Nike and Samsung, Jen brings a rare perspective to the conversation around AI. She argues that amidst all the automation and data, our ability to build trust, communicate transparently, and stay grounded in shared values will define success moving forward. Throughout the conversation, Jen makes the case that leaders today cannot rely on technical skills alone. They must create cultures of psychological safety, model adaptability, and foster a clear understanding of how AI can enhance rather than replace human capabilities. We also dive into some of the more challenging topics, including the ethical implications of AI, resistance to change, and why some employees struggle to see a future where they coexist with intelligent machines. What I found particularly insightful was Jen's ability to draw parallels between leading teams in high-stakes athletic environments and leading through tech transformation. Whether it's building resilience after a setback or navigating uncertain outcomes with confidence, the same foundational principles apply. As we look to a future where AI is embedded in every business layer, Jen's message is timely and practical. If you are a leader wondering how to support your teams through disruption without losing the soul of your culture, this episode will give you plenty to reflect on. How will you lead in a world where machines are intelligent, but people still need to feel seen?

How prepared is your business for a ransomware attack? Not just to prevent it, but to continue operating when it happens. In this episode, I sit down with Trevor Dearing, Director of Critical Infrastructure at Illumio, to discuss the latest findings from their global ransomware report and what they reveal about cyber resilience. Trevor shares insight from a survey of more than 3,000 organisations across multiple sectors. The most concerning figure is that 58 percent of those impacted by ransomware were forced to halt operations. That number has risen sharply from 43 percent just two years ago. Despite this, many businesses in the UK still avoid reporting attacks, often due to fears around reputational damage or potential retaliation. Trevor explains why that reluctance is misguided and how public support, improved infrastructure, and more explicit government guidance could encourage more transparency. We also explore the rise of containment as a more practical and cost-effective approach than prevention alone. Rather than trying to stop every attack at the perimeter, organisations are learning how to isolate and limit damage quickly. Trevor explains how zero trust architecture, microsegmentation, and one-click containment tools are being used to keep systems operational even during an incident. Only 13 percent of organisations believe their cyber resilience exceeds what is required. Trevor helps us understand why this number remains low and where organisations should focus to shift from vulnerability to resilience. From evolving regulations to future applications of AI in security, this conversation covers what leaders need to know if they prepare for the next generation of cyber threats. To access Illumio's full ransomware report, visit illumio.com. Is your cyber resilience strategy built for recovery, or just defense?

Amid the buzz of the AWS Summit in London, I sat down with Eiso Kant, the CTO and Co-Founder of Poolside, to explore how his team is reshaping the future of software development through AI. This conversation was recorded right on the show floor inside a surprisingly sleek podcast booth at the ExCel, where Eiso unpacked what sets Poolside apart in a space many claim to be in but few truly build for. Poolside is not just another AI company. It's one of a handful globally that is actually training foundation models from the ground up. While most firms are chasing general-purpose AI, Poolside has chosen a different path. They focus solely on empowering software developers inside high-consequence environments, such as banking, defense, and major global retailers. These are systems where precision and security matter, and where AI can drive measurable gains in productivity and reliability. What struck me during this discussion is how deliberately Poolside has been built for enterprise use from the start. Their model doesn't just live in the cloud. It is designed to live within the customer's own infrastructure, whether that's in their private AWS environment or even on-prem. This focus on data privacy, security, and customizability is helping Poolside win trust where it counts most. And the partnership with AWS takes this a step further, making it easier for enterprises to deploy Poolside's AI within existing cloud frameworks while meeting strict governance requirements. Eiso explained that Poolside doesn't just throw larger models at problems. Instead, they use reinforcement learning from code execution, training on millions of real codebases and test suites. This approach helps the model go beyond autocomplete and simple bug fixes. It's now stepping into longer, more complex tasks, nudging us closer to a future where AI could serve as a true teammate for software engineers. We also tackled one of the most important discussions in AI today: whether this is a cost-cutting tool or a productivity multiplier. Eiso didn't dodge the nuance. While some may use AI to reduce headcount, Poolside's focus is on enabling companies to build more, ship faster, and innovate with greater speed. That shift is not about replacing people. It's about creating leverage for development teams under pressure to deliver more in less time. If you're a CTO, CIO, or engineering leader, this episode is packed with practical insights. Whether it's understanding the ROI of AI-assisted development, the importance of retaining control of your own models, or how to think about enterprise-grade security in the age of LLMs, there's a lot here to digest. So how should we really be thinking about AI in the enterprise? Is it a partner, a tool, or the beginning of an entirely new workforce paradigm? Tune in to find out.

What if the food you eat could not only affect how you feel today but also determine how many healthy years you'll have in the future? In this episode of Tech Talks Daily, I sit down with Jonathan Wolf, the co-founder and CEO of Zoe, to explore how advanced science, AI, and data are reshaping our understanding of nutrition and health. Jonathan shares the remarkable journey of building Zoe from an idea into a leading science and nutrition company that has reached hundreds of thousands of users. From a background in physics and ad tech to pioneering personalized nutrition, Jonathan has led Zoe through significant milestones, including publishing more than 70 peer-reviewed papers and developing tools that empower individuals to understand their microbiomes, track real-time health markers, and make lasting changes to their diet. We also dive into the technology powering Zoe's new free app launch in the US, which aims to help consumers see what's really in their food. Through food photo recognition, AI-driven analysis, and a unique risk scale for processed food, Zoe is offering a tool that could change how people choose what they eat. Jonathan explains why ultra-processed foods are a major public health concern and how empowering individuals with knowledge is the first step toward lasting change. Beyond product features, this conversation also unpacks the tension between rigorous scientific integrity and business growth, the importance of behavior change, and the broader implications for public health. Whether you're interested in the future of AI in healthcare, building a purpose-driven tech company, or simply making smarter food decisions, this episode will leave you thinking differently about what's on your plate. How can personalized nutrition move from science labs into daily life, and what role should tech leaders play in that shift?

How do you teach financial literacy to a generation that's grown up swiping on social media, watching crypto rise and fall, and navigating economic uncertainty before they've even finished university? That's the question Aleksandra Medina set out to answer when she co-founded Frich—a social finance app built with Gen Z in mind. In this episode, I sit down with Aleksandra, the CPO and co-founder of Frich, to explore how she and her team are redefining financial wellness for the next generation. Born out of a small New York apartment and their own shared frustrations with managing money, Frich isn't your typical finance app. It gives users a way to benchmark their spending and saving against their peers, sparking conversations around topics often ignored—like how much support you're getting from your parents, or whether you're overpaying on rent compared to people your age. With over 800,000 users and partnerships with banks, credit unions, and fintechs, Frich has become a trusted tool in a space where many young people feel overlooked. Aleksandra explains how her role as Chief Product Officer puts her at the intersection of tech and impact, designing an app that's as much about psychology and transparency as it is about numbers. We also talk about what it's like raising funds as a first-time founder during a period of economic headwinds, and why Gen Z's financial potential is often underestimated. Throughout our conversation, we explore why open dialogue is key to improving financial well-being and how Frich uses gamified, community-driven insights to make those dialogues easier and more fun. From daily polls to data-driven recommendations, the app flips the script on traditional financial advice, replacing lectures with real-world relevance. Is Gen Z as financially lost as some headlines suggest? Or are they simply lacking the right tools and data to guide their decisions? Frich is betting on the latter. Where are you benchmarking your financial reality? And how might a little more transparency change the way you approach money?

In today's episode, I had the opportunity to speak with Rafael Carazo Salas, a scientist, entrepreneur, and the CEO and founder of CellVoyant. This is a conversation that goes beyond the hype around AI to reveal how machine learning is reshaping the future of healthcare in ways that are both profound and immediate. CellVoyant, a spinout from the University of Bristol, is using AI and advanced imaging technology to solve one of the most persistent challenges in biotech: the cost, time, and complexity involved in developing cell therapies. Rafael explained how his team is applying real-time microscopy and predictive AI to monitor and guide cell behavior. This approach doesn't rely on invasive techniques that destroy the very cells being studied. Instead, it enables a clearer path forward in cell therapy development by understanding how cells behave and adapt over time. We explored several impactful examples, from CAR-T therapies for blood cancers to emerging treatments for Parkinson's disease and type 1 diabetes. Rafael drew comparisons to Google Maps, describing how CellVoyant's platform builds dynamic roadmaps for cell development, allowing scientists to correct course in real time. It's a shift in how we think about drug development, one that has the potential to lower costs and increase access to life-saving treatments. Beyond the science, Rafael shared his insights on the UK's biotech ecosystem, the role of academic spinouts, and why now is a strategic moment for the UK to establish itself as a global leader in AI-powered biotech. As political and economic conditions shift in other parts of the world, he sees a window of opportunity to attract talent, drive innovation, and strengthen commercialisation. So how far can AI go in transforming biotech, and what role will companies like CellVoyant play in making advanced therapies available to all? Tune in to find out.

What happens when marketing, psychology, and emerging tech converge around a single purpose, redefining the relationship between brands and consumers? In today's episode, I'm joined by Jaime Schwarz, a creative force behind Brand Therapy, The TeamFlow Institute, and MRKD.art, whose work is challenging the very foundations of modern brand strategy. From early days in the advertising trenches to pioneering Web3-native branding frameworks, Jaime brings a fresh take on how brands should evolve in a world dominated by AI, XR, and blockchain. We unpack the philosophy behind Brand Therapy — not as a gimmick, but as a framework that positions the brand as a living voice within the organization, mediating between company intent and customer expectation. Jaime explains how the rise of conversational AI and tokenized digital products shifts the entire focus from knowing your customer to understanding your product, not in terms of features, but as vehicles of legacy, collaboration, and value exchange. Throughout the discussion, Jaime breaks down complex ideas into accessible frameworks, such as the shift from consumerism to "conspicuous prosumerism," where ownership is just the beginning of the story. Whether it's a sneaker, a piece of digital art, or an AI-enabled car that remembers your preferences and evolves with you, Jaime shows how technology can enhance brand relationships rather than dilute them. We also dive into the challenges of co-creation in enterprise environments, why marketers need to rethink what product-market fit actually means in the age of real-time AI interaction, and how NFTs, quantum computing, and immersive experiences are not hype but building blocks of a new economic model. Jaime's insights offer not just theory but a call to action for companies to stop waiting for the future and start prototyping it. If you're curious about how the smartest brands are embracing change without losing their core identity, this episode offers a compelling roadmap. And if you're in New York during NYTechWeek, don't miss the launch of MRKD.dj's Infinite Drop Live Album — June 6, only 150 tickets available. https://partiful.com/e/mFEMK9C7GHKoRw73ryVg

How do you measure the real impact of marketing when every campaign unfolds across multiple channels, mixes digital with physical, and generates more data than most teams can handle? That's exactly what Abby Kearns and the team at Alembic are tackling. As Chief Technology Officer, Abby is helping build a marketing intelligence platform that doesn't stop at high-level trends or guesswork. Instead, it goes deeper to identify what actions actually drive business outcomes. In this episode, Abby joins me to explain how Alembic brings together data science, custom-built neural networks, and lessons from pandemic-era contact tracing to solve one of the longest-standing problems in enterprise marketing. By ingesting data from CRM systems, media buys, social platforms, events, and even foot traffic, Alembic identifies causal relationships between brand activities and revenue. It's an approach that has already earned the trust of companies like Nvidia and Delta Airlines. We also talk about how Alembic uses a combination of deep learning and large language models. While their custom algorithms surface insights and attribute outcomes, the AI layer makes the data digestible for decision-makers. The goal is to help enterprise teams move beyond anecdotal evidence and finally answer the question: what is working, and why? Abby also opens up about the challenges that come with building and scaling a platform at the edge of what's technically possible. From managing massive data pipelines to keeping pace with generative AI innovation, the team at Alembic is pushing forward fast. This episode is packed with insights for business leaders who want to make smarter marketing decisions grounded in real data, not assumptions. Are you confident that your marketing spend is delivering measurable value, or is it time to take a closer look at what the data is really telling you?

What if the solution to screen addiction, online bullying, and tech-driven anxiety lies not in removing devices altogether, but in rethinking how we introduce them? That's the question at the heart of my conversation with Bill Brady, co-founder and CEO of Troomi. In a world where children are spending up to nine hours a day on screens, and where the dangers of unrestricted device access are no longer hypothetical, Troomi offers an intentional and thoughtful path forward. Bill joins me to share why he believes optimism, not fear, should guide the future of kids and technology. A father of five and a longtime student of digital wellness, Bill created Troomi as a developmental tool. It is a smartphone designed to grow with your child. We explore how Troomi's Android-based platform allows parents to build a tech environment that is safe, flexible, and adaptable. From contact safe-listing and real-time content filtering to the complete removal of social media, the phone helps kids communicate, learn, and grow without the overwhelming distractions and risks that dominate conventional devices. This episode also addresses the growing mental health challenges children face, from constant social comparison to online predators. With research showing that most teenagers believe social media negatively affects their well-being, Bill explains why a proactive approach is critical. He offers insights into how parents can strike a balance between digital freedom and protection without isolating their kids from the benefits of modern technology. We also discuss how Troomi is integrating AI to create a safer online experience through real-time content vetting and educational tools. Bill highlights new features on the horizon and shares the company's plans to expand beyond the United States, particularly to markets like the United Kingdom where demand for healthier tech options is growing. How can we equip the next generation with technology that supports their growth rather than hinders it?

What if AI could help your content speak every language without losing its heart? In today's episode, I sat down with Oz Krakowski, Chief Business Development Officer at Deepdub, a company reshaping how stories cross linguistic and cultural borders through AI-powered dubbing. As global demand for diverse entertainment continues to surge, Deepdub is offering studios a new way forward—one that balances scale with emotional fidelity. Oz walked me through how Deepdub's platform enables post-production teams to dub content into over 130 languages and dialects, with output that respects the tone and intent of the original performance. This isn't about replacing human creativity—it's about integrating it into smarter workflows. Through a hybrid approach, Deepdub fuses cutting-edge AI with seasoned voice actors, directors, and editors to maintain authenticity while massively improving efficiency. From monetizing dormant titles trapped in single-language formats to opening up live broadcasts for real-time localization, the implications are wide-ranging. Oz also shared how Deepdub Live is already unlocking access to new global audiences for sports, conferences, and beyond—potentially transforming how we experience real-time events. We also explored the deeper economics of AI dubbing, especially as the cost of localization begins to fall, making it more viable to bring overlooked content into untapped markets. Whether it's delivering content in regional dialects or enabling personalized voice experiences across industries like eLearning and customer service, the roadmap for AI localization is expanding far beyond the entertainment world. At a time when studios are re-evaluating their content strategies, Deepdub offers a glimpse of what's possible when AI meets cultural intelligence. Could your next global audience already be waiting? Have you considered how AI might help your content reach new viewers without losing its original voice?

How do you uncover misinformation and financial fraud hidden in plain sight across thousands of digital platforms during a global election cycle? In this episode, I spoke with Jim Webber, Chief Scientist at Neo4j, to explore how graph database technology is being used to expose coordinated disinformation campaigns, empower AI systems, and help enterprises manage the complexity of modern data. At the heart of our conversation is the story of the ElectionGraph Project, where Syracuse University used Neo4j's graph technology to investigate political ad spend on Meta platforms. What they discovered was not just political messaging, but sophisticated scams disguised as legitimate campaigns. These efforts, targeting civically engaged users, used merchandise giveaways as a front to harvest credit card details and enroll victims in recurring billing traps. Traditional analytics would have struggled to trace these relationships, but graph databases allowed researchers to map and understand the deeper connections between thousands of entities. We also unpack how graph technology goes far beyond fraud detection. Jim explains why graph databases are now foundational for businesses building AI systems, particularly those using Retrieval-Augmented Generation (RAG) to reduce hallucinations and improve decision making. Whether it's helping enterprises respond to customer needs or enabling AI agents to take action in real time, graphs provide the structure and context needed for reliable outcomes. Jim also shares the backstory behind Klarna's data transformation, where the company embraced knowledge graphs at the core of its operations and replaced major systems, including parts of Salesforce. It's a striking example of what becomes possible when a business commits to connected data as a strategic asset. From misinformation to intelligent automation, this episode dives into the real-world value of graph technology in 2025. Are you thinking critically about how your data infrastructure supports your AI ambitions?

What does digital sovereignty mean in the age of cloud computing, and is Europe finally prepared to rethink its reliance on foreign infrastructure? In this episode, I speak with David Michels from Queen Mary University of London about his latest research, which examines the growing demand for sovereign cloud services across Europe. Commissioned by Broadcom but developed independently, the report surfaces at a time when regulators, enterprises, and policymakers are all asking tougher questions about who controls data and how. David explains why the concept of a sovereign cloud is still poorly defined. Depending on who you ask, it might mean autonomy over data, protection from foreign surveillance, or strategic independence from global superpowers. That ambiguity creates confusion for customers and raises compliance risks in regulated industries. My guest also addresses one of the most persistent misconceptions in the market: the difference between data residency and data sovereignty. Just because data is stored in Europe does not mean it is immune from foreign access if the provider falls under another country's jurisdiction. We dig into the practical implications of these issues, including why many organizations are reassessing their risk exposure, particularly in light of extraterritorial legal frameworks like the US CLOUD Act. David outlines a pragmatic approach to improve clarity without waiting for new legislation. His proposed GDPR-aligned code of conduct would allow cloud providers to transparently demonstrate compliance with European data protection expectations, giving customers a stronger basis for trust and accountability. This conversation is not about cloud theory. It is about legal risk, operational impact, and policy direction. Whether you're a CIO navigating compliance, a regulator shaping guidance, or a provider building cross-border services, this episode offers a clear-eyed look at the shifting demands of digital sovereignty. Are European organizations finally ready to take a different path in the cloud?

In today's episode of Tech Talks Daily, I sit down with Jeff Butler, General Manager of Cask Canada, who shares the story of how he led a tech startup to a standout position in the competitive ServiceNow ecosystem in less than a year. Listen in to learn how Cask Canada grew from startup to standout in the ServiceNow ecosystem by focusing on people, trust, and AI-driven transformation. As we explore Jeff's unique journey from his early days witnessing the birth of Silicon Valley innovation in San Francisco to building a thriving ServiceNow consulting business in Canada, there are lessons here for anyone navigating today's fast-moving tech landscape. Jeff offers a first-hand look at the unexpected realities of launching a consultancy in Canada's evolving digital market. Rather than focusing solely on technology, he highlights the power of building genuine, long-term relationships with clients and team members. Throughout our conversation, it becomes clear that success in tech services today is shaped as much by trust, patience, and authenticity as it is by technical excellence. We also discuss how AI and automation are reshaping ServiceNow-driven digital transformations. Jeff provides valuable insight into how AI is not just enhancing customer service experiences but also beginning to change the way consulting services are delivered. Yet he makes an important point: human oversight remains vital, especially when high-stakes business decisions are involved. Looking ahead, Jeff reflects on the challenges and opportunities that ServiceNow partners face as AI capabilities mature, integration demands grow, and the implementation partner landscape changes. He also shares how building an elite consulting team required a deliberate focus on culture, communication, and finding people who want to build something bigger than themselves.

What if contracts could do more than sit in a drawer gathering dust? In today's episode, I sit down with Monish Darda, CTO and Co-founder of Icertis, to explore how AI is transforming contracts into powerful, active business assets. Monish shares how Icertis has evolved from early machine learning models to leveraging large language models like GPT to extract information and true intent from contracts. This breakthrough allows organizations to optimize business relationships, enforce commitments such as sustainability goals, and significantly reduce revenue leakage, often reclaiming up to 9% of contract value. During our conversation, Monish explains how contracts become first-class enterprise objects actively participating in workflows, shaping how commerce operates at scale. We dive into real-world examples, including how a global pharmaceutical company saves over $70 million annually by optimizing supplier pricing across multiple countries and languages. Monish also highlights Humana's success in cutting operating expenses by over $125 million by embedding contract intelligence into core processes. We also unpack the importance of data quality in building trustworthy AI systems. Monish looks at how Icertis ensures clean, actionable contract data through a standard data model, human-in-the-loop verification, and hundreds of thousands of built-in validation rules. As the world rapidly embraces AI, he shares his vision for a future where AI agents are constrained by the "rules of business" defined within contracts, ensuring responsible and reliable decision-making. Monish rounds off our discussion with an inspiring nod to Isaac Asimov and the power of storytelling in shaping our understanding of technology's future. If you ever thought contracts were just static documents, this conversation will change how you see them and reveal how AI is reshaping the foundations of enterprise operations. How is your organization preparing for a future where contracts guide and drive business outcomes?

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 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?