Tech Talks Daily

What happens when the push for smarter crypto wallets runs headfirst into the reality that everything on a public blockchain can be seen by anyone? In this episode of Tech Talks Daily, I wanted to take listeners who may not live and breathe Web3 every day and introduce them to a problem that is becoming harder to ignore. As Ethereum evolves and smart accounts unlock new wallet features, the surface area for risk grows at the same time. That is where privacy-first Layer 2 solutions enter the conversation, not as an abstract idea, but as a practical response to very real security and usability concerns. My guest is Joe Andrews, Co-founder and President at Aztec Labs. Joe brings an engineering mindset shaped by years of building consumer-facing applications and deep privacy infrastructure. Together, we unpack why privacy and security can no longer be treated as separate topics, especially as Ethereum rolls out more advanced account features. Joe explains how privacy-first Layer 2 networks act as an added line of defense, reducing exposure to threats that come from fully transparent balances, identities, and transaction histories. We also talk about what Aztec actually is, often described as the Private World Computer, and why that framing matters. Joe shares learnings from Aztec's public testnet launch earlier this year, what surprised the team once thousands of nodes were running in the wild, and how the community has stepped up in ways the company itself could not have planned for. There is also an honest discussion about the UK crypto scene, the missed opportunities, and the quiet resilience of builders who continue to ship despite regulatory uncertainty. As we look ahead, Joe outlines what comes next as Aztec moves closer to enabling private transactions on a decentralized network, and why the next phase is less about theory and more about real people using privacy in everyday interactions. If you are curious about how privacy-first Layer 2 solutions fit into Ethereum's roadmap, or why privacy might be the missing piece that finally makes smart wallets usable at scale, does this conversation change how you think about the future of crypto, and where would you like to see this technology go next? Useful Links Connect with Joe Andrews Learn more about Aztec Labs Tech Talks Daily is Sponsored by Denodo

What happens when the systems designed to make life easier quietly begin shaping how we think, decide, and choose? In this episode of the Tech Talks Daily Podcast, I sit down with Jacob Ward, a journalist who has spent more than two decades examining the unseen effects of technology on human behavior. From reporting roles at NBC News, Al Jazeera, CNN, and PBS, to hosting his own podcast The Rip Current, Jacob has built a career around asking uncomfortable questions about power, persuasion, and the psychology sitting beneath our screens. Our conversation centers on his book The Loop: How A.I Is Creating a World Without Choices and How to Fight Back, written before ChatGPT entered everyday life. Jacob explains why his core concern was never about smarter machines alone, but about what happens when AI systems learn us too well. Drawing on behavioral science, newsroom experience, and recent academic research, he argues that AI can narrow our sense of possibility while convincing us we are gaining freedom. The result is a subtle tension between convenience and control that many listeners will recognize in their own digital lives. We also explore the idea of AI companies behaving like nation states, accumulating talent, influence, and authority without the checks that usually accompany that kind of power. Jacob reflects on the speed of AI deployment, the belief systems driving its biggest champions, and why individual self control is unlikely to be enough. Instead, he makes the case for systemic responses, cultural guardrails, and a renewed focus on protecting human skills that cannot be automated away. There is room for optimism here too. We talk about where AI genuinely helps, from medicine to scientific discovery, and how leaders can hold hope and skepticism at the same time without slipping into hype or fear. From preserving entry level work as a form of apprenticeship to resisting the urge to outsource thinking itself, this episode offers a thoughtful look at what staying human might mean in an age of intelligent machines. Jacob has also appeared on shows like The Joe Rogan Experience, This Week in Tech, and The Don Lemon Show, but this conversation strips things back to fundamentals. How much choice do we really have, and what are we willing to give up for frictionless answers? If AI is quietly closing the loop around our decisions, what does fighting back actually look like for you, and where do you think that line between help and influence should be drawn? Useful Links Connect With Jacob Ward Check out his website and book The Rip Current Podcast Tech Talks Daily is Sponsored by Denodo

How is HR changing when AI, economic pressure, and rising employee expectations all collide at once? In this episode of Tech Talks Daily, I'm joined by Simon Noble, CEO of Cezanne HR, to unpack how the role of HR is evolving from a traditional support function into something far more closely tied to business performance. Simon shares why HR is increasingly being judged on outcomes like retention, capability building, and readiness for change, rather than policies, processes, or cost control. Yet despite that shift, many HR leaders still find themselves pulled back into a compliance-first mindset as budgets tighten, skills shortages persist, and new legislation raises the stakes. We explore how AI fits into this picture without stripping the humanity out of HR. Simon is clear that AI should automate administration and free up time, rather than replace human judgment or empathy. Used well, it removes friction from onboarding, compliance, and everyday queries, giving HR the space to focus on culture, leadership, and long-term talent development. Used poorly, it risks adding noise without value. The difference, he argues, comes down to data. Without clean, consolidated data, AI simply cannot deliver meaningful insight, no matter how advanced the technology appears. The conversation also looks inward at Cezanne HR's own growth journey. Simon describes rapid expansion as chaos with better branding, and explains why maintaining culture, trust, and clarity becomes harder, yet more important, as teams scale. From onboarding new employees to ensuring a consistent customer experience, the same principles apply internally as they do for customers using HR technology. We also touch on trust, transparency, and the growing focus on areas like pay transparency, data responsibility, and employee confidence in how their information is handled. As expectations continue to rise, HR's credibility increasingly rests on accuracy, fairness, and the ability to turn insight into action. As HR steps closer to the center of business strategy, what mindset shift is needed to move from reacting to change toward actively shaping it, and how prepared is your organization to make that leap? Useful Links Connect with Simon Noble Learn more about Cezanne HR Tech Talks Daily is Sponsored by Denodo

What does it really mean when AI moves from answering questions to making decisions that affect real people, real money, and real outcomes? In this episode of Tech Talks Daily, I'm joined by Joe Kim, CEO of Druid AI, for a grounded conversation about why agentic AI is becoming the focus for enterprises that have moved beyond experimentation. After years of hype around generative tools, many organizations are now facing a tougher question. Can AI be trusted to take action inside core business processes, and can it do so with the accuracy, security, and accountability that enterprises expect? Joe brings a rare perspective shaped by decades leading large-scale enterprise software companies, including his time as CEO of Sumo Logic. He explains why Druid AI deliberately avoids positioning itself as a generative AI company, and instead focuses on systems that can make decisions, trigger workflows, and complete tasks inside regulated, high-stakes environments. We unpack why accuracy thresholds matter when AI touches billing, healthcare, admissions, or compliance, and why security and governance are no longer secondary concerns once AI is allowed to act. We also talk about scale and proof. Druid AI now supports over 120 million conversations every month, a figure that keeps climbing as enterprises move agentic systems into production. Joe shares how those conversations translate into measurable business outcomes, from operational efficiency to revenue growth, and why many AI initiatives fail to reach this stage. His "5 percent club" philosophy cuts through the noise, focusing on the small number of use cases that actually deliver return while most others stall in pilots. The conversation also explores why higher education has become a surprising pressure point for AI adoption, how outdated systems contribute to student churn, and how conversational agents can remove friction at moments that decide whether someone enrolls, stays, or leaves. We close by looking ahead at Druid AI's next chapter, including new platform capabilities designed to make building and deploying agents faster without sacrificing control. As more enterprises demand results instead of promises, are we ready to judge AI by the decisions it makes and the outcomes it delivers, and what should that accountability look like in your organization? I'd love to hear your thoughts. Where do you see agentic AI delivering real value today, and where do you think the risks still outweigh the rewards? What does it really mean when AI moves from answering questions to making decisions that affect real people, real money, and real outcomes? In this episode of Tech Talks Daily, I'm joined by Joe Kim, CEO of Druid AI, for a grounded conversation about why agentic AI is becoming the focus for enterprises that have moved beyond experimentation. After years of hype around generative tools, many organizations are now facing a tougher question. Can AI be trusted to take action inside core business processes, and can it do so with the accuracy, security, and accountability that enterprises expect? Joe brings a rare perspective shaped by decades leading large-scale enterprise software companies, including his time as CEO of Sumo Logic. He explains why Druid AI deliberately avoids positioning itself as a generative AI company, and instead focuses on systems that can make decisions, trigger workflows, and complete tasks inside regulated, high-stakes environments. We unpack why accuracy thresholds matter when AI touches billing, healthcare, admissions, or compliance, and why security and governance are no longer secondary concerns once AI is allowed to act. We also talk about scale and proof. Druid AI now supports over 120 million conversations every month, a figure that keeps climbing as enterprises move agentic systems into production. Joe shares how those conversations translate into measurable business outcomes, from operational efficiency to revenue growth, and why many AI initiatives fail to reach this stage. His "5 percent club" philosophy cuts through the noise, focusing on the small number of use cases that actually deliver return while most others stall in pilots. The conversation also explores why higher education has become a surprising pressure point for AI adoption, how outdated systems contribute to student churn, and how conversational agents can remove friction at moments that decide whether someone enrolls, stays, or leaves. We close by looking ahead at Druid AI's next chapter, including new platform capabilities designed to make building and deploying agents faster without sacrificing control. As more enterprises demand results instead of promises, are we ready to judge AI by the decisions it makes and the outcomes it delivers, and what should that accountability look like in your organization? I'd love to hear your thoughts. Where do you see agentic AI delivering real value today, and where do you think the risks still outweigh the rewards? Useful Links Connect with Joe Kim, CEO of Druid AI. Druid AI Website Tech Talks Daily is Sponsored by Denodo  

The world is building data centers, identity rails, and AI policy stacks at a speed that makes 2026 feel closer than it is. In this conversation, Rajesh Natarajan, Global Chief Technology Officer at Gorilla Technology Group, explains what it takes to engineer platforms that remain reliable, secure, and sovereign-ready for decades, especially when infrastructure must operate outside the safety net of constant cloud connectivity. Raj talks about quantum-safe networking as a current risk, not a future headline. Adversaries are capturing encrypted traffic today, betting on decrypting it later, and retrofitting quantum-safe architecture into national platforms mid-lifecycle is an expensive mistake waiting to happen. He also highlights the regional nature of AI infrastructure, Southeast Asia prioritizing sovereignty, speed, and efficiency, Europe leaning on regulation and telemetry, and the U.S. betting on raw cluster scale and throughput. Sustainability at Gorilla isn't a marketing headline, it's an engineering requirement. If a system can't prove its environmental impact using telemetry like workload-level PUE, it isn't labeled sustainable internally. Gorilla applies the same rigor to IoT insight per unit of energy, device lifecycles, and edge-level intelligence placement, minimizing data centralization without operational justification. This episode offers marketers, founders, and technology leaders a rare chance to understand what national-scale resilience looks like when platform alignment breaks first, not technology. Remembering that decisions must be reversible, explicit, and measurable is the foundation of how Gorilla is designing systems that can evolve without forcing rushed compromises when uncertainty becomes reality. Useful links: Connect with Dr Rajesh Natarajan Gorilla website Tech Talks Daily is Sponsored by Denodo