The Tech Blog Writer Podcast

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

Here's the thing. Most enterprise AI talk today starts with chatbots and ends with glossy demos. Meanwhile, the data that actually runs a business lives in rows, columns, and time stamps. That gap is where my conversation with Vanja Josifovski, CEO of Kuma.ai, really comes alive. Vanja has spent two and a half decades helping companies turn data into decisions, from research roles at Yahoo and Google to steering product and engineering at Pinterest through its IPO and later leading Airbnb Homes. He's now building Kuma.ai to answer an old question with a new approach: how do you get accurate, production-grade predictions from relational data without spending months crafting a bespoke model for each use case? Vanja explains why structured business data has been underserved for years. Images and text behave nicely compared to the messy reality of multiple tables, mixed data types, and event histories. Traditional teams anticipate a prediction need, then kick off a long feature engineering and modeling process. Kuma's Relational Foundation Model, or RFM, flips that script. Pre-trained on a large mix of public and synthetic data warehouses, it delivers task-agnostic, zero-shot predictions for problems like churn and fraud. That means you can ask the model questions directly of your data and get useful answers fast, then fine-tune for another 15 to 20 percent uplift when you're ready to squeeze more from your full dataset. What stood out for me is how Kuma removes the grind of manual feature creation. Vanja draws a clear parallel to computer vision's shift years ago, when teams stopped handcrafting edge detectors and started learning from raw pixels. By learning directly from raw tables, Kuma taps the entirety of the data rather than a bundle of human-crafted summaries. The payoff shows up in the numbers customers care about, with double-digit improvements against mature, well-defended baselines and the kind of time savings that change roadmaps. One customer built sixty models in two weeks, a job that would typically span a year or more. We also explore how this fits with the LLM moment. Vanja doesn't position RFM as a replacement for language models. He frames it as a complement that fills an accuracy gap on tabular data where LLMs often drift. Think of RFM as part of an agentic toolbox: when an agent needs a reliable prediction from enterprise data, it can call Kuma instead of generating code, training a fresh model, or bluffing an answer. That design extends to the realities of production as well. Kuma's fine-tuning and serving stack is built for high-QPS environments, the kind you see in recommendations and ad tech, where cost and latency matter. The training story is another thread you'll hear in this episode. The team began with public datasets, then leaned into synthetic data to cover scenarios that are hard to source in the wild. Synthetic generation gives them better control over distribution shifts and edge cases, which speeds iteration and makes the foundation model more broadly capable upon arrival. If you care about measurable outcomes, this episode shows why CFOs pay attention when RFM lands. Vanja shares examples where a 20 to 30 percent lift translates into hundreds of thousands of additional monthly active users and direct revenue impact. That kind of improvement isn't theory. It's the difference between a model that nudges a metric and a model that moves it. By the end, you'll have a clear picture of what Kuma.ai is building, why relational data warrants its own foundation model, and how enterprises can move from wishful thinking to practical wins. Curious to try it yourself? Vanja also points to a sandbox where teams can load data and ask predictive questions within a notebook, then compare results against in-house models. If your AI plans keep stalling on tabular reality, this conversation offers a way forward that's fast, accurate, and designed for the systems you already run.

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

At VMware Explore in Las Vegas, the buzz wasn't just about generative AI, but about where and how it should run. My guest is Tasha Drew, Director of Engineering for the AI team in the VMware Cloud Foundation division at Broadcom, who has been at the center of this conversation. Fresh off the main stage, where she helped debut VMware's new Private AI Services and Intelligent Assist for VMware Cloud Foundation, Tasha joins me to unpack what these announcements mean for enterprises grappling with privacy, cost, and integration challenges. Tasha explains why private AI is resonating so strongly in 2025, outlining the three pillars that define it: protecting sensitive intellectual property, managing regulated or high-value data, and ensuring role-based control of fine-tuned models. She shares how organizations often start their AI journey in the public cloud, but as experimentation turns to production, cost pressures, data compliance, and proximity to data drive them toward private AI. We also dive into VMware's own evolution toward building an AI-native private cloud platform. Tasha highlights the journey from deep learning VMs and Jupyter notebooks to full AI platform services that empower IT teams to deliver models efficiently, save money, and accelerate deployment of retrieval-augmented generation (RAG) applications. She introduces Intelligent Assist for VMware Cloud Foundation, an AI-powered guide that helps teams navigate complex deployments with context-aware support and step-by-step instructions. Beyond the technology, Tasha reflects on the broader ecosystem shifts, from partnerships with NVIDIA and AMD to the role of Model Context Protocol (MCP) in breaking down integration barriers between enterprise systems. She believes MCP represents a turning point, enabling seamless workflows between platforms that historically lacked incentive to work together. This conversation captures a pivotal moment where private AI is moving from theory into enterprise adoption. For leaders weighing their next move, Tasha provides both the strategic framing and the technical insight to understand why private AI has become one of the most talked-about forces shaping enterprise IT today.

Factories don't usually make headlines at tech conferences, but what Audi is doing inside its production labs is anything but ordinary. At VMware Explore in Las Vegas, I sat down with Dr. Henning Löser, Head of the Audi Production Lab, to talk about how the automaker is reinventing its factory floor with a software-first mindset. Henning leads a small team he jokingly calls “the nerds of production,” but their work is changing how cars are built. Instead of replacing entire lines for every new piece of technology, Audi has found a way to bring the speed and flexibility of IT into the world of industrial automation. The result is Edge Cloud 4 Production, a system that takes virtualization technology normally reserved for data centers and applies it directly to manufacturing. In our conversation, Henning explained why virtual PLCs may be one of the biggest breakthroughs yet. They look invisible to workers on the line but give maintenance teams new transparency and resilience. We explored how replacing thousands of industrial PCs with centralized, virtualized workloads not only reduces downtime but also cuts energy use and simplifies updates. And yes, we even discussed the day a beaver chewed through one of Audi's fiber optic cables and how redundancy kept production running without a hitch. This episode is about more than smart factories. It's about how an industry known for heavy machinery is learning to think like the cloud. From scalability and sustainability to predictive maintenance and AI-ready infrastructure, Audi is showing how the car of the future starts with the factory of the future. If you've ever wondered how emerging technologies like virtualization and private cloud are reshaping the shop floor, this is a story you'll want to hear.

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

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

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

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

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

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

What do you do when your technical brilliance doesn't translate into clear, compelling communication? That's where Salvatore Manzi comes in. With a background in business communication and a career spent coaching leaders across tech, finance, and global policy, Salvatore helps bold thinkers bring clarity and connection to even the most complex ideas. In this episode, we talk about the communication challenges that many technical leaders face—especially when speaking to non-technical stakeholders. Whether you're leading a product team, presenting in a high-stakes board meeting, or trying to assert your voice in a fast-paced discussion, Salvatore offers practical strategies that go far beyond public speaking tips. His insights are grounded in two decades of real-world experience, from coaching TEDx speakers and United Nations delegates to guiding SVPs through business model pivots and helping raise hundreds of millions in funding. We explore how data-driven leaders can use storytelling without compromising accuracy, how to manage energy and presence when nerves kick in, and what leadership looks like when you lean more analytical than charismatic. Salvatore shares a refreshing take on body language, framing it not as performance but as a tool for genuine alignment between your message and your intention. We also dig into the nuance of communicating uncertainty—how to be honest and credible without losing influence. For anyone in a technical role looking to lead more effectively, this episode is packed with insight. Salvatore's mission is to help people speak with clarity and lead with authenticity. After this conversation, you may just find yourself doing both a little differently.

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

As AI tools become increasingly embedded in the workplace, the future of work hangs in a delicate balance between automation and opportunity. In this episode, J.D. Seraphine, founder and CEO of Raiinmaker, joins Neil to challenge the dominant narrative of AI-driven job loss. Instead, he offers a bold vision—one where technology enhances human creativity, not replaces it. J.D. shares how Raiinmaker is merging Web3 and AI to build platforms that reward human contribution, decentralize value, and give people a voice in shaping the future of artificial intelligence. We explore what it means to create ethical, human-led AI systems, how businesses can support young workers through upskilling and mentorship, and why the biggest challenge may not be employee readiness—but leadership inertia. From entry-level displacement to data ethics, from complementary currencies to AI-generated video training, this conversation goes far beyond the hype. J.D. also speaks candidly about the real risks ahead—alongside the unprecedented potential for a new kind of economic empowerment.

David Hawig never set out to work in blockchain. He began his career in health tech, drawn to the potential of scaling impactful solutions. But it was the promise of a more transparent and user-controlled internet that ultimately led him to the Web3 Foundation, where he now serves as Director of Ecosystem Development and Investor Relations. In our conversation on the Tech Talks Daily Podcast, David shares why Web3 is not just a trend or buzzword, but a complete rethink of how digital systems should function. He describes a world where users own their data, can verify transactions without relying on central authorities, and can move between services without friction. To David, the Web3 movement is not about hype or speculation. It's about enabling a future where the internet is built on truth, not trust. At the heart of the Web3 Foundation's work is Polkadot, a protocol designed to solve the scalability and interoperability challenges that plague many early blockchain networks. David explains that Polkadot's sharded infrastructure allows workloads to be split across participants in a trustless way. This setup not only enables more transactions but positions the ecosystem to support millions of users as mainstream adoption accelerates. That acceleration, he argues, is already happening. Thanks to new regulations like the Clarity Act and Genius Act in the US, enterprise adoption is becoming a reality. Where Web3 once attracted only startups and crypto-native communities, today major companies, including sports brands and entertainment groups, are actively building in the space. Unlike earlier efforts that felt more like PR stunts, these companies now see tangible benefits. Web3 can deliver faster, cheaper, and more flexible digital services, available 24/7, with no lock-in to single vendors. David is especially passionate about removing the barriers that have made Web3 feel intimidating to the average user. While early blockchain projects often demanded technical knowledge and wallet key management, he sees a future where users interact with Web3 products as easily as they would a mobile app. Behind the scenes, cryptography and decentralization are doing the heavy lifting, but from the user's perspective, the experience is seamless. One area David is particularly excited about is decentralized storage. As more businesses realize the risks of relying on centralized cloud giants, alternatives are emerging that offer both cost advantages and greater control. He sees this as a critical part of the broader shift toward self-sovereign infrastructure. When asked if large corporations truly understand the scale of the disruption ahead, David is cautious but optimistic. Many established players, he says, still underestimate how quickly network effects can take hold. Once enough users and companies move into Web3 ecosystems, the old models will no longer be competitive. Whether it's financial services, social media, or identity management, the shift toward user-owned infrastructure will be difficult to reverse. Looking ahead to 2026 and beyond, David points to the upcoming Jam upgrade as a major milestone. This next evolution of the Polkadot network is designed to dramatically improve scalability, supporting not just crypto-native transactions but also broader use cases in gaming, ticketing, payments, and more. The goal is clear: create a robust, low-cost, interoperable infrastructure capable of supporting millions of users across different networks and applications. Before signing off, David leaves listeners with a recommendation. He suggests reading Man's Search for Meaning by Viktor Frankl, a book he returns to often when reflecting on motivation and purpose. It's a fitting choice for someone working at the edge of one of the most transformative shifts in modern tech. The Web3 Foundation is not just funding protocols or building tools. It's laying the groundwork for a future where the internet belongs to everyone. And if David's predictions are right, that future may arrive faster than we think.

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

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

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

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

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

AI is finding its way into almost every corner of customer service, but is it really what customers want? According to Kinsta's recent survey, the answer is overwhelmingly no. An incredible 93 percent of respondents said they would rather speak to a human than an AI chatbot when they need support. Nearly half even said they would cancel a service if it relied solely on AI-driven support. In this episode, Roger Williams, Community Manager at Kinsta, breaks down the story behind those numbers and explains why his team continues to invest heavily in human-first support. Kinsta has built its reputation on 24/7 access to real engineers who understand the complexities of WordPress hosting, resulting in a 98 percent customer satisfaction score and consistently high ratings on platforms like G2 and Trustpilot. Roger shares how Kinsta blends human expertise with AI tools in a way that enhances, rather than replaces, the customer experience. He talks about the role empathy plays in building trust, the importance of empowering support staff to own conversations, and why support should be viewed as an opportunity to strengthen relationships rather than just a cost to be reduced. We also discuss the growing perception that AI in support is more about saving money than improving service, how business leaders can avoid falling into that trap, and what the future of open web hosting could look like as AI capabilities mature. Whether you are in tech leadership, run a customer-facing team, or simply value a good support experience, this conversation offers insights that go beyond the AI hype and focus on what truly matters to customers.

In a business climate shaped by rapid technological disruption, shifting geopolitical landscapes, and evolving customer expectations, strategy cannot remain static. JD Carter, Chief Strategy Officer at Vasion, believes the key to success lies in constantly aligning vision with execution while adapting to market realities in real time. In this conversation, JD shares how his role involves continuously monitoring external signals such as technology shifts, regulatory changes, and economic pressures, then translating those insights into operational action. We explore his approach to looking beyond the company vision by breaking it down into achievable missions that link long-term goals with day-to-day work across cross-functional teams. A major focus of the discussion is AI readiness and how organisations can move beyond hype to real impact. JD outlines a five-stage process for becoming AI-ready, starting with digitising and centralising documents and data, followed by cleaning and structuring information for use with large language models. He explains how automating repetitive workflows, modernising infrastructure, and ensuring interoperability across systems such as ERP and HR platforms create the foundation for orchestrated automation at scale. Governance and access controls complete the picture, ensuring that AI deployment meets both internal and regulatory standards. We also look at how Vasion balances short-term market needs with a long-term platform vision. JD describes how leveraging the company's market-leading print infrastructure products supports current growth, while investing in R&D drives the development of a multi-product SaaS platform designed to integrate AI across the enterprise. A customer-first mindset shapes every decision, from pricing to product development, with continuous engagement through advisory boards, surveys, and direct conversations ensuring that partner strategies align with customer priorities. To illustrate these principles in action, JD shares how Vasion responded to market demand for system-generated print job support by developing a SaaS-based output automation product. This pivot addressed a gap created by ERP and EMR vendors moving customers to the cloud and positioned Vasion at the start of its multi-product journey. We discuss the signals leaders should watch to keep strategy relevant, including shifts in customer behaviour, the pace of technology adoption, and internal friction that may indicate misalignment. JD likens strategy to a GPS system, with vision as the destination and constant recalibration required to navigate roadblocks and changing conditions. The conversation closes with a focus on embedding strategic agility into company culture. JD explains Vasion's Missions of Aspirational Performance system, which connects corporate values directly to execution by breaking down strategic goals into work that individuals can see contributing to the bigger picture. He also shares his personal three-pronged approach to continuous learning, combining formal education, informal learning, and mentor-driven guidance. This episode offers practical insight for leaders navigating uncertainty, balancing present-day demands with future opportunity, and embedding adaptability into the DNA of their organisations.

MariaDB is a name with deep roots in the open-source database world, but in 2025 it is showing the energy and ambition of a company on the rise. Taken private in 2022 and backed by K1 Investment Management, MariaDB is doubling down on innovation while positioning itself as a strong alternative to MySQL and Oracle. At a time when many organisations are frustrated with Oracle's pricing and MySQL's cloud-first pivot, MariaDB is finding new opportunities by combining open-source freedom with enterprise-grade reliability. In this conversation, I sit down with Vikas Mathur, Chief Product Officer at MariaDB, to explore how the company is capitalising on these market shifts. Vikas shares the thinking behind MariaDB's renewed focus, explains how the platform delivers similar features to Oracle at up to 80 percent lower total cost of ownership, and details how recent innovations are opening the door to new workloads and use cases. One of the most significant developments is the launch of Vector Search in January 2023. This feature is built directly into InnoDB, eliminating the need for separate vector databases and delivering two to three times the performance of PG Vector. With hardware acceleration on both x86 and IBM Power architectures, and native connectors for leading AI frameworks such as LlamaIndex, LangChain and Spring AI, MariaDB is making it easier for developers to integrate AI capabilities without complex custom work. Vikas explains how MariaDB's pluggable storage engine architecture allows users to match the right engine to the right workload. InnoDB handles balanced transactional workloads, MyRocks is optimised for heavy writes, ColumnStore supports analytical queries, and Moroonga enables text search. With native JSON support and more than forty functions for manipulating semi-structured data, MariaDB can also remove the need for separate document databases. This flexibility underpins the company's vision of one database for infinite possibilities. The discussion also examines how MariaDB manages the balance between its open-source community and enterprise customers. Community adoption provides early feedback on new features and helps drive rapid improvement, while enterprise customers benefit from production support, advanced security, high availability and disaster recovery capabilities such as Galera-based synchronous replication and the MacScale proxy. We look ahead to how MariaDB plans to expand its managed cloud services, including DBaaS and serverless options, and how the company is working on a “RAG in a box” approach to simplify retrieval-augmented generation for DBAs. Vikas also shares his perspective on market trends, from the shift away from embedded AI and traditional machine learning features toward LLM-powered applications, to the growing number of companies moving from NoSQL back to SQL for scalability and long-term maintainability. This is a deep dive into the strategy, technology and market forces shaping MariaDB's next chapter. It will be of interest to database architects, AI engineers, and technology leaders looking for insight into how an open-source veteran is reinventing itself for the AI era while challenging the biggest names in the industry.

In this episode, I am joined by Charles Southwood, Regional GM of Denodo Technologies, a company recognised globally for its leadership in data management. With revenues of $288M and a customer base that includes Hitachi, Informa, Engie, and Walmart, Denodo sits at the heart of how enterprises access, trust, and act on their data. Charles brings over 35 years of experience in the tech industry, offering both a long-term view of how the data landscape has evolved and sharp insights into the challenges businesses face today. Our conversation begins with a pressing issue for any organisation exploring generative AI: data reliability. With many AI models trained on vast amounts of internet content, there is a real risk of false information creeping into business outputs. Charles explains why mitigating hallucinations and inaccuracies is essential not just for technical quality, but for protecting brand reputation and avoiding costly missteps. We explore alternative approaches that allow enterprises to benefit from AI innovation while maintaining data integrity and control. We also examine the broader enterprise pressures AI has created. The promise of reduced IT costs and improved agility is enticing, but how much of this is achievable today and how much is inflated by hype? Charles shares why he believes 2025 is a tipping point for achieving true business agility through data virtualisation, and what a virtualised data layer can deliver for teams across IT, marketing, and beyond. Along the way, Charles reflects on the industry shifts that caught him most by surprise, the decisions he would make differently with the benefit of hindsight, and the one golden rule he would share with younger tech professionals starting their careers now. This is a conversation for anyone who wants to understand how to harness AI and advanced data integration without falling into the traps of poor data quality, overblown expectations, or short-term thinking.

In the movies, Tony Stark's JARVIS is the ultimate AI assistant, managing schedules, running simulations, controlling environments, and anticipating needs before they are voiced. In reality, today's AI agents are still far from that vision. Despite 2025 being heralded as the year of agentic AI, the first offerings from major players have been underwhelming. They can perform tasks, but they remain a long way from the seamless, hyper-intelligent assistants we imagined. In this episode, Dr. Robert “Bobby” Blumofe, CTO at Akamai Technologies, joins me to explore what is really holding AI assistants back and what it will take to build one as capable as a top human executive assistant. Bobby argues that the leap forward will not come from chasing ever-larger models but from optimization, efficiency, and integrating AI with the right tools, infrastructure, and processes. He believes that breakthroughs in model efficiency, like those seen in DeepSeek, could make capable agents affordable and viable for everyday use. We break down the spectrum of AI agents from simple, task-specific helpers to the fully autonomous, general-purpose vision of JARVIS. Bobby shares why many of the most valuable enterprise applications will come from the middle ground, where agents are semi-autonomous, task-focused, and integrated with other systems for reliability. He also explains why smaller, specialized models often outperform “ask me anything” LLMs for specific business use cases, reducing cost, latency, and security risks. The conversation covers Akamai's role in enabling low-latency, scalable AI at the edge, the importance of combining neural and symbolic AI to achieve reliable reasoning and planning, and a realistic five-to-seven-year timeline for assistants that can rival the best human EAs. We also look at the technical, social, and business challenges ahead, from over-reliance on LLMs to the ethics of deploying highly capable agents at scale. This is a grounded, forward-looking discussion on the future of AI assistants, where they are today, why they have fallen short, and the practical steps needed to turn fiction into reality.

Multi-agent AI systems are moving from theory to enterprise reality, and in this episode, Babak Hodjat, CTO of AI at Cognizant, explains why he believes they represent the future of business. Speaking from his AI R&D lab in San Francisco, Babak outlines how his team is both deploying these systems inside Cognizant and helping clients build their own, breaking down organisational silos, coordinating processes, and improving decision-making. We discuss how the arrival of optimized, open-source models like DeepSeek is accelerating AI democratization, making it viable to run capable agents on far smaller infrastructure. Babak explains why this is not a “Sputnik moment” for AI, but a powerful industry correction that opens the door for more granular, cost-effective agents. This shift is enabling richer, more scalable multi-agent networks, with agents that can not only perform autonomous tasks but also communicate and collaborate with each other. Babak also introduces Cognizant's open-sourced Neuro-AI Network platform, designed to be model and cloud agnostic while supporting large-scale coordination between agents. By separating the opaque AI model from the fully controllable code layer, the platform builds in safeguards for trust, data handling, and access control, addressing one of the most pressing challenges in AI adoption. Looking ahead, Babak predicts rapid growth in multi-agent ecosystems, including inter-company agent communication and even self-evolving agent networks. He also stresses the importance of open-source collaboration in AI's next chapter, warning that closed, proprietary approaches risk slowing innovation and eroding trust. This is a deep yet accessible conversation for anyone curious about how enterprise AI is evolving from single, monolithic models to flexible, distributed systems that can adapt and scale. You can learn more about Cognizant's AI work at cognizant.com and follow Babak's insights on LinkedIn.

AI adoption in the tech sector has reached a tipping point, and the latest EY Technology Pulse poll offers a fascinating look at just how quickly things are moving. In this episode, I'm joined by Ken Englund, Partner at EY, to unpack the survey's findings and what they reveal about the next two years of AI in enterprise. Conducted with 500 senior tech executives from companies with more than 5,000 employees, the poll focuses on AI agents, autonomous deployments, and the shifting priorities that are shaping investment strategies. Ken shares why half of the respondents expect more than 50% of their AI deployments to be fully autonomous within 24 months, and why optimism around AI's potential remains high. He also explains a notable shift away from last year's heavy focus on large language models toward applied AI and agentic systems designed to handle real-world business workflows. While 92% of tech leaders plan to increase AI spending in 2026, the investment isn't solely about technology—it's about competitiveness, customer experience, and strategic alignment. One of the more surprising takeaways is the human side of the equation. Despite headlines predicting widespread job losses, only 9% of respondents anticipate layoffs in the next six months, down from 20% last year. Instead, companies are balancing upskilling existing staff with bringing in new AI talent, with roles emerging in areas like MLOps, AI product management, and forward-deployed engineering. Ken and I also dive into the growing weight of governance, data privacy, and security. With autonomous agents becoming more embedded in core operations, boards, CFOs, and audit teams are taking a closer look at trust frameworks without wanting to slow innovation. The conversation highlights a critical inflection point: most companies are still in the “automating existing workflows” phase, but the real breakthroughs will come when AI enables entirely new business models. This episode is a snapshot of a sector in rapid evolution—where enthusiasm is tempered by lessons learned, and where the road from pilot to production is still full of challenges. You can read the full EY Technology Pulse poll here.

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

Electric vehicles promise a cleaner future, but battery performance remains one of the biggest bottlenecks. In this episode, Tim Holme, co-founder and CTO of QuantumScape, takes us inside the company's mission to build a new generation of solid-state lithium-metal batteries that could change the game for EVs and beyond. Tim explains why the industry has been stuck with incremental improvements to lithium-ion for decades and why replacing the graphite anode with lithium metal could unlock longer range, under-15-minute charging, and improved safety. He shares how QuantumScape's ceramic separator prevents the dendrite formation that has held back lithium-metal designs, and why this innovation can make batteries both more energy-dense and safer, even under extreme conditions. We also discuss the company's recent “COBRA” manufacturing breakthrough, which has increased separator production speed by roughly 200 times. This leap is key to scaling production for automotive partners like Volkswagen's PowerCo and Murata. Tim outlines how QuantumScape is approaching commercialization through a capital-light licensing model, avoiding the pitfalls that have caused other U.S. battery innovations to be commercialized overseas. Beyond electric vehicles, Tim sees untapped potential for solid-state batteries in grid-scale storage and at EV charging stations, where they could buffer demand and reduce grid strain. He also reflects on the global battery race, why careful partner selection is essential for protecting IP, and how the U.S. can maintain leadership in next-generation energy storage. Whether you are interested in battery chemistry, clean tech innovation, or the business of scaling breakthrough hardware, Tim offers a rare look at the science, strategy, and partnerships shaping the future of energy storage.

Tax season scams are nothing new, but David Maimon is tracking a worrying evolution. As head of Fraud Insights at SentiLink and a professor of fraud intelligence at Georgia State University, David has been studying how organised crime groups are now blending stolen identities with generative AI and deepfake technology to outpace traditional security measures. In this conversation, he explains how identities from some of the least likely victims, including death row inmates, are being exploited to open neobank accounts, set up fake businesses, and run sophisticated bust-out schemes with a low risk of detection. David breaks down how these operations work, from creating synthetic identities using stolen Social Security numbers to manufacturing convincing documents and faces that can pass liveness checks. He reveals the telltale signs his team uncovered, such as shared physical addresses, legacy email domains, and consistent digital fingerprints that point to coordinated fraud rings. With tools like DeepFaceLive, Avatarify, and cloned voices now being deployed to bypass authentication, he warns that the gap between criminal innovation and institutional defences can be as wide as 7 to 12 months. We also explore why financial institutions struggle to detect these scams early, and why layered verification, combining real-time checks with historical identity analysis, is essential. David shares the threats on the horizon, from increasingly realistic AI-generated images to voice cloning attacks, and stresses the need for both technological solutions and public awareness to slow the momentum of these schemes. Whether you work in banking, cybersecurity, or simply want to protect your own identity, this episode offers a rare look inside the tactics, tools, and vulnerabilities shaping the next wave of financial fraud. And yes, there is still time at the end for a great book recommendation and a classic Tom Petty track.

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

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

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

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

In this episode of Tech Talks Daily, I caught up with Raj Samani, Chief Scientist at Rapid7, to unpack the rapidly evolving world of ransomware. Raj has been on the front lines of cybercrime response for years and has seen firsthand how these attacks have professionalized. Gone are the days of casual ransomware notes asking for a few hundred dollars. Today, these groups operate like fully formed businesses with help desks, R&D teams, and carefully designed extortion models. We talked about how ransomware has become a reputational risk issue more than just a technical one. Raj shared that CEOs are often more concerned about data being exfiltrated and leaked to the press than they are about systems being locked down. It's no longer just about recovering files. It's about trust, public perception, and the long tail of brand damage. One of the most revealing parts of our discussion was how these attacks typically unfold. Raj walked me through real-world scenarios where criminals have remained inside networks for months, even years, before launching their final payload. He also described how careful planning, coordinated strike days, and threat intelligence can disrupt an attacker's kill chain before irreversible damage is done. We explored the uncomfortable truth that many organizations still fall victim to basic attacks because of poor cyber hygiene. While the threat landscape is becoming more sophisticated with the use of zero-day vulnerabilities and social engineering, many breaches still happen through exposed RDP ports or convincing phishing attempts. Raj also offered candid insights into the ethics and complexities of ransomware negotiations, why outright banning payments may backfire, and what companies should do in the first few hours after discovering they've been hit. He made it clear that cybersecurity is no longer just an IT issue. It affects everything from supply chains to public services and daily life. Is your organization prepared for the moment when ransomware moves from IT's concern to the boardroom's crisis?

n this episode of Tech Talks Daily, I'm joined by Mohib Yousufani, a senior partner at PwC who leads growth, turnaround, and digital transformation initiatives for Fortune 500 companies. Mohib brings a sharp focus on value creation, helping business leaders move beyond technology hype to deliver measurable outcomes through thoughtful digital strategies. Our conversation begins with a hard truth: many companies are confusing technology adoption with business outcomes. Mohib shares how organizations often rush to embrace the latest AI trends or automation tools without first identifying the core problems they need to solve. That misalignment, he explains, is why many digital transformation efforts stall or fail to scale beyond pilot mode. Mohib breaks down PwC's approach to digital transformation, which begins by translating enterprise ambition into actionable plans. We explore how aligning business unit goals, operating models, and leadership behavior is critical to successful implementation. He also offers a candid view of why so many projects suffer from process debt and legacy friction, often ignoring the people and culture dynamics that are central to lasting change. One of the most powerful parts of our discussion centers on how to evaluate ROI. Instead of focusing solely on cost savings, Mohib suggests expanding the lens to include revenue growth, time to market, risk mitigation, and strategic agility. He shares a compelling success story involving a CPG company that used AI and data science to optimize trade promotions and pricing, resulting in a three percent revenue lift and two percent margin expansion. We also talk about leadership's role in setting the tone. Culture, Mohib emphasizes, acts as a multiplier. Without executive alignment and clear behavioral modeling, even the most sophisticated tools won't deliver the promised value. If your organization is rethinking digital strategy, this episode is packed with insights to help you move from experimentation to real business impact. Are you building digital solutions that scale beyond buzzwords?

In this episode of Tech Talks Daily, I sat down with Fred Helou, founder and CEO of Vagaro, a platform reshaping how service-based businesses in the beauty, wellness, and fitness sectors operate in a digital world. What began as an idea sparked by a frustrating haircut booking experience during a business trip to Korea has evolved into a platform used by over 250,000 professionals worldwide. Fred walked me through his journey from developing the concept in 1999 to officially launching Vagaro in 2009 after being laid off during the financial crisis. Along the way, he navigated shifting technology trends, from desktop tools to mobile apps and now artificial intelligence. At its core, Vagaro has always aimed to be a digital assistant for its users, allowing solopreneurs and large enterprises alike to focus on their craft while automation handles the rest. Our conversation explored how AI is quietly transforming the day-to-day operations of small businesses. From writing emails and responding to reviews to answering customer chats and booking appointments in real time, Vagaro's AI tools are making it easier for service providers to grow without hiring additional staff. Fred outlined a future where professionals simply set goals for their schedule and let AI optimize bookings, promotions, and customer engagement around the clock. What stood out was Fred's commitment to enhancing—not replacing—the human experience. He spoke candidly about the irreplaceable role of the hairdresser or personal trainer and why no one wants scissors near their neck managed by a robot. Instead, the platform empowers professionals with enterprise-grade tools once out of reach for smaller operators. Fred also shared how his experience growing up during the Lebanese Civil War shaped his resilience as a founder. That perspective has influenced Vagaro's long-term approach to product development, culture, and navigating uncertainty. As AI evolves from assistance to autonomy, how is your business preparing to scale without losing the human touch that sets it apart?

In today's episode of Tech Talks Daily, I sat down with Andy Bell, Head of Data Product Management at Precisely, to explore a challenge that many organizations continue to underestimate: the role of data integrity in AI strategies. With only 12 percent of businesses expressing confidence in the quality of their AI data, it's clear that the rush to implement AI is often outpacing the readiness of the data that supports it. Andy and I unpack what happens when enterprises leap into generative or agentic AI without addressing foundational data issues. From hallucinations to bias to unreliable outputs, the risks are significant. As we discussed, these risks don't just impact models — they erode trust with customers and complicate accountability, especially in regulated industries where traceability is non-negotiable. We then explored the power of third-party data enrichment and how it can offer much-needed context that internal datasets often lack. Andy shared real-world examples, including how a major delivery company saved 65 million dollars by optimizing address accuracy and how San Bernardino County used Precisely's wildfire risk models to improve emergency planning. These aren't abstract use cases — they show measurable business value. Andy also introduced the Precisely Data Link program, a solution designed to make it easier to connect, manage, and query multiple third-party datasets. With persistent IDs and flexible delivery methods through APIs, managed services, and platforms like Snowflake and Databricks, Precisely is helping organizations speed up time to value while reducing integration headaches. Looking ahead, Andy shared how Precisely is building AI capabilities that allow users to query third-party data using natural language. This shift aims to make complex data interactions more intuitive and accessible to business users who may not be data engineers. If data is the fuel for AI, then the quality and context of that data will define the road ahead. Is your organization doing enough to ensure its data can be trusted by the AI it deploys?

In this episode of Tech Talks Daily, I sat down with Joseph Landes, co-founder and Chief Revenue Officer at Nerdio, to explore how one conversation at a Microsoft conference led to a billion-dollar cloud automation company. From his 23-year career at Microsoft to building a fully remote team now supporting over five million users, Joseph's story blends strategic risk-taking with deep industry insight. We unpacked how Nerdio grew from a startup idea in 2018 to a company that just secured 500 million dollars in Series C funding. Joseph walked me through the early days of building the business alongside co-founder Vadim Vladimirsky and how they focused on simplifying Microsoft Azure for IT professionals and MSPs. Their goal was clear: make cloud management easier, faster, and more cost-effective through automation and policy-driven governance. But this episode wasn't just about cloud optimization. We also dug into Nerdio's fully remote culture and the intentional design behind it. Joseph shared how initiatives like appointing city mayors, launching the Nerdio Break Room, and hosting an annual global kickoff have helped maintain a strong sense of community and accountability across 350 remote employees. We also discussed why Nerdio does not compete with Microsoft. It enhances and extends Microsoft's products, helping customers navigate Azure complexity while staying aligned with Microsoft's fast-changing roadmap. This customer-centric strategy, coupled with deep product knowledge and agility, has been key to Nerdio's ability to scale without losing focus. Looking ahead, Joseph shared his perspective on why AI and continuous cost optimization will shape the future of enterprise IT. He made a strong case for simplifying IT operations, empowering professionals, and turning savings into reinvestment opportunities. In an era of complexity and noise, Nerdio's growth story is a reminder of what can happen when you combine deep platform expertise with a culture that truly listens. How is your organization turning cloud complexity into an advantage rather than a barrier?

The training room is changing, and it's not going back. In this episode, I sat down with Phil Friedman, the founder and CEO of CGS Inc., to explore how AI, avatars, and immersive simulations are rewriting the playbook on workplace training. With over four decades at the helm of CGS—a company he built from scratch after immigrating to the US—Phil brings a perspective shaped by both technological evolution and global business experience. The heart of our conversation centered on Cicero, CGS's AI-driven platform that blends artificial intelligence with extended reality to create dynamic, real-time role-play simulations. Far from just another e-learning tool, Cicero tackles one of the biggest blind spots in workforce development today: soft skills. From objection handling in medical device sales to flight attendant training and fast-food onboarding, the platform is being used to scale training faster, cheaper, and more effectively than traditional classroom or online methods ever could. What really stood out was how Phil views this as a moment of acceleration rather than disruption. AI isn't here to replace human trainers or eliminate roles; it's a tool that can deepen learning and speed up how people acquire both interpersonal and job-specific skills. In a world where young workers are more comfortable with gaming engines than whiteboards, the immersive, responsive nature of AI-powered simulations offers a natural fit. Phil shared compelling stories from industries like healthcare, aviation, and fast food, where training time has been slashed from months to days. But more than the metrics, it's the idea that training can now adapt in real time, simulate unpredictable human behavior, and offer meaningful feedback immediately that points to where we're headed next. As AI and XR technologies converge, what will it mean when every employee can have a personalized, just-in-time coach at their fingertips?

When we think about gene editing, the conversation often feels trapped between scientific journals and ethical debates too complex for public forums. In this episode, I spoke with Neal Baer, a rare voice who bridges both worlds. Known to many as an award-winning television showrunner for series like ER, Law & Order SVU, and Designated Survivor, Neal is also a Harvard-trained physician and co-director of the Media, Medicine, and Health program at Harvard Medical School. His latest project brings all of that experience together in a new collection of essays that explores the promise and peril of CRISPR gene-editing technology. Neal takes us on a journey that begins with his time as a medical resident treating a young sickle cell patient, and leads to a much broader conversation about science, ethics, and storytelling. We discuss how CRISPR is already being used to cure diseases like sickle cell, and how companies are now exploring gene edits that promise permanent reductions in cholesterol. But the real power of this discussion is not just in what CRISPR can do, but in what we still don't fully understand about its long-term impact. The conversation moves into difficult territory—unintended mutations, germline editing, the risk of pathologizing human diversity, and the slippery slope of “enhancement” where only those with access can benefit. Neal raises critical questions about the social cost of deciding which conditions should be “fixed” and who gets to make that call. We also dive into the lack of political and regulatory oversight, and why a global framework, not just scientific advancement, is urgently needed. This episode offers a powerful reminder that the future of CRISPR shouldn't be left solely to researchers or startups. It demands wide engagement, from classrooms to policymaking, and inclusive voices that challenge how we define progress. How should we decide what counts as improvement when the very definition of being human is at stake?

In this episode of Tech Talks Daily, I welcomed back Sumit Johar, CIO at BlackLine, for a timely conversation about how AI is transforming finance operations from the inside out. When we last spoke earlier this year, AI was still in the early stages of enterprise experimentation. Just a few months later, everything has shifted. Sumit shared how AI has moved well beyond pilot programs and into a space where business leaders themselves are actively requesting implementations. What stood out in our conversation was how this change has reshaped the relationship between CIOs and CFOs. The skepticism is fading, and a stronger sense of collaboration is emerging as both sides work together to drive transformation, align strategies, and reimagine outcomes. We explored the growing need for CIOs to be “multilingual”—not in the linguistic sense, but in their ability to navigate both technology and business. It's no longer enough to speak in code or technical jargon. CIOs must understand finance workflows, end-to-end processes, and the operational pressures CFOs face every day. This alignment is critical when evaluating how and where to deploy AI. Sumit also unpacked some of the core challenges around AI integration, including data quality, long-term sustainability, security, and ethical use. Unlike previous SaaS waves, AI adoption carries more complex risk vectors. Demos might impress, but real-world deployments demand rigorous controls, responsible governance, and the right culture. The conversation covered the ongoing build versus buy dilemma, why it's context-specific, and how BlackLine approaches those decisions with long-term scalability in mind. Sumit also shared how internal councils and cross-functional collaboration have helped guide AI strategy across the organization. If you're leading digital transformation or building the next phase of AI integration in your finance or IT teams, this episode offers clear, experience-driven insights. What's your organization doing to prepare for AI not as a concept, but as a day-to-day operational reality?

In this episode of Tech Talks Daily, I sat down with Boris Bialek, VP and Field CTO at MongoDB, for a conversation that moved well beyond databases. As AI continues to accelerate across sectors, MongoDB is positioning itself at the intersection of modern data architecture and intelligent application development. Boris shared how his team is simplifying AI adoption for enterprises, with a clear focus on real-world outcomes, developer productivity, and global inclusion. We began by exploring MongoDB's recent acquisition of Voyage AI. This move extends MongoDB's native capabilities into vector search, embeddings, and re-rankers, allowing developers to build AI-powered applications more efficiently. Boris explained how MongoDB is removing the complexity from AI integration by providing a unified API, collapsing what used to be 18 disconnected tools into a streamlined developer experience. But the discussion wasn't just about technology. Boris brought a passionate focus to the issue of financial inclusion. We talked about how AI can enable alternative credit scoring for the 27 percent of adults globally who remain unbanked. By analyzing behavioral signals such as mobile payment histories or utility data, AI can help unlock microcredit opportunities for individuals and small businesses in underserved regions. Boris shared use cases from PicPay in Brazil, M-Pesa in Africa, and Proxtera in Singapore, each demonstrating how AI and MongoDB are enabling new forms of digital trust. We also tackled the organizational and technical hurdles to enterprise AI adoption. From fears about hallucinations to managing constant model updates, Boris described how MongoDB is building systems that prioritize transparency, auditability, and scale. With its document model and integrated tooling, MongoDB offers a stable foundation for companies navigating fast-moving AI transformations. For developers, the platform now includes learnmongodb.com and quick-skill badges designed to make AI approachable and hands-on. And with the upcoming release of Boris's new book, there's more to come on how businesses can move from pilot experiments to production-grade solutions. How is your organization rethinking its data strategy to make AI work at scale?

When we think about innovation in technology, power grids rarely enter the spotlight. Yet, they are the foundation for everything from artificial intelligence to electric vehicles and data centers. In this episode, I spoke with Adrian Guggisberg, President of the Smart Power Division at ABB, to unpack the evolving role of electrical power distribution in a world shifting rapidly toward digital infrastructure and clean energy. Adrian joined me from Zurich to share how ABB is helping grid operators navigate an increasingly complex landscape. With rising pressure from extreme weather, surging energy demand, and growing decentralization of power sources, the traditional grid model is being challenged on multiple fronts. We explored recent high-profile outages like the Heathrow disruption and the cascading blackouts in Spain and Portugal, and what these incidents reveal about systemic vulnerabilities. What stood out was Adrian's clear message that resilience is no longer optional. He walked me through how switchgear plays a vital role in controlling flow, isolating faults, and restoring power with precision. Rather than waiting for outages to happen, ABB is championing a smarter, decentralized approach that supports microgrids and localized decision-making. The transition to intelligent infrastructure requires investment, digital tools, and collaboration across public and private sectors. We also discussed the cultural and political shift required to truly modernize the grid. Adrian pointed out that while grid operators understand the urgency, public awareness and policymaker support will be key to driving progress. His optimism came through clearly, especially when he talked about ABB's purpose in powering a more sustainable future. If energy is the backbone of society, then conversations like this are the starting point for building something stronger. What would a smarter grid mean for the communities and industries you serve?  

In a digital-first world where cybersecurity often dominates headlines, the conversation around physical security can sometimes feel like an afterthought. But what if technology could bring a new level of intelligence, proactivity, and efficiency to protecting real-world environments? In this episode, I sat down with Ryan Porter, co-founder and CEO of LVT, to learn how his team is reshaping physical security through innovation rooted in both technology and field experience. What began in Ryan's garage as a way to monitor construction projects through live video has evolved into a powerful enterprise platform used by 30 of the Fortune 50. LVT provides mobile security units equipped with cameras, lights, solar power, and edge-based AI capabilities that don't just observe but actively deter criminal behavior. From parking lots to retail environments, and even the Super Bowl, LVT's presence is being felt wherever safety is at risk. Our conversation uncovered how LVT's approach differs from traditional reactive security models. Rather than reviewing footage after incidents happen, LVT creates controlled environments designed to prevent events before they occur. This shift toward deterrence, combined with a visible and multi-sensory presence, is producing measurable results. In cities like Paducah and Opelika, LVT's Access Task Force program contributed to a ten percent reduction in citywide crime. We also explored how the company overcomes the challenges of deploying AI in environments with limited power and bandwidth. By running intelligent models on edge devices, LVT delivers real-time insights in places that lack the infrastructure for heavy cloud computing. The result is a system that delivers value instantly, improves business intelligence, and enhances community safety. This is not just about technology for its own sake. It is about building systems that serve people, keep environments secure, and foster collaboration between businesses, law enforcement, and local communities. How are you using technology to create safer, smarter spaces in the real world?

In today's episode of Tech Talks Daily, I connected with Brittany Christenson, CEO of AidKit, to explore how cutting-edge technology is being used not to disrupt markets or chase margins, but to deliver real, measurable social impact. AidKit is a public benefit corporation building infrastructure that helps vulnerable communities access aid quickly, securely, and with dignity. While many tech conversations orbit around scale and efficiency, Brittany brings a different kind of energy, one grounded in values, user empathy, and purpose-built innovation. She shared how AidKit's journey began as a nonprofit initiative during the pandemic, evolved into a for-profit startup to attract engineering talent, and most recently achieved B Corp certification, reinforcing its long-term commitment to balancing people, planet, and profit. We discussed what dignity and equity look like in real-world software experiences, and how user-centric design can transform burdensome forms and gatekeeping processes into streamlined, accessible interfaces that actually work for people in need. Aidkit doesn't stop at technology. Their model also includes multilingual support, advisory councils made up of program beneficiaries, and robust fraud prevention tools that protect both funds and privacy. One of the standout takeaways was how Brittany views trust and transparency as core features, not afterthoughts. Governments rely on Aidkit to deliver programs with high stakes and public scrutiny, and that trust is earned through a combination of technical competence, clear communication, and reliable systems. AidKit is already supporting over 200 agencies and nonprofits, has processed more than half a million applications, and recently surpassed 330 million dollars in aid disbursements, including nine million dollars in a single week. This conversation is not just about scaling a social impact startup. It is about leading with conviction, refusing to compromise mission for growth, and using the best of what technology offers to serve communities with care. How can your tech strategy support social outcomes without losing sight of the people it's built for?

When we talk about the future of enterprise software, AI is front and center. But behind the buzzwords, real transformation is happening in how businesses plan, execute, and deliver professional services. In this episode, I sat down with Raju Malhotra, Chief Product and Technology Officer at Certinia, to explore how AI is shifting from theory to practice in high-scale environments. Certinia, a native ISV on Salesforce, is helping global tech and service firms like Cisco, Siemens, and PwC automate their services operations. With over two million users and six million active projects, the platform isn't just adding AI for the sake of it. It's embedding it directly into workflows to solve tangible business challenges. Raju shares a clear framework for understanding how different types of AI are being implemented. Predictive AI is already deeply integrated into enterprise processes. Generative AI is gaining traction for simplifying content and communication. Agentic AI, the most recent frontier, enables digital agents to complete complex tasks independently within enterprise guardrails. What stood out in our conversation was the emphasis on outcomes over features. Raju makes a compelling case for starting every technology decision by understanding the customer's goals. Certinia's approach avoids chasing trends for the sake of headlines. Instead, the focus is on delivering results like improved margins, higher resource utilization, and smarter project delivery. We also discussed Certinia's early adoption of Salesforce's Agent Force and how their team works closely with Salesforce engineering to align on AI strategy. Rebranding their ERP Cloud to Financial Management Cloud was another move that reflects their sharper focus on services-centric financials, rather than trying to be everything to everyone. There's a clear message in this conversation. Innovation in AI must be matched with investment in performance, latency, scale, and user experience. For any tech leader navigating the AI landscape, Raju's insights provide a grounded, real-world guide. How are you aligning your AI investments with measurable business outcomes?

In this episode of Tech Talks Daily, I had the opportunity to sit down with Amanda Hamilton, patron and director at the National Association of Licensed Paralegals (NALP). While many of our discussions often focus on cutting-edge technology and digital transformation, today's conversation tackled a very different kind of disruption, one happening quietly in the legal industry. The legal landscape in the UK has shifted dramatically over the last decade, particularly following the 2013 legal aid cuts. This policy change left many without affordable access to legal representation. Amanda walks us through how the paralegal profession stepped in to fill that gap, providing legal support at lower costs while still maintaining high standards of professionalism and care. What stood out was how NALP functions as a voluntary regulatory body, offering credibility and structure to a sector that otherwise lacks statutory regulation. We also explore how AI and digital tools are reshaping legal work. Amanda offers a grounded view on where technology helps and where it still cannot replace human expertise. From virtual hearings during the pandemic to the efficiency gains through email and digital collaboration, the legal profession is gradually adapting. Amanda stresses the importance of using technology thoughtfully, especially in situations where personal judgment and contextual understanding are critical. Another important theme was transparency and trust. The National Paralegal Register is a public tool that allows individuals and employers to verify the qualifications and membership levels of licensed paralegals. Amanda believes this kind of openness is vital to building awareness and confidence in the services paralegals can offer. So, whether you're exploring legal tech, building new professional services, or facing legal challenges yourself, this conversation sheds light on the growing role of paralegals in today's evolving legal system. How is your industry approaching transparency, training, and the impact of emerging technologies?

What if the average UK tech worker could reclaim almost an entire workday each week without extra hours simply by harnessing AI tools like ChatGPT and robotic process automation more effectively? In this episode, I sit down with Oliver Latham from Pearson's Enterprise Learning and Skills division, to unpack research revealing how intelligent automation frees tech professionals from repetitive tasks and opens space for creative strategic collaboration. Instead of fuelling fears of mass job losses, the data reveals a more optimistic human‑centred view of how AI will reshape roles, reshuffling responsibilities rather than replacing people. Oliver and I discuss which tasks are most ripe for automation, for example code refactoring to backup procedures, and how that shift could alleviate the UK's tech skills shortage by letting workers focus on high impact projects. We weigh potential challenges too and note that organisations will need to rethink job design, invest in upskilling power skills such as communication and learning agility and build a culture of continuous development. As we look ahead we explore how large language models and robotic process automation differ in their impact across roles, why learning cultures must evolve to deliver micro learning at the point of need alongside robust credentials and how teams can reorganise around a new division of labour that includes both human and AI agents. Oliver offers practical advice for tech leaders wondering where to start and how to maintain agility as change accelerates. If you've ever felt overwhelmed by AI hype or are curious how automation could give you back precious hours each week, this conversation offers fresh perspectives on AI's real value in tech. How would you redesign your job if you had an extra day each week, what would you stop doing and what would you start? 

What if the biggest leap forward for small businesses wasn't about selling more, but reclaiming time? In this episode of Tech Talks Daily, I sit down with John Waldmann, CEO and co-founder of Homebase, to unpack how AI isn't just a Silicon Valley toy for large enterprises but a lifeline for the millions of small businesses keeping local economies afloat. John explains how Homebase's newly launched AI Assistants are transforming everyday operations, automating hiring, scheduling, and admin tasks that once drained hours from already stretched owners and managers. But this is more than a tech play. John shares why he's spent his career championing small business owners, and how Homebase is designed with them, not just for them. We explore how generative AI and real-time personalization are lowering the barrier of entry to entrepreneurship, and why small businesses might actually be outpacing the big players in adopting AI with creativity and speed. From the realities of running a restaurant to designing software that respects the nuances of hourly work, John's perspective offers a refreshing reminder that the goal of AI isn't to replace people. It is to give them more space to do what makes their business special. Could AI finally tilt the playing field in favour of small businesses? And are we doing enough to ensure that human-first values stay at the centre of this technological shift? Listen in, then let us know how you see AI transforming the small business landscape in your world.

What if the key to global access to high-quality education isn't policy reform or private investment, but open source software? In this episode of Tech Talks Daily, I sit down with Scott Anderberg, CEO of Moodle, to explore how one of the world's most widely used learning platforms is quietly transforming education in ways that extend far beyond the classroom. Scott's journey is anything but linear. From helpdesk support in Denver to leading online education efforts across the US, UK, and Australia, his international experience has shaped a clear mission: to make education more accessible, more inclusive, and more creative. His role at Moodle aligns perfectly with that goal. We discuss what open source really means in the context of education and why it continues to be misunderstood. Scott explains how Moodle's global community of developers and educators contributes everything from security-tested code to deeply localised customisations that enable learning to happen anywhere, even in places without electricity. Projects like MoodleBox and the Inventorium for at-risk students in Australia reveal the power of local innovation when built on flexible, open platforms. Scott also outlines Moodle's measured approach to AI, focusing on what delivers actual value. Rather than embedding generative tools for novelty, they've released an AI subsystem that allows the community to experiment and share what works. This model not only encourages innovation but also respects the diverse regulatory, cultural, and economic environments their users operate within. Throughout the conversation, we explore the myths that often discourage adoption of open source solutions. Security, support, and scalability are frequently raised, but Scott shows how Moodle's global ecosystem consistently challenges those assumptions. Innovation doesn't have to be proprietary or top-down. In fact, when communities co-create solutions, the results are often more resilient and more relevant. We close with a powerful reflection on the importance of diversity in both tech and education. While some organisations are becoming hesitant to talk about inclusion, Scott argues that now is the time to stand firm. Education is about connection, and you cannot truly connect people if only a narrow group is included in the conversation. Open platforms like Moodle make it possible to include everyone, not just in theory but in practice. So can open source help us rebuild education in a way that is genuinely inclusive and globally relevant? Or are there still barriers that need to be broken? I'd love to hear your thoughts. What role should open platforms play in shaping the next chapter of learning?