Tech Talks Daily

Gene Hoffman, CEO of Chia Network, shares insights on tokenizing equity investments while ensuring regulatory compliance. He explains how their innovative platform, Permuto, will redefine investment by separating dividends from capital gains, paving the way for a new era of secure and sustainable investing. This approach is particularly beneficial for low-risk investors, especially retirees. Gene also emphasizes Chia's commitment to open-source technology and green practices, which are attracting institutional interest and shaping the future landscape of digital finance.

When cybersecurity companies are racing to outpace evolving threats, innovation often starts in an unexpected place: revenue operations. In this episode of Tech Talks Daily, I sit down with John Queally, Senior Director of Revenue Operations at Clari, to explore why RevOps has become a vital engine behind the performance and resilience of cybersecurity leaders. John brings a unique perspective from his journey through banking, analytics, and enterprise tech. What stands out is how rapidly the RevOps function has matured from a back-office support role to a central, strategic force. Especially in the cybersecurity space, where innovation requires ongoing investment and risk is measured in seconds, the pressure to run efficient, scalable revenue processes has never been greater. We delve into why clean, trusted data is the backbone of any AI strategy and how 67% of revenue leaders still don’t trust the data they're using. It’s a staggering insight, and one that underscores the urgent need for cross-functional alignment. John explains how RevOps can serve as the connective tissue across sales, marketing, customer success, and finance, moving companies from a place where they're debating the accuracy of dashboards to making real decisions in real time. He also shares a behind-the-scenes look at Clari’s work with cybersecurity firms like Okta, where implementing balanced pipeline strategies and streamlining task prioritization has unlocked measurable improvements. We discuss the rise of AI, but John doesn’t just repeat industry headlines. He calls out the "unsexy" truth that real AI advantage requires the hard work of data cleanup first and those who do it will pull ahead. From operational transparency to building trust within revenue teams, this episode challenges assumptions about how data, AI, and RevOps intersect. And for anyone in cybersecurity or enterprise tech wondering how to scale effectively while preparing for what’s next, this conversation offers a grounded and insightful starting point. Is your company still debating data? Or are you ready to turn trusted insights into action?

In today’s episode of Tech Talks Daily, I sat down with Bulent Cinarkaya, General Manager of Field Service Management at ServiceNow, to explore how AI is transforming the frontlines of field service. Often overlooked in the broader tech conversation, the technicians working outside the office are now seeing real, tangible improvements to their daily workflows thanks to advancements in intelligent automation. Bulent brings a wealth of knowledge from working closely with global organizations that rely on ServiceNow to improve how they plan, dispatch, and support field teams. We talked about how agentic and generative AI are no longer theoretical tools; they are actively used to predict what technicians will need before arriving, automate access to resources, and reduce inefficiencies in task planning. One of the most compelling parts of our conversation was how ServiceNow is using AI to improve productivity and enhance the human experience. From easing the onboarding of new technicians to capturing decades of experience from retiring experts, AI is helping teams bridge a generational gap in expertise. Technicians can now rely on intelligent systems to surface the correct information at the right moment, whether through summarizing technical documents or guiding them through complex tasks. We also discussed the operational impact, with examples from customers like Bell Canada, Coursera, and British Telecom, who are seeing measurable improvements in scheduling accuracy and time to resolution. Bulent stressed the importance of unified data models, integrated platforms, and strong change management as organizations look to scale AI to ensure adoption and success. This episode is a wake-up call for anyone still on the fence about AI in field service. AI is not only improving technician efficiency, but it’s also helping companies retain talent, meet rising customer expectations, and ultimately future-proof their operations. So, how ready is your organization to move beyond proof of concept and turn AI into a field-ready advantage?          

What does it take to turn a moment of frustration into a global mission to tackle waste? At the AWS Summit in London, I sat down with Tessa Clarke, co-founder and CEO of Olio, to explore how a single idea born on a snowy Swiss street evolved into a powerful tech platform reshaping how communities think about consumption, sharing, and sustainability. Tessa shared her personal journey, from growing up on a farm where food waste was unthinkable to climbing the corporate ladder before walking away to co-found Olio. That decision came after she was told to throw away perfectly good food while moving house, a moment that sparked an idea and a deeper calling. What followed was years of research, a grassroots WhatsApp experiment, and ultimately, the creation of an app that now connects millions of users worldwide. In our conversation, we explored how Olio uses technology to drive real-world change. Tessa explained how AWS has been a foundational partner since day one, helping Olio scale sustainably without compromising its values. She also gave an inside look at how AI is integrated thoughtfully across their operations, from assisting users in listing items faster to detecting potentially unsafe or inappropriate listings before they go live. What stood out is how intentional Tessa and her team have been in making AI serve the mission, not distract from it. Whether it’s reducing friction within communities or using automation to offset operational challenges, every tech choice is aligned with their goal: to build a waste-free world. We also discussed how AI is helping them break the traditional link between headcount and impact, paving the way toward profitability while staying people-focused. As Olio aims to reach a billion users by 2030, this episode is a reminder of what happens when purpose and technology meet. Tessa’s story offers a compelling blueprint for founders, technologists, and anyone looking to use digital tools to solve human problems. How can a simple act of sharing create ripple effects across the world, and what role will technology play in scaling that vision responsibly?

Darran Milne, co-founder and CEO of VividQ, brings a rich background in quantum physics to the table as he discusses the exciting realm of true holography. He reveals how VividQ is turning theoretical concepts into practical applications, like immersive 3D experiences for gaming. Darran highlights its potential in automotive and healthcare, where holography could replace traditional screens and improve user interaction. He emphasizes the importance of thoughtful engineering over hype, outlining a strategic rollout for these revolutionary technologies.

What if companies could tap into powerful behavioral AI without compromising user privacy or crossing legal lines? In this episode of Tech Talks Daily, I sit down with Frank Portman, CTO of Yobi, to explore how his team is building foundation models grounded in real user behavior, backed by ethically sourced and consented data. Frank shares how Yobi is taking a distinct approach. They're not building large language models or racing to dominate generative AI headlines. Instead, they're focused on data integrity, transparency, and security from day one. With a strategic partnership with Microsoft Azure, Yobi delivers models that run directly within a customer’s environment. That means privacy is preserved, data stays protected, and companies still benefit from intelligent, adaptive systems. We unpack how Yobi avoids risky use cases like financial underwriting and healthcare, how their models are trained to avoid demographic bias, and why they actively reward systems for being bad at guessing personal traits. This isn’t just about compliance. It’s about designing products that work better because they’re built responsibly. Frank also opens up about Yobi’s internal culture, his belief in first-principles thinking, and how empowering engineers to "place bets" drives innovation. He offers insight into what the AI industry must learn quickly from recent missteps, including data misuse and growing public skepticism. If you're exploring AI solutions and wondering how to build or buy systems that scale without cutting ethical corners, this conversation delivers clarity, honesty, and direction. Are you ready to rethink what responsible AI should look like inside your company?

In this insightful discussion, Sue Harnett, Founder and CEO of Rewriting the Code, shares her journey of creating a nonprofit that empowers over 35,000 women in tech. She emphasizes the urgency of systemic change for inclusivity, driven by personal experiences of feeling out of place. Sue explores innovative initiatives like Rewrite AI and Rewrite Cybersecurity aimed at preparing women for high-demand tech roles. The conversation highlights the vital importance of mentorship, community support, and the need for genuine commitment to diversity in the industry.

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

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

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