Rory Blundell: Who's Governing Your AI Agents? Probably No One. | Ep 1294

In this episode of The Digital Executive Podcast, host Brian Thomas speaks with Balaji Tammabattula, founder and Chief Industrial Architect of Barrupan, about reimagining the infrastructure needed to power the AI revolution. Balaji shares how a power shortage at a planned chemical manufacturing facility sparked a transformation into AI power infrastructure development. He discusses LAMP Texas and the BeyondGiga vision: bringing AI data centers, advanced manufacturing, and innovation together on energy-independent campuses. By generating power on-site, these developments aim to accelerate construction, reduce strain on the electrical grid, and address community concerns about rising energy costs. Balaji also explores the growing role of nuclear technologies, including small modular reactors, and the potential for space-based data centers in the future. His message is clear: the next era of AI depends on building smarter, more resilient energy and industrial infrastructure.

In this episode of The Digital Executive Podcast, host Brian Thomas speaks with Chandan Mahajan, co-founder and Chief Growth Officer at DotConnect, about helping enterprises turn AI ambition into measurable business results. Drawing on more than 20 years of enterprise technology experience, Chandan explains why industry-specific AI can outperform general-purpose solutions by leveraging the unique context, workflows, and expertise of a business. He shares how DotConnect combines consulting, engineering, and its Compass Studio platform to accelerate AI implementation while allowing companies to retain ownership of their solutions and data. Chandan also explores the future of agentic AI, emphasizing that organizations must become AI-native while remaining human-owned. His central message: companies can rent AI models, but they must own their technology, business context, and capabilities to maintain control and long-term competitive advantage.

In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Dharmateja Uddandarao, Senior Data Scientist and Statistician at Amazon, to make a distinction that most business leaders have never fully grasped — and that costs organizations millions of dollars in misattributed decisions every year. Dharmateja opens by tracing how causality became the through line of his career not by design, but by repeatedly hitting the same wall: a beautiful, high-accuracy model would ship a recommendation, a leader would ask whether the product actually caused the outcome or whether it would have happened anyway, and the model had no answer. That gap — between what happened and what would have happened — is where statistics, data science, and economics all converge, and it is the problem Dharmateja has spent his career learning to solve. He then breaks down why all three disciplines are necessary: classical econometrics has the deepest theory of identification but is often rigid; machine learning handles complexity and scale but is causally blind, happily telling you that ice cream sales cause drownings because both rise in summer; and causal inference theory provides the connective tissue — the language of counterfactuals and potential outcomes — that makes it possible to ask what the world would have looked like if you had acted differently. He illustrates this with an ad measurement example where a naive eleven-point lift becomes a credible eight-point lift once confounding is properly addressed, and walks through counterfactual forecasting as a method for estimating causal effects when no randomized experiment was possible. His close is direct: the next decade of AI is not about prediction becoming cheaper — it already is. It is about decisions becoming more intelligent. And that requires causal grounding, honest uncertainty, and economic context, not just bigger models.

In this episode of The Digital Executive Podcast, host Brian Thomas speaks with Shauna Geraghty, Senior Vice President and Global Head of People & Talent at Talkdesk, about how AI is transforming HR, workforce strategy, and the future of work. As one of Talkdesk’s first U.S. employees, Shauna helped scale the company from a startup to more than 1,500 employees. She explains why HR and IT must work together to redesign how organizations operate, using AI to automate repetitive tasks while empowering employees to focus on strategic work and meaningful relationships. Looking ahead, Shauna shares three essential capabilities for future HR leaders: business and technology fluency, organizational and workforce architecture, and transformation leadership. Her message is clear: successful AI adoption is about more than efficiency—it’s about amplifying human potential and creating greater business value.

In this episode of The Digital Executive Podcast, host Brian Thomas sits down with Seymour Segnit, founder and CEO of MagFast, to explore what it takes to build a hardware company around a single, deceptively simple idea: that charging your devices should be effortless, elegant, and yes, delightful. Seymour opens with a career that spans Oxford engineering, Ogilvy and Saatchi advertising, Capital Radio, early SaaS, and USB charging — a patchwork of experiences that he argues has made him a better operator because he has enough fluency in each discipline to actually understand the people working across them. MagFast’s core insight is that people do not need more adapters. They need one integrated system — chargers, cables, and power banks that share a common design language and snap together magnetically using the industry-standard Qi2 and USB-C technologies that now span both Apple and Android ecosystems. By locking into those standards rather than proprietary ones, MagFast can offer genuine interoperability without asking customers to choose a walled garden. He then walks through what twenty-five million dollars in direct-to-consumer sales has taught him that a traditional hardware company never learns: you cannot know your customers if you do not know who they are. Building a unified customer data layer has allowed MagFast to deploy a voice agent named Maggie that actually delights people — not because it sounds good, but because it knows that your package was delivered to your porch in Kansas City at 2:30 yesterday afternoon. The difference between a great voice and a great agent, Seymour notes, is the data behind it. He closes with a vision of where charging is heading — wireless magnetic connections becoming as routine as Wi-Fi, the USB-C standard lasting decades — and a business philosophy built around the toughest standard he knows: is it delightful? If not, it is not done.