Investigating the transition to a computational world.
Why More People Are Starting To Build - Ian Sutherland
For decades, turning an idea into a product required funding, developers, technical expertise and a team. Today, that barrier is beginning to disappear. In this episode of BASELINE, former Tide CFO Ian Sutherland shares how a career break after helping scale Tide from less than $1 million to more than $200 million in revenue led him to an unexpected discovery: modern AI tools had dramatically reduced the distance between an idea and a working product.
We explore why more people are starting to build, how AI is changing entrepreneurship, what it means for startups and investors, and why some of the most interesting products of the next decade may come from people who understand the problem rather than those who simply know how to code.
Topics include AI-assisted software development, Claude Code, angel investing, startup economics, productivity, the future of work, niche software businesses, venture capital, and the changing relationship between expertise and execution.
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Why 93% of Enterprise AI Projects Miss the Point - Sol Enenmoh
Artificial intelligence is no longer just changing productivity tools. Inside large enterprises, banks and global institutions, AI and AI governance are beginning to reshape how organisations coordinate, decide and operate.
In this episode, former HSBC AI transformation lead Sol Enenmoh explores the growing tension between traditional enterprise structures and computational systems evolving at machine speed. From governance and organisational silos to agentic systems, AI literacy and sovereign infrastructure, this conversation examines what may become one of the defining transitions of the next decade:
What happens when enterprises are no longer structured around humans coordinating work… but around computational systems coordinating humans?
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Are People Shipping Code They Don’t Understand? Tudor Girba
What if AI feels intelligent partly because humans already stopped understanding the systems they depend on? In this episode of BASELINE, Tudor Girba joins Ian Smith to explore one of the most overlooked challenges in modern technology: the growing gap between the software we create and our ability to comprehend it. As AI generates more code, organisations are becoming increasingly dependent on systems that nobody fully understands.
From legacy banking infrastructure and enterprise software to AI-assisted development and digital transformation, Tudor argues that the future of software engineering may depend less on writing code and more on learning how to read, understand and evolve complex systems.
The conversation explores why so many modernisation projects fail, how organisations become trapped inside their own technology, the hidden economics of software, the role of AI in accelerating complexity, and why understanding systems may become one of the most valuable capabilities in the age of artificial intelligence.
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You can no longer trust video calls - Will Taylor
AI can now clone voices, fake video calls and imitate real people convincingly enough to steal millions of dollars from businesses in real time. In BASELINE089, Ian Smith sits down with Will Taylor from YEO Messaging to explore the collapse of trusted communication in the AI era. As deepfakes, AI-generated identities and social engineering attacks become increasingly indistinguishable from reality, organisations are facing a new challenge: how do you prove the person on the other side of a message, voice note or video conference is actually real?
The conversation explores artificial intelligence, deepfake fraud, cybersecurity, secure messaging, digital identity, facial recognition, data sovereignty, privacy and the growing tension between convenience and security. Will explains how YEO Messaging is building technology designed to continuously verify human identity during communication using real-time facial recognition and localised data sovereignty models.
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Why One Engineer Thinks Humans Can’t Keep Up Anymore - Elie Talj
Modern engineering systems are becoming increasingly software-defined. From vehicles and aerospace systems to robotics and critical infrastructure, software is now the bottleneck limiting how quickly complex systems can be built, tested and deployed. In BASELINE088, former McLaren Principal Engineer and Arrival Director Elie Talj explores why engineering may be approaching the limits of human scalability, and how new forms of AI could radically accelerate the creation of deterministic control software.
The discussion explores the hidden complexity inside modern engineering systems, the tension between speed and reliability, and why current AI coding tools struggle in safety-critical environments.
Elie explains Hypercritical’s thesis that future engineering systems may no longer be manually programmed, but instead discovered by AI systems capable of inventing, testing and continuously refining entirely new control algorithms against real-world requirements. The conversation spans automotive systems, aerospace engineering, autonomous vehicles, simulation environments, AI verification, quantum algorithms and the future of industrial innovation.
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The Actual Cost of AI Compute - Richard Self
AI promises abundance, automation and intelligence at planetary scale. But what problem is it actually solving? In BASELINE086, Richard Self joins BASELINE to explore the economics, infrastructure and physical reality behind artificial intelligence, large language models, generative AI and the next generation of compute systems.
Drawing on 50 years inside modern computing, from Rolls-Royce mainframes to today’s AI infrastructure race, Richard examines why many AI benchmarks are becoming meaningless, the true economics of generative AI, the physical limits of compute and energy, and why SpaceX is rapidly positioning itself as an AI infrastructure company through orbital data centres and low Earth orbit compute systems.
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$2B to $10B: Why Quantum Suddenly Matters - Kirill Pyshkyn
BASELINE: What AI Is Actually Changing Billions are now flowing into quantum computing. But most people still think it’s too early. In this episode of BASELINE, Ian Smith sits down with Kirill Pyshkin, investor and physicist, to unpack what’s actually happening inside the quantum market. Investment has jumped from around $2 billion to over $10 billion in a year. Large institutions like HSBC and Moderna are already reporting real-world results. So why does it still feel like a science project?
This conversation breaks down what changed in 2025 and why it matters, where quantum is already being used today, why one breakthrough can shift an entire industry, the real risks around encryption and security, how investors separate signal from hype, and what happens next as quantum moves from research to deployment.
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If Something Goes Wrong… This Is All You Have - John Dodd
If something goes wrong at sea, there is no one coming to help you. The only thing that connects you to rescue… is a signal.
In this episode, I sit down with John Dodd from Inmarsat, part of Viasat, to understand what really happens when that signal is sent. This is about the systems that keep people alive when they are completely on their own. How they work, what they’re up against, and what it takes to make sure they don’t fail. Because out there… it has to work.
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The Emergence of Intelligence (And Why You’re Losing Your Edge) - Errol Rasit, Gartner
Errol Rasit is a Managing Vice President of Emerging Technologies Research at Gartner, where he advises global organisations on how technologies like artificial intelligence, cloud, and data infrastructure are reshaping business, decision-making, and human behaviour. With nearly two decades inside Gartner and leadership roles across research, product, and innovation, Errol brings a rare combination of deep technical insight and real-world enterprise perspective.
In this BASELINE conversation, we explore the emergence of intelligence through AI and what it actually means beyond the hype. From hyper-personalisation and AI-generated communication to the breakdown of trust, accountability, and human effort, this discussion goes deep into how behaviour is already changing at scale. We cover the rise of generative AI, the ChatGPT effect, and how organisations are restructuring around agentic systems.
Errol shares why ease of use is driving mass adoption, how accuracy drift creates long-term risk, and why ongoing human oversight still matters. We also explore decentralised data ownership, privacy trade-offs, and the growing role of AI in healthcare, retail, and everyday decision-making.
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I Didn’t Expect AI to Save So Much Money - Rob Paton
For a long time, creativity, marketing, and software were separate, outsourced functions. AI is collapsing those boundaries. In this conversation with independent brand consultant and creative Rob Paton, we explore what changes when execution becomes fast, cheap, and accessible to everyone. We talk about why traditional agency models are under pressure, why creativity still matters but shows up differently, and how AI-assisted tools are shifting work in-house.
From branding and production to custom software and “vibe coding,” this episode looks at what happens when teams can build directly instead of buying capability. We also ground the discussion in a real case study from a heating installation business, showing how AI-assisted tools can remove bottlenecks, reduce cost, and change how decisions get made.
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The Algorithmic Leap | AI, Innovation, and the Rules of the Game - Dr John Fletcher
In BASELINE052, Ian Smith sits down with Dr John Fletcher an Oxford, Imperial, and Cambridge-trained physicist and Chief Scientist at The Innovation Game. John is not just a world-class academic - he’s a rare innovator who bridges the gap between research and real-world impact.
At The Innovation Game, he is building technology that creates genuine competitive advantage, not just another layer of AI hype. His work proves how algorithms can solve critical problems in logistics, medicine, and science showing that the future of AI is about application, not buzzwords.
Artificial Intelligence: Utopia or dystopia?