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by Baseline Podcast
An investigative archive of humanity transitioning from human-centered systems to computationally-mediated civilization.
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AI is accelerating software development at an unprecedented pace. But what if the real problem isn’t building software anymore?What if the problem is understanding it?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.
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?
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.
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.
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.
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.BASELINE uncovers how AI and technology are transforming business, creativity, and society.
Enterprise AI adoption is accelerating, but implementation is proving far more difficult than expected. While organisations are investing heavily in artificial intelligence, machine learning, and large language models, many are struggling to translate capability into real operational impact. Bob De Caux is the Chief AI Officer (CAIO) at https://www.ifs.com/enThis conversation explores the gap between AI innovation and enterprise execution, covering the realities of AI strategy, organisational readiness, and the challenges of deploying AI systems at scale. Topics include AI transformation, enterprise architecture, data readiness, internal capability gaps, and the pressure on leadership teams to act before fully understanding the implications.Drawing on real-world experience inside enterprise environments, this discussion breaks down why AI initiatives often stall, where companies are overestimating progress, and what needs to change for AI to deliver measurable value.
The AI job market is expanding rapidly, but most people still don’t know how to access it.In this episode, Ian sits down with William Excell, a recruiter working directly with AI startups and high-growth technology companies, to break down what is actually happening inside the hiring market.As AI reshapes how companies are built, teams are becoming smaller, faster, and more selective. The result is a fundamental shift in what companies look for and who gets hired.
An investigative archive of humanity transitioning from human-centered systems to computationally-mediated civilization.
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