AIAW Podcast

In Episode 179 of the AIAW Podcast, we’re joined by Henrik Appert, Founder and CEO of Magma Math, for a fascinating conversation on AI and the future of mathematical thinking and learning. As AI systems become increasingly capable of solving mathematical problems instantly, the deeper question emerges: what does it actually mean for humans to think mathematically? Together with host Henrik Göthberg and guest co-host Anders Enström, we explore how AI is transforming classrooms, what may be fundamentally broken in how mathematics is taught today, and how new tools can strengthen human learning and peer interaction. From the philosophy of mathematical reasoning to the realities of school system adoption, and from workforce implications to the broader societal impact of improving global mathematical literacy, this episode examines how education may evolve in a world where machines can calculate but humans still need to understand.
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In this episode of the AIAW Podcast, we’re joined by Dr. Catherine Mulligan, technology strategist, sustainability expert, and author of Designing Resilient Digital Systems, for a timely conversation on the future of digital sustainability. Drawing on her work at the intersection of AI, blockchain, 5G, IoT, and public policy, Catherine explains why traditional digital transformation—focused primarily on efficiency and scale—is increasingly failing to address long-term environmental and societal challenges. We explore what it truly means to build resilient digital systems capable of withstanding climate shocks, geopolitical instability, and rapid technological change. From the energy footprint of massive AI models and the global race for AI infrastructure to Europe’s ambitions for digital sovereignty and the role of human judgment in an increasingly automated world, this episode looks at how organizations can design technology that serves both business and the planet. If you care about the future of AI, sustainability, and responsible digital leadership, this is a conversation you won’t want to miss. 
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In Episode 177 of the AIAW Podcast, we sit down with Magnus Hyttsten, former Google AI Engineering Lead and EU AI Act specialist, for a grounded and timely conversation on AI quality, security, and compliance at enterprise scale.
 
Drawing on his experience building generative AI evaluation systems at Google, Magnus breaks down the real challenge of defining “quality” in non-deterministic models and explains why robust evaluation frameworks, engineering discipline, and governance are becoming mission-critical. 

We explore the EU AI Act as a potential accelerator for trustworthy innovation rather than a constraint, unpack common security blind spots in enterprise AI strategies, and look ahead to what responsible AGI development might require.

If you’re serious about moving from AI experimentation to secure, production-ready systems, this episode is essential listening. 
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In Episode 176 of the AIAW Podcast, we sat down with Danilo Nobrega, Founding Go-to-Market Lead for the Nordics at LangChain, to unpack what it truly takes to scale enterprise AI agents beyond the prototype stage. Drawing on his background in data infrastructure at MongoDB and his work expanding LangChain across Scandinavia, Danilo shared practical insights into the shift from simple LLM wrappers to fully orchestrated, stateful, production-ready agentic systems. We explored LangGraph, agent memory, feedback loops, observability, and cost control—breaking down how organizations can build reliable, explainable, and economically sustainable AI applications at scale. From enterprise use cases and ROI to the Nordic AI ecosystem and the future of AGI, this episode delivers a grounded and strategic look at where agent engineering is headed next. 
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In Episode 175 of the AIAW Podcast, we’re joined by Anders Hammarbäck, Co-Founder and CEO of RedpineAI, to explore why proprietary data may become the ultimate competitive advantage in the AI era. As models increasingly commoditize, Anders argues that the real moat lies in owning and structuring high-quality, licensed data. We discuss RedpineAI’s vision of a “Knowledge Layer” designed to reduce hallucinations, power agentic AI systems, and unlock new applications in science and enterprise. From Europe’s role in data sovereignty to the future of AGI and the evolving labor market, this episode dives into how the next wave of AI innovation may be defined not by bigger models—but by better data. 
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