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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Season 12 of the AIAW Podcast kicks off with a high-stakes question: Can we reach Artificial General Intelligence (AGI) by 2026? In Episode 174, we’re joined by Karim Nouira, founder of sics.ai (Superintelligence Computing Systems), for a deep and provocative conversation on the technical frontiers of AGI. From LLM limitations and JEPA’s alternative path to robotics brains and latent space reasoning, we unpack what it would take to build truly autonomous systems. We also explore Sweden’s role in the global AGI race, the future of labor in an agentic world, and the societal implications of superintelligent machines. A powerful start to a season focused on what’s next in AI. Tune in. 

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In Episode 173 of the AIAW Podcast, we close out Season 11 with a festive and future-focused Christmas & Year-End Special—and you're invited. Together with surprise guests Patrick Couch, Jesper Fredriksson, and Fredrik Olsson, we look back at the AI rollercoaster that was 2025: from breakthroughs in model development and enterprise AI maturity to the biggest twists in tech and regulation. We also look ahead to 2026, sharing bold predictions, strategic challenges, and the trends that could define the next wave of AI transformation. Equal parts serious and celebratory, this episode is the perfect way to reflect, recharge, and reset for what’s next. Grab something festive and tune in to the grand finale of Season 11. 

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We explore how to scale in the age of AI without drowning in complexity, moving from one-off pilots to reusable platforms, and from efficiency-only thinking to adaptability, trust, and aligned autonomy. Helena Hörnerbrandt shares enterprise-tested principles that travel across 65+ markets, plus a real ABS rollout that shows product over project in action.

• deepfake demo as a visceral risk signal
• value-led scaling and decoupling growth from OPEX
• escaping point-solution spaghetti with use case families
• bimodal model for value creation and capitalization
• governance that speeds decisions, not stalls them
• continuous design over static process change
• trust, discipline, aligned autonomy, and mastery
• product vs project and market enablement roles
• ERP standardization vs data pattern standardization
• the intelligence plane and shared, synthetic, real-time data
• buy to build, ecosystem scaling, and partnerships
• Europe’s need for sandboxes and co-created guidance
• AGI outlook across both risk and opportunity

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In Episode 170 of the AIAW Podcast, we’re joined by Jim Dowling, CEO of Hopsworks, co-creator of featurestore.org, and author of the upcoming O’Reilly book Building Machine Learning Systems with a Feature Store. Known as "Mr. Feature Store," Jim walks us through the evolution of AI infrastructure. From traditional batch learning to real-time, agentic workflows powered by vector databases, RAG, and LLMs. We discuss how feature stores serve as the memory layer of AI agents, enabling contextual awareness and low-latency decision-making, and why they’re central to the future of scalable, ethical, and sovereign AI systems. Tune in for a deep dive into the systems powering tomorrow’s most advanced AI applications. 

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 In Episode 169 of the AIAW Podcast, we’re joined by Alexander Norén, journalist and economics correspondent at SVT, for a behind-the-scenes conversation on Homo Roboticus—the newly released second season of SVT’s acclaimed documentary series that began with Generation AI. While the series dives into how artificial intelligence is transforming work and society, this episode goes further, tackling the political and economic implications of automation that are often left out of mainstream narratives. From Nobel laureates to tech CEOs, Alexander reflects on the conflicting visions for AI’s role in our future: will it liberate us from drudgery, or quietly reshape power and inequality? A candid and provocative discussion about jobs, basic income, AI anxiety—and the uncertain future we’re all stepping into. 

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 In this episode of the AIAW Podcast, we’re joined by Hugi Aegisberg, AI & Innovation Lead at the Central Bank of Sweden (Sveriges Riksbank), for a forward-looking conversation on how artificial intelligence is reshaping the future of central banking. From rethinking monetary policy and financial stability to building public trust through open-source AI and digital assistants, Hugi shares practical insights from inside one of the world’s oldest financial institutions. We dive into Sweden’s approach to hybrid cloud, data sovereignty, ethical AI deployment, and what it means to empower every citizen with their own AI agents. A must-listen episode at the intersection of technology, public governance, and economic transformation. 

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In this episode, Luka Crnkovic-Friis, Head of AI/ML at King (Microsoft), joins us for a sharp, honest look at the real-world challenges of deploying agentic AI systems at scale. Drawing from his experience leading AI innovation at the company behind Candy Crush, Luka unpacks the practical bottlenecks of integrating reasoning models and autonomous agents into business processesfrom accuracy trade-offs and productivity pitfalls to the psychological complexities of human-AI collaboration. We explore the shift from System 1 to System 2 AI, the rising need for contextual understanding, and how Reinforcement Learning could unlock the next phase of enterprise automation. If you’re navigating LLMs, decision-making agents, or the evolving AI workplace, this is your must-listen guide to what’s possible—and what’s still holding us back. 

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