Mikkel B. Rasmussen brings a rare lens to the AI conversation. As an applied anthropologist, he has spent decades helping companies like LEGO uncover what is really going on beneath the surface.

In this episode, he shares how deep insight often begins with being wrong, why surprise is the clearest sign you have found something meaningful, and how the pain of not knowing is essential to breakthrough thinking. He also explains how AI is transforming his own research, from pattern recognition to video ethnography, and introduces a provocative idea: Anthropology Without Anthropologists.

Jeremy and Henrik reflect on what it means to teach AI how to surprise us, how synthetic data might reshape experimentation, and why better insights begin with better questions.

Key Takeaways

• Insight starts with being wrong
  Mikkel defines insight as the gap between how we think the world works and how it actually is. Anthropology helps uncover these mismatches, and that is where real breakthroughs begin.
• Pain is part of the process
  Mikkel and Jeremy both reflect on the emotional struggle that precedes insight. The doubt, sleepless nights, and questioning whether the work will ever come together is not failure. It is a necessary stage of discovery.
• Surprise is a signal
  The moment of surprise, when a new pattern emerges or an assumption is shattered, is at the core of applied anthropology. For Mikkel, it is the clearest sign that you have found something real.
• AI can accelerate experimentation
  Mikkel shares how AI is already helping his team analyze patterns, run faster experiments, and even conduct interviews that outperform humans in some cases. The goal is not to replace people but to push the limits of what is possible.

HARL: humanactivitylab.com

00:00 Intro: Why This Conversation Matters
00:25 Meet Mikkel: Founder of Human Activity Laboratory
01:14 Understanding Anthropology and AI
03:32 Applied Anthropology: Tools and Techniques
04:56 The Role of Narratives in AI
07:06 The Importance of Sensory and Social Dimensions
13:06 Case Study: LEGO and the Anthropology of Play
21:07 The Role of Surprise in Anthropology
27:51 AI and Human Synergy
31:26 Exploring AI's Limitations and Potential
32:46 Anthropology Without Anthropologists
34:17 AI's Role in Generating Insights
37:23 Human Bias in AI-Generated Ideas
42:05 Synthetic Data and Its Applications
47:34 The Future of AI in Anthropology
49:25 The Debrief

📜 Read the transcript for this episode:

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Show edited by Emma Cecilie Jensen.

In this teaser, Jeremy and Henrik debrief their conversation with Mikkel B. Rasmussen, founder of the Human Activity Laboratory. They expected a conversation about AI’s limitations, but got a rethinking of insight itself. They explore Mikkel’s definition of insight as the gap between how we think the world is and how it actually is, why surprise is a critical signal, and how pain often precedes clarity. They also touch on Mikkel’s experiments with AI interviewers that sometimes outperform human researchers, and why this episode challenged how they think about narrative, understanding, and the role of AI.
Full episode LIVE NOW.

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Show edited by Emma Cecilie Jensen.

Diarra Bousso returns to Beyond the Prompt to share how she's reprogramming the fashion industry using AI, math, and a relentless spirit of experimentation. From selling AI-generated products before they exist to cutting out waste and wait times, she walks us through a radical new approach to design and operations.

She explains how her team uses scientific rigor to test marketing ideas, create on-demand collections, and rethink the traditional fashion calendar. Diarra also opens up about the origin of her experimental mindset, which began during a year of recovery after a life-changing accident, and how that philosophy now shapes her leadership.

The episode wraps with reflections on sustainability, mental health, and what it means to build a joyful, human-first company in the age of AI. Diarra shares how she’s using AI not just to scale her business, but to reclaim her time, and why her next venture might bring these tools to creators everywhere.

Key Takeaways

• Experimentation is the foundation
  Diarra treats her entire business as a lab. Every idea is a test, and her team is trained to think in hypotheses, measure results, and adapt quickly.
• AI enhances human creativity
  She sees AI as a creative partner, not a replacement. It helps her move faster, make smarter decisions, and focus on the parts of design that require real taste and vision.
• Sell before you build
  By testing AI-generated designs with customers before making anything, Diarra unlocks cash flow, cuts waste, and sidesteps the long timelines of traditional fashion.
• Sustainability starts with the founder
  Diarra applies the same mindset to her own life. She’s using AI to reclaim time, reduce burnout, and build a business that supports health as well as growth.

Website: diarrabousso.com
DIARRABLU: diarrablu.com

00:00 Intro: AI-Driven Fashion
00:13 Meet Diarra Bousso: Founder of DIARRABLU
01:43 The Power of Experimentation
02:00 A Life-Changing Accident and Recovery
04:40 Embracing a Culture of Experimentation
06:13 Scientific Approach to Business
09:48 Empowering the Team
15:03 AI in Fashion Design
18:36 Revolutionizing the Fashion Industry
28:09 Traditional vs. Digital Fashion Models
32:18 Embracing AI in Fashion Design
32:49 Collaborating with Retailers Using AI
35:06 AI's Role in Prototyping and Design
36:58 The Future of AI in Creative Industries
39:14 Navigating Resistance to AI
48:10 Operationalizing AI for Efficiency
52:18 Balancing Innovation and Personal Well-being
57:19 Debrief

📜 Read the transcript for this episode: Transcript of How The Worlds Leading AI-first Fashion House Flips The Cash Flow Equation with Diarra Bousso

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.

In this teaser, Jeremy and Henrik debrief their conversation with Diarra Bousso, founder of the AI-first fashion startup DIARRABLU. They reflect on Diarra’s use of the word “yet” as a signal of growth, what it means to run a fashion brand more like a lab, and how her team “manages her back” when the ideas overflow. They also explore how AI is reshaping speed, sustainability, and experimentation in the fashion industry, and why your own lived experience might be your biggest asset in an AI-powered world.
Full episode dropping next week.

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.

In this episode, Illia Polosukhin joins Henrik and Jeremy to trace the origins of transformers and how practical constraints inside Google led to a breakthrough that reshaped modern AI. He explains why recurrent models were hitting limits, how parallel attention opened the door to scale, and why he believed a major jump in capability was imminent long before the rest of the world saw it.

The conversation then turns to the risks and responsibilities of today’s AI systems. Illia describes how models can be subtly guided to influence user opinions, why open weights are not the same as truly open models, and how hidden behaviors can be embedded during training. He explains why provenance and verifiable data pipelines matter, especially as AI begins mediating more of the information we rely on.

Later in the episode, Illia outlines how blockchain can support trust, identity, and coordination in a future where AI agents act on our behalf. He shares why information is becoming more valuable than money, how ownership of personal AI models will shape user agency, and why domain expertise becomes significantly more powerful when paired with modern generative tools.

Key Takeaways:

• Transformers emerged from practical constraints, not theory
  Illia explains that the shift from recurrent networks to attention was driven by speed and parallelization needs at Google, not a desire to invent a new paradigm.
• AI’s step change was foreseeable to early builders
  Illia expected a ChatGPT level breakthrough several years before it arrived, based on clear research signals and accelerating model performance.
• Provenance and trust will define the next phase of AI
  As AI systems can be subtly manipulated, Illia argues that verifiable data pipelines and transparent training processes are essential to prevent large scale misinformation.
• Ownership and identity matter in an agent driven world
  Illia believes individuals will soon rely on AI agents that act autonomously, making it critical that users own their models and that interactions between agents are secured and verified.

https://near.ai – NEAR AI Cloud and Private Chat products are now live, try them here
Illia's X: x.com/ilblackdragon
Illia's Substack: ilblackdragon.substack.com
NEAR X: x.com/nearprotocol

00:00 Intro: AI and Information Control
00:29 Meet Illia Polosukhin: Co-Author of 'Attention is All You Need'
01:03 The Evolution and Impact of AI
13:24 The Birth of Near AI and Blockchain Integration
15:16 Challenges and Innovations in Blockchain and AI
22:17 Privacy and Security in AI Applications
26:58 Exploring Sleeper Agents in AI
29:19 Practical AI Implementation in Teams
30:06 AI's Role in Product Development
31:41 Challenges and Future of AI in Development
36:35 AI and Economic Alignment
41:46 The Future of AI Agents
44:14 Debrief

📜 Read the transcript for this episode: Transcript of The Future Of AI With Illia Polosukhin: The Man Who Put The T In GPT |

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.

In this teaser, Jeremy and Henrik reflect on their conversation with Illia Polosukhin, co-author of the “Attention Is All You Need” paper and founder of Near Protocol. They dig into Illia’s early expectations for ChatGPT, why “owning your AI” isn’t just a catchphrase, and how blockchain could help protect the information we rely on. They also explore what it really means to work with AI and why your own experience might be more powerful than you think.
Full episode dropping soon.

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.

In this episode, Christian Keller joins Henrik and Jeremy to explain how world models are shaping the next stage of generative AI. He talks through how AI learns using different types of inputs, and why video adds a sense of continuity, change, and cause and effect that text alone does not provide. Christian shares vivid analogies and clear examples to show what multimodal models make possible.

The conversation moves into how AI is now used throughout the research process, from generating synthetic data to evaluating model outputs. Christian shares how this loop is already in motion and how AI is helping scale and accelerate experimentation. He also reflects on the shift after ChatGPT launched, and how that changed the pace and structure of research work.

Later in the episode, Christian describes how individual workflows are evolving, and how asking simple questions like “Could AI help with this?” often opens new possibilities. He shares examples from his own work and home life, including how his wife built and graded her own French exercises using generative tools.

Key Takeaways:

• Text removes essential information
  Christian explains that text compresses reality and loses detail, context and temporality. Images and video help restore what text leaves out.
• World models give AI a sense of change
  Video introduces the before and after and how things move or enter a scene. This helps models learn cause and effect and builds more robust understanding.
• AI helps build AI
  Models can generate data, evaluate results and support researchers during development. Christian shows how this creates new ways of scaling experimentation and training.
• Workflows shift when AI handles early steps
  Christian shows how tasks like debugging and prototyping change with generative tools, which reshapes roles and opens new opportunities for innovation.

LinkedIn: Christian Keller | LinkedIn

00:00 Intro: Information Compression
00:37 Meet Christian Keller: AI Expert
01:13 The Evolution of AI Products
02:11 Impact of ChatGPT on AI Development
02:38 Understanding PyTorch and Its Role
07:41 The Bitter Lesson in AI
09:12 Challenges and Future of AI Models
18:57 Using AI to Build AI
23:25 Innovative Chat Interfaces
23:41 Building the Autos Platform
24:35 Epiphanies in AI Integration
25:18 AI in Entrepreneurial Workflows
26:32 Challenges in AI Integration
31:15 Bias in AI Models
38:06 Debrief

📜 Read the transcript for this episode: Transcript of AIs Next Frontier: World Models Explained by Christian Keller |

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.

In this teaser, Jeremy and Henrik break down their immediate takeaways from their conversation with Christian Keller, including model fidelity, hallucinations, and the surprising ways AI is already reshaping everyday workflows.
Full episode drops tomorrow.

For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin:

Henrik: https://www.linkedin.com/in/werdelin
Jeremy: https://www.linkedin.com/in/jeremyutley

Show edited by Emma Cecilie Jensen.