Bots & Bosses (english)

Bots & Bosses (english)

By Dominic von ProeckBusinessEntrepreneurshipTechnologyEducationHow To
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Bots & Bosses (english) episodes

  • Insights from Silicon Valley: Is Europe Really Falling Behind in AI?
    Sources
    Dominic’s conversations with a private equity firm, the service company of a major AI lab, and a startup from Y Combinator
    (anonymized background conversations, no public links)
    Andreessen Horowitz:
    State of Markets II
    ChainCatcher:
    Summary of the report “State of Markets II”
    Amazon Web Services:
    AWS Global Startup Trends Report
    Softprom:
    AWS Engines of Growth 2026
    heise online:
    Massive transformation canceled: Meta wanted to become “AI-native” and failed
    CTA Links
    - Leaders of AI: https://www.leadersofai.com/
    - Newsletter: https://www.leadersofai.com/newsletter
    - MBAI: https://www.leadersofai.com/
    - AI Integration Expert: https://www.leadersofai.com/
    6 min
  • Jev Shows Where AI in Companies Is Really Heading
    Summary:
    Jev is not a topic just because it is loud right now. For us, it is an early indicator. In this episode, we explain why new AI names only become relevant when they truly change something for companies: in costs, processes, dependencies, and operational execution.
    Key Topics:
    - What Jev actually is: a decision model instead of a classic language model
    - Why specialized models for routing, evaluation, and prioritization are becoming relevant
    - What this means for European companies and sovereignty
    - How we at Leaders of AI evaluate new players
    - Three questions you can apply directly to your own day-to-day work
    Mentioned Resources:
    - TypeSafe AI launch post on System One Models and Jev
    - Trending Topics analysis of Jev and TypeSafe AI
    - Global Tech Council guide to Jev AI
    Sources:
    - TypeSafe AI. Introducing System One Models and Jev. 15.09.2026. https://typesafe.ai/blog/introducing-system-one-models-and-jev
    - Trending Topics. Jev: A New AI Model That Refuses to Write Text Has Developers Hooked. 22.09.2026. https://www.trendingtopics.eu/jev-a-new-ai-model-that-refuses-to-write-text-has-developers-hooked/
    - Global Tech Council. Jev AI: Complete Guide. 23.09.2026. https://www.globaltechcouncil.org/ai/jev-ai-complete-guide/
    - Google Doc Briefing. Have you heard of Jev yet? Accessed 01.10.2026. https://docs.google.com/document/d/12bt4FPzV8r4r-V2eaHqWfT9bIYTDUrtELDDOD1OysyM/edit?usp=sharing
    CTA Links:
    - Leaders of AI: https://www.leadersofai.com
    - Newsletter: https://www.leadersofai.com/newsletter
    6 min
  • Fluid Teams: Why We No Longer Have to Choose Between Agents and an Operating System
    Agents or operating system? For three episodes, we explored this question. In the grand finale of our series, we resolve it and present a third approach: Fluid Teams.
    In this episode, you will learn:
    - Why the question “agents or operating system” is the wrong question
    - What connectability means and why it decides the value of AI
    - How the formula “value equals quality times connectability” works in practice
    - What Fluid Teams are and how AI calculates the best AI setup by itself
    - Two concrete examples from the everyday work at Leaders of AI
    - Why Fluid Teams are currently research, and when results can be expected
    This is Part 4 and the finale of our blog and podcast series on AI architecture in companies.
    Sources:
    - Physaric, Leaders of AI: Connectability. The underestimated factor that decides the value of AI. Guide for leaders, 2026
    - Physaric, Leaders of AI: Why AI often stays ineffective. A formula for the value of human-AI collaboration. Working paper, 2026
    - Leaders of AI blog series: AI architecture in organizations: [Part 1,](https://www.leadersofai.com/blog/sind-ki-agenten-schon-wieder-outdated) [Part 2](https://www.leadersofai.com/blog/vorteil-von-ki-agenten), [Part 3](https://www.leadersofai.com/blog/dein-ki-betriebssystem-kann-alles-dein-team-nutzt-es-trotzdem-nicht), [Part 4](https://www.leadersofai.com/blog/fluide-teams-das-grande-finale-unserer-serie-zu-agenten-und-betriebssystemen), 2026
    - Thariq Shihipar, 2026: [Anthropic: Dynamic Workflows in Claude Code](http://x.com/trq212/status/2061907337154367865)
    More about Leaders of AI: [leadersofai.com ](https://www.leadersofai.com/)
    Newsletter: [www.leadersofai.com/newsletter](https://www.leadersofai.com/newsletter)
    5 min
  • Your AI operating system can do anything. Your team still doesn’t use it.
    An AI system that can do everything, knows everything, and connects all departments. Sounds perfect. We tested it for six months in parallel with our 53 AI assistants. The result surprised even us.
    In this episode, you’ll learn:
    - What makes the AI operating system different from the agent approach
    - Why a system without a face and a role does not build trust
    - How an AI system checks itself, and why that is a problem
    - How a governance incident showed us where the real risks are
    - Why the agent approach is human-first and the operating system is AI-first
    - The key question that shows you which approach fits your company
    This is part 3 of our blog and podcast series about AI architecture in companies.
    Sources:
    - Leaders of AI blog series: AI architecture in organizations, part 1–3
    - Internal self-experiment
    More about Leaders of AI: leadersofai.com
    Newsletter: [www.leadersofai.com/newsletter](https://www.leadersofai.com/newsletter)
    6 min
  • The most surprising benefit of AI agents? Humanity.
    AI agents are a turbo boost in companies mainly because they make trust, roles, and responsibilities visible—not because of some technical trick. In this episode, you’ll learn why agents fit into everyday work so quickly, and how clear leadership logic helps you keep adoption, quality, and governance stable.
    - Why AI projects rarely fail because of tools—but because of unclear goals, vague responsibilities, and missing quality standards
    - Think of agents as “roles on the team”: delegate, review, build feedback loops, keep ownership (instead of believing in a black box)
    - How we work at Leaders of AI with 10 people + 50+ AI colleagues—and why names like Monika, Helga, or Paula are interface design for responsibility
    - Scaling without chaos: orchestration instead of model power (example: Jürgen as a “manager agent” → less coordination, more stable quality)
    Sources: [Measuring Human Leadership Skills with AI Agents](https://www.nber.org/papers/w33662), Harvard Kennedy School / NBER, 2025.
    More info at: https://leadersofai.com. And here is our newsletter: https://www.leadersofai.com/newsletter
    6 min
  • Europe 2031 Review: Europe’s AI future will be decided in how it is used
    In this episode, it’s about a simple but crucial idea:
    Europe’s AI future will not be decided by models, but by execution, enablement, and how organizations apply AI.
    You’ll learn:
    Why the real AI bottleneck in Europe is not attention, but application
    Why access to tools alone does not create an advantage
    Why teams, processes, and enablement will matter more than the next big AI announcement
    More about Leaders of AI:
    [https://leadersofai.com](https://leadersofai.com/)
    Newsletter:
    5 min
  • Dominic’s Digital Twin

    In this episode, it’s about Dominic’s digital twin and the question of why a twin is not a replacement for leadership, but a tool to make leadership logic available in hybrid organizations.

    You will learn:

    • why a digital twin is more than a copy
    • why leadership principles in agentic organizations must be made explicit
    • why orientation matters more than perfect imitation
    • what happens when teams and AI systems work more independently
    • why strong AI organizations don’t fail because of models, but because of vagueness

    More info at: https://leadersofai.com.

    And here is our newsletter: https://www.leadersofai.com/newsletter

    5 min
  • From Homo Sapiens to Homo Agenticus
    In this episode, it’s about the AI paradox: why strategically outsourcing routine work to AI does not automatically make us more superficial, but—at best—can help us reflect better.
    You’ll learn:
    - why the debate about “lazy-thinking students” misses the point
    - what Wang and Zhang found in their study with 912 students
    - why cognitive offloading does not automatically mean less thinking
    - why efficiency and critical review do not contradict each other
    - what we mean by the term Homo Agenticus
    Sources and mentions:
    - Wang & Zhang (2026):
    - More about Leaders of AI:
    - Newsletter:
    6 min
  • How self-learning AI is shaping our marketing
    In this episode, it’s about how self-learning AI is shaping our marketing – and why this creates a new leadership task.
    You’ll learn:
    - why our LinkedIn performance suddenly dropped, even though we had good content
    - how a second agent analyzes the data and directly improves the skills of the first
    - why marketing is an ideal starting point for self-learning AI systems
    - why the real challenge is not technology, but leadership
    - why in the future the key question won’t be whether AI learns, but where it learns toward
    Sources and mentions:
    - Business Punk column by Dominic von Proeck, published on 01/06:
    - More about Leaders of AI:
    - Newsletter:
    4 min
  • What 81,000 people want from AI
    In this episode, it’s about a surprisingly simple insight from 81,000 interviews: people mainly want AI when it saves time, helps them do better work, and speeds up learning.
    You’ll learn:
    - why this insight matters more for companies than it seems at first
    - which three motives are behind real AI adoption
    - why unreliability and job worries remain the biggest brakes
    - why leaders need to translate AI not through tools, but through specific use cases
    - why reliability is the real lever for adoption
    Sources:
    - Anthropic: What 81,000 people want from AI:
    - More about Leaders of AI: [https://www.leadersofai.com](https://www.leadersofai.com/)
    - Newsletter:
    - Blog: [www.leadersofai.com/blog/was-81-000-menschen-von-ki-wollen](www.leadersofai.com/blog/was-81-000-menschen-von-ki-wollen)
    5 min

About Bots & Bosses (english)

From the publisher's feed

10 humans. 50+ AI colleagues. A company that feels like science fiction – but it's just our Tuesday. In "Bots & Bosses" we share what we learn at Leaders of AI every single day: Which AI assistants shine, which ones mess up spectacularly, and why Jürgen – our AI team lead – still got promoted.