OMR Education · OMR Education / Rolf Hermann / Andre Alpar / Tarek Müller

So entgehst du dem KI-Burnout mit Jens Polomski von SnipKI

·37 min·3 clips

Jens Polomski explains how AI overuse causes 'brain fry' and why work becomes more intense, not easier.

1. OMR Education host Rolf Herrmann interviews Jens Polomski, founder of SnipKI, on the topic of AI burnout and cognitive overload from excessive AI tool use. 2. Polomski is a Cologne-based entrepreneur who has spent 15 years in marketing, founded SnipKI as a KI Enablement company for the German Mittelstand, and runs one of Germany's largest AI newsletters. 3. The episode addresses the central paradox that AI, sold as a productivity tool, is making many workers' days more intense rather than easier, and examines why this happens and what to do about it. 4. Polomski references a BCG study published in Harvard Business Magazine coining the term 'AI Brain Fry' to describe the cognitive depletion caused by over-reliance on AI tools under escalating workplace expectations. 5. He explains that once companies roll out tools like Microsoft Copilot — citing a real case where a large energy provider bought 700 Copilot licences with no adoption plan — managers immediately expect tasks that took two days to be completed in one hour. 6. Polomski describes the 'New Shiny Object Syndrome': the habit of hopping from tool to tool whenever a new AI product launches on LinkedIn or X, driven by clickbait like 'the 10 best AI tools' rather than focused problem-solving. 7. He argues that differences between leading language models have become marginal for most practical tasks, and that benchmarks measuring coding or mathematics performance are rarely relevant to the average business user. 8. The hammer-and-nail metaphor captures his core advice: a solid grasp of a basic tool beats owning a fancy one that lights up and sings but whose user doesn't know how to drive a nail. 9. Polomski identifies a structural cause of AI burnout specific to German companies: basic digitalisation was never mentally completed, meaning employees don't know what a digital process is, yet are now expected to run autonomous agent systems. 10. He describes visiting marketing teams who have no concept of process automation and asks, 'How have you been working for the last five or ten years?' — illustrating the gap between where organisations are and where AI adoption assumes they should be. 11. SnipKI's KI-Führerschein (AI driving licence) programme is positioned as a solution to this gap, offering structured foundational education before companies attempt advanced AI deployments. 12. Polomski recommends FOMO management through curation: selecting two or three trusted newsletters and one podcast rather than subscribing to every channel, and using AI itself to generate a daily summary from chosen sources. 13. He describes his 'second brain' system — built in part using OpenCrawl — that collects lecture transcripts, articles, and notes, allowing him to query his own knowledge in plain language rather than clicking through file folders. 14. For daily AI-assisted workflows, he recommends starting the morning with an AI-generated briefing covering the previous 24 hours' AI news, web traffic anomalies, email marketing performance, and calendar conflicts. 15. On Sunday evenings, he uses AI to map the coming week, identifying scheduling conflicts and task blockers before they become Monday crises. 16. He concedes he is still FOMO-susceptible but says the act of consciously reducing information sources provides measurable peace of mind and better focus. 17. The conversation is a relaxed, two-person interview recorded late in the evening — Polomski mentions the baby monitor next to them — giving it an informal, unguarded quality. 18. Herrmann asks probing follow-up questions that push Polomski to be specific and personal rather than staying at a general advisory level, producing concrete anecdotes and named tools. 19. Marketing professionals, team leads, and small-to-medium business owners who feel overwhelmed by the pace of AI development will find practical frameworks in this episode. 20. Listeners seeking technical deep-dives into model architecture, code, or enterprise-scale AI deployments will find the episode too high-level.

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