The Friday Brain Upgrade: The bee sting that woke me up to AI disruptionThe bee sting that woke me up to AI disruptionI remember that Slack conversation with my boss 2.5 years ago vividly. “Basti, now that I can ask AI about Agile… what do I need your role for?” I was so fucking terrified. Not angry. Terrified. We were just exchanging AI impressions in a casual conversation. I was getting into the topic without real exposure yet. What did I do? Denial. Classic human response to exponential change. But here’s the thing… Back then, AI wasn’t yet that powerful. So it was easy to find arguments showing why AI wouldn’t be a danger. But this argumentation was based on a narrow context window and very narrow time horizon prediction. As humans, we’re terrible at predicting exponential changes. It was easy to argue away. But that conversation was an impulse. Like a bee sting. Andy Grove called these “strategic inflection points” - moments when 10X forces emerge that are ten times more powerful than normal competitive forces. Clayton Christensen warned us about this in ‘The Innovator’s Dilemma’ - disruptive technologies don’t announce themselves. They start small, seem harmless, then suddenly they’re everywhere. This means the old rules don’t apply anymore. In your career, this looks like: your expertise becoming commoditized overnight. AI’s disruptive nature creates exactly this strategic inflection point. Grove warned us: “Getting through a strategic inflection point involves confusion, uncertainty and disorder.” I was living proof of that confusion. But he also said something that terrified me even more: ”The greatest danger is in standing still.” Wait a minute… I was doing exactly what Grove warned against: standing still while the 10X force was building around me. That’s when I knew denial wasn’t an option. So what did I do? Here’s where everything changed: I realized I had to move. Fast. Back then, I was already growing my understanding of better learning methods. Working at Blinkist, learning was everywhere. With my newly developed note-taking approach and basic understanding of externalizing thinking, I went on an AI learning journey. The AI Playbook gave me my first real understanding of prompt engineering. AI courses and conferences - including a Mindvalley AI summit - provided wide-range overviews of capabilities and impact potential. But it was the practical use cases that mattered. Immediately applying AI for crafting workshops. Supporting my need to build sessions fast. The ease of summarizing sessions. Small, initial steps to invite AI into my daily work. Then came the real test. I moved from Agile Coach & Product Coach to our Leadership Course Design team. Team builder experience, workshop design skills, and team lead backing equipped me for building live sessions. That was a steep, fast learning curve. Working in a startup inside a startup meant high speed. I had to access previous learnings fast. Scan material fast. Design exercises and session flows fast. Not with hundreds of people, but in a fast-pacing, small, agile team setup. Here’s what made the difference: Speed to work with insights and previous learnings. When I could build off previous experiences - especially when I’d already invested in externalizing my learnings and insights - the difference was huge. When I’d collected insights from various sources and integrated them into one easy-to-access system. The breakthrough insight: When you externalize and centralize thoughts, you can increase speed to building new things. When I could access my presentations, workshops, and thoughts about Agile Coaching, I built an Agile Practitioner course. Even for topics rather new to me - DEI initiatives, Women in Leadership - the system of externalizing insights and nurturing insights from collaborations and research was incredibly helpful. The main ingredient? Fast iterations with AI. I’d use AI to think through complex topics - breaking down learning theories, exploring different angles on workshop design. Then I’d delegate the nitty-gritty detail tasks - formatting, research, initial drafts. Orchestrated by me, but with strong delegation of work aspects to AI. Zooming out, this transformation is happening everywhere. Sure, companies need time. Sure, we see failed adoptions. And yes, we get trapped by early-stage denial again. But here’s what trips us up: our human limitations in predicting long-term changes and our consistent underestimation of exponential growth. Then came my wake-up call. I went from being a €130k Agile Coach to a line item on a spreadsheet. The humiliation was crushing. 24 years of expertise, reduced to a cost center. But here’s what I realized: they weren’t firing me because I was bad at my job. And that realization? It was liberating. That’s when everything changed. As a solopreneur, I’m now in the high-speed zone. My financial survival depends on removing friction. Depends on fast build-measure-learn cycles. Depends on speed, decisions, and action. The transformation is complete. Here’s what it looks like: Comparing my past approach to how I work today? It’s a 180° turn. Today I work with 40 AI assistants. They support, guide, coach, and train me in most aspects of running my business. It’s fast, and solution quality keeps increasing. Let me show you what this looks like in practice:Last week, I needed to design a session on “Efficient usage of AI assistants.” Old me: Days of research, reading papers, creating slides from scratch. New me: 4 hours. Here’s how:
The result? A workshop that would have taken me days now takes less than a day. That’s not efficiency. That’s transformation. 4 examples of approaches that changed for me:
These are many shifts of approches and tools in parallel. This isn’t the first time this has happened. When personal computers emerged in the 1980s, some accountants embraced spreadsheet software. Others insisted on their calculators and ledger books. Guess which ones were still employed in 1995? The pattern is always the same: new technology emerges → early adopters gain massive advantages → laggards become obsolete. The only difference now? The cycle is happening in months, not decades. What matters for all of them? Context. When I can provide deeper insights - my understanding of 4MAT or Five Lightbulbs - I can leverage AI assistants’ strength and tailor them to my needs. The gain in speed, quality, and finding paths to apply insights is mindblowing. The full journey: It started with that frightening moment of realizing my 13-year role would vanish. It continued with job transitions and high-speed learning. The final needle mover? Detaching from employer dependency. To take that step, I had to enable fast-pace learning, rapid iterations, and business operations for myself. My already-available foundation for learning and applying through externalized insights helped immensely. My proficiency in embedding AI in workflows was crucial. Now compare that to my former colleagues who are still doing things the old way:
That’s the difference between riding the wave and being crushed by it. Here’s why this approach works: We can agree that AI is getting more powerful every month, right? And we can agree that the professionals who thrive will be those who leverage AI, not compete with it? So if that’s true, then the logical conclusion is: the faster you integrate AI into your workflow, the bigger your advantage becomes. It’s not about being replaced BY AI. It’s about being replaced by someone who USES AI better than you do. If I could pass my past self 4 survival strategies for AI disruption, they would be:1) Become AI proficient (not just aware)It enables everything else. Start small and iterate with AI experience. All sources are available - you just need to take the steps. 2) Externalize everything (your brain is not a storage device)Only when you get thoughts from your head into notes can you leverage full AI power. Then you can leverage your brain at a much higher level. 3) Build your knowledge stack (employment is temporary)Grow your own insights stack and detach from employment dependency. Jobs are under pressure. Have your things together. Become highly adaptable. When you can tap into your wisdom and derive action from previous learnings, you can shift gears when needed. 4) Invest in fast-lane learning (time is your enemy)Don’t wait for employers to finance your path. Sometimes you must invest in your future from your own pocket. I invested $6k in group coaching, $4k in Building a Second Brain, $1k+ in marketing courses, plus many smaller insights. Compared to doing it alone, this was essential for speed. Here’s the reality check: If you’re still waiting for your employer to upskill you, and you think AI won’t affect your role, and you believe gradual change is enough… You’re about to become a statistic. Not in 10 years. Not in 5 years. Right now, someone in your field is building what you do - but faster, cheaper, and with AI assistance. I know that sounds challenging. I hear you. I’ve been there too. But I can assure you - it’s about taking the steps. And leveraging clever supporting systems. Imagine this in just 9 weeks: While your colleagues are still googling basic questions, you’re synthesizing insights from your externalized brain and 40 AI assistants. You’ll be building solutions while they’re still understanding problems. That’s the speed advantage of an integrated learning ecosystem. Learning Ecosystem Mastery combines AI learning with building your personal knowledge system. It’s about rediscovering the joy of curiosity and having those “aha moments” that change everything. Learn smart, Basti P.S. Cohort #02 starts in July. Limited to 25 attendees. If you’re ready to stop being a statistic and start building your AI-integrated learning ecosystem, just reply with ‘ECOSYSTEM’ and I’ll send you the details for Cohort #02. P.P.S… To respond to this newsletter, just hit reply. I love getting replies, read all of them, and reply to as many as possible(And if you received this email from a friend, and would like to subscribe, please go here: https://pages.quintsmart.com/) I will publish my newsletter every Friday at about 13:00 o’clock CET. See you next Friday. |
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