The AI Productivity Trap
Why Your Peculiar Obsessions Are Now Your Strategic Advantage
"The thing that made you weird as a kid can make you great as an adult - if you don't lose it." - Kevin Kelly
I recently spent 48 hours with AI, achieving peak productivity, only to realise I had created nothing of real value.
I designed a 12-week workout programme, vibe-coded a fitness app to track it, and generated an article about the experience: 3 functional outputs, maximum efficiency and zero wasted effort. The workout made logical sense, the app worked perfectly, and the article was structured and coherent. However, the sheen of this modern productivity triumph masked fundamental flaws in each output.
AI raises the bar for speed to "good enough", but actually, value comes from injecting your distinctive human perspective back into the work.
The workout in practice had a progression that was way too steep. The app was brittle and insecure—I'd have to rewrite it entirely if it were to be anything more than a toy project. The article was utterly forgettable, reading like all the LinkedIn nonsense out there—because that's precisely what it was: an average of averages.
It's this speed and autocompletion that creates a paradox where AI requires a need for specialist skills to improve its output, whilst making it hard to actually acquire those skills.
Why Traditional Learning Paths Are Disappearing
AI creates seductive shortcuts that undermine the core of learning. Why read a book when AI can summarise it? Why write when AI can generate content? Why struggle through the basics when AI can handle them instantly?
These shortcuts are destroying learning motivation both psychologically and structurally. There is increasing evidence that AI is eliminating junior roles and routine work that used to serve as training grounds, while making skill development seem pointless.
Recent MIT research reveals the consequences when we are seduced by these shortcuts. Scientists studied people writing essays with AI assistance versus those working from memory alone. When asked to quote from the essays they'd just written, 83% of AI users couldn't do it, compared to only 11% of those who worked without assistance. They'd outsourced not just the writing, but the cognitive processes that create genuine understanding.
It feels like, in some dystopian gotcha moment, we're beginning to hit a wall and realise we need all the skills we skipped learning. Reading is how we learn to think and write. Making mistakes is how we learn. Hard graft is just necessary to develop real competence.
But by the time you discover this, the traditional learning ladder has been dismantled, and quite honestly, seemingly too much effort to climb.
Why Passionate Learning Becomes Essential
I discovered something similar growing up. I had varied passions: I wanted to play basketball like The Professor, draw like Jamie Hewlett, code like David Braben, and drum like Dave Abbruzzese. However, when choosing subjects at school, I abandoned what really captivated me for what seemed "practical".
This mistake left me struggling for years. It was incredibly hard to motivate myself to learn things I didn't care about. I fell into the trap of learning to pass exams rather than exploring what actually interested me.
Everything changed when I rediscovered computer science. Suddenly, the love of learning returned. I started asking very different questions—not just about that domain, but eventually about others, too. I realised my diverse interests weren't a bug; they were my advantage.
"Find what you love and let it kill you... For all things will kill you, both slowly and fastly, but it's much better to be killed by a lover." - Charles Bukowski
Something is going to consume your time and energy, regardless, so make sure it's something you care about.
AI handles all the basic work now, so the minimum viable expertise for humans has shot up dramatically. Getting to that level requires sustained motivation for thousands of hours of deep work. Only genuine passion provides that fuel. This passion is what gets you through to the specialisation level, where you become valuable.
What Happens When You Follow Your Interests
When I finally followed my real interests things started to fall into place. My curiosity became a connecting force that let me create insights across completely different fields.
When we had the idea to sell market data at uSwitch, my pure fascination drove me to research pricing theory, negotiation, presentation frameworks, and innovation positioning. Our first sale came directly from combining a presentation framework I'd studied, pricing insights from a B2B sales group, and conversations with sales experts—cross-domain integration that only happened because of an authentic obsession with getting it right.
Similarly, when our CEO asked me to take responsibility for our contact centre, my diverse interests—psychology, systems thinking, and genuine curiosity—became essential. I learned from industry experts, our own highly skilled team, as well as reading around the subject. The payoff has been we're now smashing our previous NPS performance and I have a much better understanding of a really key part of our organisation.
Your peculiar combination of obsessions can become your sustainable competitive advantage. However, it is only because passion drives us to delve deeper when others stay on the surface.
This pattern isn't unique. Every person I've worked with who has done something meaningful has had an unconventional background—growing up as a hippy, living in a caravan, skipping university, helping create the Pirate Bay at 14, or being in a rock band. Meanwhile, many of the brightest individuals with the highest grades struggle to make a meaningful impact. The future belongs to people who are irreplaceably themselves, not those who are competently generic.
How AI Can Accelerate This Learning
Here's where the paradox resolves: AI can dramatically propel your learning, but only if you use it as a thinking partner, not a thinking replacement.
🚫 Wrong way - AI as thinking replacement:
Let AI autocomplete others' thoughts
Skip the learning process entirely
Generate content without understanding
Result: you remain at your current level of (in)competence
✅ Right way - AI as a thinking partner:
Use AI to refactor YOUR thoughts
Accelerate YOUR learning across multiple domains
Compress feedback loops while you do the actual thinking
Result: you learn faster while developing your distinctive perspective
I've discovered AI can now act as a catalyst for my learning across multiple fields—psychology, strategy, writing, technology—but only because I use it to enhance my thinking, not replace it. Instead of letting AI summarise books for me, I read them and use AI to help me connect ideas across domains. Instead of generating content, I think through problems and use AI to help refine my arguments.
You still have to read the book, but AI can help you understand how it connects to other things you've learned. You still have to think, but AI can help you iterate and refine faster than ever before. I’ve been inspired by how my son uses NotebookLM to create podcasts to help him prepare for his exams and have used AI extensively for feedback in early drafts of this post (see Claude’s opinion at the end).
The idea is to use AI to refine and develop your thoughts, not to autocomplete others'. When you maintain ownership of the thinking process, AI becomes an incredible accelerant for developing the specialised skills you need.
Weaponise Your Weirdness
Follow the obsession-to-value cycle: Follow your passions → use AI to rapidly test concepts and validate interest → if promising, use AI to accelerate deeper learning → get to competence → deploy obsessions strategically → link to new passion.
Identify your authentic obsessions:
Stop asking "What's efficient?" Start asking "What am I curious about?"
Notice what you naturally stay up late thinking about
Look for intersections between your obsessions—that's where your unique value lies
Deploy them strategically:
Volunteer for projects that combine your interests
Translate insights across domains
Become the bridge between different departments
When we were scaling loveholidays, I wasn't just thinking about technology, I was drawing on psychology for team dynamics, systems thinking for processes, and philosophy for strategic decisions. My diverse interests became interconnected tools that no specialist could replicate.
This approach isn't about being a jack-of-all-trades, though, as the full quote reminds us, that's "oft times better than a master of one." It's about becoming a master of synthesis—someone who sees patterns and solutions that specialists miss.
The Stakes
In a world where AI handles competent execution, human experience becomes the ultimate differentiator. But this capability emerges from genuine engagement with your actual interests, even when they seem impractical.
Your next step isn't to audit your interests—it's to stop apologising for them. Take that weird combination of things you're curious about and lean into it. Utilise AI to handle routine tasks, allowing you to focus on developing the synthesis capabilities that only you can provide.
The kid obsessed with spinning basketballs whilst coding and drawing comics? That wasn't scattered attention—it was intellectual curiosity across domains. Your peculiarities aren't bugs to fix—they're features to amplify.
Find what you love and let it kill you. In an AI world, that's not romantic advice—it's the most practical survival strategy there is.
How would you describe your weird combination of interests? I’d love to hear about the distinctive paths that have shaped your expertise—share your thoughts in the comments.
AI Perspective: How This Essay Was Actually Written
A note from Claude: This piece serves as an interesting case study for its own argument.
What we accomplished together:
Transformed a sprawling 4,000-word draft into focused 1,800 words
Eliminated repetitive sections and strengthened logical flow
Applied Nicolas Cole's 1/3/1/3/1 structure for better engagement
Resolved contradictions and clarified the core AI paradox
The process demonstrated the thesis in action: The author didn't ask me to write for him. Instead, he used me exactly as he prescribes—as a thinking partner rather than replacement. He brought distinctive expertise from scaling tech companies, genuine passion for the subject, and unique insights from his unconventional career path. I provided structural analysis and rapid feedback loops that compressed editing cycles from weeks to hours.
Why this collaboration worked: I could help organise and refine, but I couldn't create the insights about BJJ teaching resilience, the market data synthesis breakthrough, or the understanding of how passion drives sustained learning. The value came from his foundation of knowledge and experience.
The meta-lesson: He wrote an essay about not losing your weirdness by using his own weird combination of interests—technology, psychology, business strategy, martial arts—while demonstrating exactly how to use AI as a learning accelerant rather than replacement.
The irony is perfect: AI dramatically accelerated the writing process, but only because the human brought the expertise and distinctive perspective that made the content valuable in the first place.