What if you could send something from today to your younger self 15 years ago? What would it be?
For most of us, the answers range from practical to profound: stock tips, relationship advice, or perhaps a stern warning about that regrettable haircut. But here’s a more intriguing proposition: What if you could send the latest AI technology back to 2010?
Imagine a younger version of yourself receiving a laptop equipped with today’s sophisticated AI tools like DeepSeek running locally via Ollama or LM Studio, accessible offline, requiring no cloud subscription, no data privacy concerns. Just pure computational intelligence at your fingertips, 15 years ahead of schedule.
How would that single intervention transform your trajectory? And more importantly, what does this thought experiment reveal about how we’re using, or underutilizing, the AI tools available to us right now?
When Web Design Was the Future
Fifteen years ago, I was convinced that web design was my golden ticket. I spent countless hours mastering Photoshop gradients, learning CSS float layouts (before Flexbox existed), and debating whether to use jQuery or prototype.js for animations. The landscape felt infinite with possibility, yet impossibly constrained by what I didn’t know.
The challenges were relentless: debugging cross-browser compatibility issues that consumed entire weekends, manually coding responsive layouts before frameworks existed, and struggling to teach myself programming concepts from scattered blog posts and Stack Overflow threads that didn’t always have answers. Every project felt like reinventing the wheel because the collective knowledge we take for granted today simply wasn’t accessible or organized.
Now imagine dropping an AI-equipped laptop into that scenario, specifically, one with DeepSeek R1 running locally. You install Ollama, open your terminal, run ollama pull deepseek-r1:7b, and suddenly you have a reasoning-capable AI assistant that works entirely offline. No API costs. No monthly subscriptions. Just instant access to a thought partner that can explain complex programming concepts, debug your code, suggest optimal solutions, and even help you understand the underlying principles of computer science you’re missing from your self-taught journey.
The transformation would have been staggering. Those weekend debugging sessions? Reduced to hours. The anxiety about choosing the right career path? Mitigated by an AI that could help you explore multiple trajectories, skill gaps, and emerging opportunities. The isolation of self-directed learning? Replaced with a 24/7 mentor that never tires of your questions.
The Compounding Effect of Accelerated Learning
The true power of this thought experiment is about acceleration. When you compress learning curves, you don’t just save time; you fundamentally alter what becomes possible.
In software development, having AI assistance in 2010 would have meant building more sophisticated applications earlier. Developers could have experimented with machine learning concepts before they became mainstream, created more robust systems with fewer security vulnerabilities, and potentially accelerated the entire industry’s evolution by several years.
In healthcare, imagine medical students and researchers with AI-assisted analysis of medical literature, pattern recognition in patient data, and hypothesis generation for clinical trials, all running on local machines without privacy concerns. The COVID-19 pandemic response might have looked dramatically different if the preceding decade had normalized AI-assisted medical research and drug discovery.
In education, teachers equipped with AI tools in 2010 could have personalized learning paths for students, identified knowledge gaps in real-time, and created customized curricula that adapted to individual learning styles, long before “personalized learning” became an educational buzzword.
In creative industries, writers, designers, and artists would have had an intelligent collaborator to push past creative blocks, explore variations rapidly, and learn new techniques at an unprecedented pace. The barrier between imagination and execution would have shrunk considerably.
The pattern is clear: AI doesn’t just make existing work faster; it makes previously impossible work feasible.
The Productivity Paradox We’re Living Right Now
Here’s the uncomfortable truth this thought experiment reveals: We’re living in that future right now, and most of us aren’t capitalizing on it.
The tools exist. You can install Ollama or LM Studio today. You can run DeepSeek R1 locally on your machine. You can have that AI assistant I fantasized about having in 2010. Yet organizational adoption remains sluggish, individual usage is often superficial, and we’re collectively experiencing what historians might call “the great AI lag”, the gap between technological availability and practical implementation.
Why? Because transformation requires more than tools; it requires mindset shifts, workflow redesigns, and a willingness to fundamentally rethink how we approach problems. My 2010 self wouldn’t have automatically become a better developer just by having AI, I would have needed to learn how to ask better questions, how to verify AI outputs critically, and how to use it as a thinking partner rather than a replacement for thinking.
Your Time Machine Moment Is Now
The real lesson from our thought experiment isn’t about regret for what could have been. It’s about recognizing that future generations will look back at 2025 the same way we just looked at 2010. They’ll wonder why we had such powerful tools and used them so timidly. They’ll be puzzled by our hesitation, our skepticism, and our failure to fully integrate AI into our daily workflows.
What’s your “what if” scenario? If you could send AI back to your earlier self, what specific challenge would you address? What career pivot might you have made sooner? What creative project would you have attempted that seemed too daunting?
More importantly, what are you going to do with the AI tools available to you right now?
The time machine you wished for already exists. It’s called the present moment, and it’s equipped with technology that would have seemed like science fiction just a few years ago. The question is what you’re going to do differently starting today.
Could you share your time machine thought experiment in the comments on Substack? What would AI-equipped you have accomplished 15 years ago? And what will AI-equipped you accomplish in the next 15 years?
Dejan Majkic
