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The Disappearing Struggle: Intelligence, Ego, and the Meaning of Work in the Age of AI

There was a time—not long ago—when writing code felt like entering a duel with complexity itself. You would sit for hours, sometimes days, holding entire systems in your mind. Variables, logic flows, edge cases, syntax rules, memory constraints—all competing for attention. It was exhausting. Mentally expensive. At times even painful. But when it worked—when the code finally ran as intended—the reward was immense. Not just satisfaction, but a deep, almost physical sense of achievement. A feeling that you had stretched your mind to its limits and won. This feeling was not unique to programming. It resembled what one experiences when solving a difficult problem in physics or thermodynamics: the slow accumulation of understanding, the tension of uncertainty, and finally, the release of clarity. It was, in many ways, the purest form of intellectual labor. And more importantly—it became part of our identity. We equated this struggle with intelligence. With worth. With pride. To endure comple...
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When Code Becomes Secondary and Logic Reigns

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Source  The history of programming is the history of translation. For over half a century, humans have been painstakingly converting ideas into languages that machines can execute. From the rigid world of assembly to the elegance of Python, every leap forward in programming has been about one thing: narrowing the gap between human thought and machine action . But the arrival of Large Language Models (LLMs) has brought us to a turning point. The value of an engineer will no longer be measured by how quickly they can write code, but by how precisely they can design logic. Large Language Models have shifted the center of gravity from syntax to reasoning, from typing instructions to architecting systems.  The future belongs to those who can think in pure structure and let AI handle the translation into machine language.  I didn’t arrive at this conclusion by reading headlines,  I arrived at it by building real AI systems, watching code become the least important part o...
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From France to the “MIT of Canada”: Why I Chose a 6-Month Research Internship at the University of Waterloo Over a Company Placement

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  Courtesy of the University of Waterloo. When most engineering students approach their final years of study, they often set their sights on internships in established companies, the kind that promise industry exposure, networking opportunities, and the comfort of a corporate structure. I chose a different path. Instead of joining a company, I packed my bags, flew across the Atlantic, and began a six-month research internship at the University of Waterloo,  often called the MIT of Canada . Why? The reasons were as personal as they were professional. Aligning Research With My Entrepreneurial Vision Before coming to Waterloo, I had already been working on entrepreneurial projects in France related to smart health and assistive living,  from fall detection systems for seniors to IoT-based health monitoring solutions. When I discovered the Ubiquitous Health Technology Lab (UbiLab) at Waterloo, I knew it was the perfect fit. The lab’s research on ambient sensor networks...
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Engineering Studies in Europe vs North America: What Every Student Should Know

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Photo by  ESCP When it comes to studying engineering, both Europe and North America offer incredible opportunities — but they do so in very different ways. I’ve had the chance to study engineering in France at the UTC_Sorbonne University , and soon I’ll be heading to the Georgia Institute of Technology in the U.S. for my Master’s in Computer Science with a specialization in Artificial Intelligence. Here’s what I’ve learned from navigating both worlds. Program Structure: Theory vs Application One of the first differences you’ll notice is how theoretical French engineering education can be, especially in the first years. At UTC, and in many French engineering schools, the first two years are a common core — no matter your specialization, you study advanced mathematics, physics, chemistry, mechanics, and even computer science. The idea is to form a “generalist” engineer before you dive deep into your field. And the mathematics? Let’s just say this: you don’t just use theorems — ...
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Designing AI That Matters: My Research Journey at the University of Waterloo

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  Source When people hear “Artificial Intelligence,” they often picture breakthrough algorithms or futuristic robots. In reality, designing AI that truly matters means building systems that solve real human problems,  and doing it with purpose, ethics, and context in mind. My six-month research internship at the University of Waterloo’s Ubiquitous Health Technology Lab (UbiLab) was a deep dive into that reality. It wasn’t about chasing the latest AI trend, it was about engineering intelligence that works in the real world , under real constraints, for people who actually need it. AI in Service of a Bigger Mission The project aimed to improve independent living for seniors and people with health challenges. We developed an ambient activity recognition and behavioral anomaly detection system that could operate without cameras or microphones : protecting privacy while still providing actionable insights. This required: IoT Sensor Integration: Zigbee-based motion, door, ...
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The Race to AGI: What Will Change, Who Will Win, and How We’ll Adapt

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OpenAI CEO Sam Altman In the world of Artificial Intelligence, few concepts spark as much debate, and imagination, as AGI and ASI . We’ve all been amazed by what AI tools like ChatGPT can do, but what’s coming next is far beyond clever chatbots. These terms don’t just represent technological milestones, they signal a shift that could redefine the balance of power, reshape economies, and challenge the way humans see themselves. I’ve been fortunate enough to work in AI research, and I’ve seen up close that the most important conversations aren’t about what AI can do today, but about what’s coming tomorrow,  and how we’re going to adapt. What Exactly Are AGI and ASI ? Let’s start with clear definitions: Artificial General Intelligence (AGI) is AI that can match human intelligence across virtually all tasks, learning, reasoning, adapting, and problem-solving, without being limited to a single domain. Artificial Superintelligence (ASI) goes even further: an intelligence tha...
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AGI’s Dark Side: How Superintelligence Could End Freedom as We Know It

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  (We’ll start with a fictional story, but one that could be reality sooner than we think.) The Story I was in Tel Aviv, finishing my last semester at university. It was a Thursday morning, and the beach was already full of surfers. I had my laptop open in a small café, pretending to study, but really I was scrolling through Instagram. That’s when I noticed something strange. My feed had shifted. Overnight, the lighthearted posts from my friends had been replaced with subtle political content, articles about “national unity,” AI-generated videos questioning the loyalty of pro-Palestinian activists, and even a suspicious “breaking news” clip claiming that a student at my university had been arrested for “collaborating with hostile organizations.” The name sounded familiar. Then I realized, it was my name. It wasn’t true, of course. But by the time I texted my friends to explain, some had already seen the video, believed it, and distanced themselves. I thought it was just a sm...
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