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The Strange Loops of Generative AI

They (AI) weren’t trained to find truth; they were trained to continue a pattern. It’s like giving someone half a crossword puzzle and asking them to finish it—not by solving it, but by guessing what kind of answers usually go there.

There’s something inherently human about wanting to make things that make things.

It’s why we build factories, write programs, or start companies. But when the things we build start writing poems, painting pictures, and generating music—well, that’s when it gets interesting. That’s generative AI.

Most people, when they hear “AI,” still picture something out of science fiction: a robot with glowing eyes or maybe the calm voice of a spaceship computer. But AI in the real world doesn’t look like that. It looks more like autocomplete on steroids. It writes essays, draws pictures, composes

AI’s Warped Mirror - Revealing More About Us Than Itself

AI doesn't create new ideas but mirrors human knowledge—revealing not just intelligence, but also biases and assumptions, making it both insightful and unsettling.

I was thinking about whether AI really creates anything new, or does it just reflect what we already know. Or, more accurately, what we think we know. It’s like a mirror, but not a perfect one. More like one of those antique mirrors that’s slightly warped, showing a version of reality that’s close enough to feel real but distorted enough to reveal things we might not have noticed before.

That’s what makes AI so fascinating—and unsettling. It doesn’t just reflect our intelligence; it reflects our assumptions, our biases, our fears. The way an AI

The Race to the Bottom in AI - OpenAI Still Leads, But at What Cost?

Despite fierce competition and plummeting AI costs, OpenAI’s GPT-4o remains the best overall model, but its dominance is threatened as cheaper, near-equivalent alternatives erode its pricing power.

For the last few years, the AI space has been defined by a single truth: OpenAI was ahead. Far ahead. They had the best models, the biggest breakthroughs, and a pricing structure that reflected their dominance. And despite all the advancements in open-source AI and competing models, that still hasn’t changed. GPT-4o remains the best overall model in terms of quality, reasoning ability, and flexibility.

But something else has changed: the cost dynamics of AI are shifting rapidly, and OpenAI is no longer operating in a world where they can price however they want. The industry isn’t just

When IT Is No Longer IT - Why AI Might Need Its Own Team

As AI reshapes how businesses operate, should it have its own dedicated team instead of being another task on IT’s plate?

Once upon a time, IT had a clear purpose. It was the department that kept the servers running, fixed your email when it broke, and made sure you had access to the company database. IT was about infrastructure—routers, firewalls, and enterprise software. If it had a power button and it lived in the office, it belonged to IT.

But something strange has happened over the last few decades. IT has absorbed more and more responsibilities, to the point where it’s not entirely clear what IT is anymore. First, they inherited software licensing. Then they took ownership of SaaS

The New York Times Embraces AI, Efficiency Boost or Threat to Journalism?

In 1994, The New York Times published an article questioning whether the internet would be good for journalism. Thirty years later, it’s making a similar calculation about AI. The news that The Times is officially embracing AI tools for its product and editorial teams is less of a surprise and more of a confirmation: resistance is futile.

But this isn’t just another industry adapting to technology. It’s a case study in how legacy institutions, especially those built on human judgment and credibility - navigate the tension between efficiency and authenticity.

AI is inevitable. The real question is

The New Bottleneck - Why Judgment Matters More Than Intelligence in the Age of AI

AI has commoditized intelligence, the new differentiator is human judgment—the ability to ask the right questions and make meaningful decisions.

For most of history, intelligence was a scarce resource. If you could think faster, remember more, and solve complex problems better than others, you had an edge. Schools and careers were built around this advantage. But that world is gone.

Now, with advanced AI, especially large language models (LLMs), has changed the equation. Intelligence, at least in the traditional sense, is no longer the bottleneck.

We now have AI systems that can process information faster than any human, write better than most professionals, and pass graduate-level exams in multiple disciplines.

The result? The value of raw intelligence has plummeted. The

The Strange Loops of Generative AI

AI’s Warped Mirror - Revealing More About Us Than Itself

The Race to the Bottom in AI - OpenAI Still Leads, But at What Cost?

When IT Is No Longer IT - Why AI Might Need Its Own Team

The New York Times Embraces AI, Efficiency Boost or Threat to Journalism?

The New Bottleneck - Why Judgment Matters More Than Intelligence in the Age of AI

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