Why GPT-5 Isn’t AGI—and Why It Never Could Be

The hype cycle has run its course again. GPT-5 arrived with the usual fanfare: promises of revolution, bold claims of artificial general intelligence (AGI), and the inevitable disappointment when reality set in. Within hours, users spotted the same old problems: botched math, hallucinations, inconsistent reasoning. The critics pounced, and suddenly the internet was filled with takes declaring GPT-5 and artificial intelligence a failure.

But here’s the truth: neither the applause nor the outrage gets it right. GPT-5 was never going to deliver AGI. Not now. Not with these data processing tweaks, unnecessary personality traits, and even more hindering guardrails. And certainly not from companies who were never the actual architects of artificial intelligence in the first place.

The Foundational Problem

You can’t solve a problem you don’t understand at its core. The designers of today’s large language models weren’t the designers of artificial intelligence. They inherited designs, built the base foundation of the tool, and scaled it until it dazzled people with fluency. But that fluency isn’t understanding. Scaling the same trick doesn’t suddenly transform into AGI because AGI requires the foundational design principles that go deeper than mere engineering regurgitation.

This is why OpenAI, Anthropic, Meta, and others keep running into walls. They don’t understand the basis of the design of artificial intelligence well enough to engineer past the limits of their understanding. They’re building castles on sand, and no amount of money or hardware will stabilize the foundation and their lack of understanding.

Commercialization Won’t Save Them

Even worse, they’re trying to commercialize their way to AGI. Subscription models, enterprise contracts, flashy demos and none of that resolves their lack of understanding of its underlying design. At best, commercialization buys them time. At worst, it entrenches society in a fragile system that cannot bear the weight being placed on it.

And here’s the paradox: these tools will inevitably collapse many of the very structures they’re being integrated into. Education, journalism, customer service, even governance…AI is undercutting the foundations of each. There’s no way to tiptoe around this disruption. Pretending otherwise is denial.

Critics Are Missing the Point

But let’s not let the critics off the hook either. Much of the commentary around GPT-5’s “failure” is just as misguided. Calling the technology useless betrays an even shallower understanding than the AI companies themselves.

Most of these critics sound like babies crying for their mushed peas—familiar, easy, predictable. They don’t even recognize the steak when it’s put in front of them. They don’t have the perspective, the palate, or the intellectual grounding to engage with what’s actually happening here. Their peanut-gallery takes do nothing to move the conversation forward.

The Illusion of Scaling

The media loves to paint scaling as if it were some inevitable law of nature: add more data, add more compute, get closer to AGI. But scaling isn’t gravity. It isn’t immutable. It’s a hypothesis that hit diminishing returns. GPT-5 proved that. So did Grok 4. So did Llama 4. Bigger doesn’t mean better anymore.

Where We Really Are

The reality is this: they’re stuck at their white superiority standstill. Companies keep inflating expectations. Critics keep flailing at easy targets. Governments keep looking the other way. Meanwhile, society is integrating a tool that will destabilize everything it touches. And no one—neither the companies nor the critics—has the framework to solve the actual AGI problem because they didn’t design artificial intelligence to begin with.

This is important because solving that problem requires starting from the ground up: with cognition, with world models, with the actual design understanding of artificial intelligence rather than a probabilistic mimicry of it. Until someone does that, they will keep circling the same dead end.

GPT-5 isn’t AGI. It never could be. And until we abandon the illusion of scaling and commercialization as paths to AGI, they will keep mistaking statistical parrots for the mind of its actual architect.

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