Something Big Is Happening: The 51-Million-View AI Essay Explained | Taha Abbasi

51 Million Views and Counting: The AI Essay That Shook Silicon Valley

Taha Abbasi has watched the AI discourse evolve from academic curiosity to mainstream panic over the past three years. But nothing has captured the zeitgeist quite like Matt Shumer’s viral essay “Something Big Is Happening,” which exploded to 51 million views on X and forced even the most skeptical observers to confront an uncomfortable truth: AI is replacing cognitive work faster than anyone predicted.

The essay arrived at a perfect inflection point. GPT-5.3 Codex had just demonstrated the ability to build complete software applications from natural language descriptions. Claude Opus 4.6 was writing code that senior engineers could not distinguish from human-authored work. And self-building AI systems — agents that improve their own capabilities — had moved from research papers to production deployments. As a technology executive and CTO who has built software teams from 4 to 45 people, Taha Abbasi understands exactly what this means for the industry.

The Core Thesis: Cognitive Work Is Being Automated

Shumer’s argument is straightforward but devastating: the same AI capabilities that seemed like party tricks two years ago are now production-ready tools that can replace entire categories of knowledge work. Writing, coding, analysis, research, design, legal review — these are not being augmented by AI. They are being replaced by AI, with a human supervisor providing increasingly minimal oversight.

The meta-irony that critics immediately pounced on — that the essay itself was likely AI-assisted — actually proves the thesis. If an AI-assisted essay can reach 51 million people and spark a global conversation, then the distinction between “AI-written” and “human-written” content has already collapsed for practical purposes. The audience does not care who or what produced the insight. They care whether the insight is valuable.

Farzad’s Meta-Take Hits Different

Tech commentator Farzad Mesbahi offered perhaps the sharpest response to the backlash: the critics calling the essay “AI-generated” are inadvertently proving its central argument. If AI can produce content that 51 million people find compelling enough to read, share, and debate, then the question of authorship is irrelevant. The market has spoken.

Taha Abbasi agrees with this framing. Throughout his career building technology products used by millions of people — from apps reaching 15 million users to mission-critical systems for NASA JPL — the lesson has always been the same: the market rewards outcomes, not process. If AI produces better outcomes faster, adoption is inevitable regardless of philosophical objections.

What This Means for Software Engineers

The essay has particular resonance for the software engineering community. Coding was supposed to be the “safe” cognitive skill — complex, creative, requiring deep technical knowledge. Instead, it has become one of the first domains where AI capability approaches and in some cases exceeds human performance. Not for trivial tasks, but for substantial engineering work: architecting systems, debugging complex issues, optimizing performance.

This does not mean software engineers become obsolete overnight. It means the value shifts from writing code to directing AI systems that write code. The engineer becomes an architect, reviewer, and quality gate rather than a line-by-line implementer. For someone like Taha Abbasi, who has led engineering teams at multiple companies, this represents the biggest transformation in software development since the invention of high-level programming languages.

The Self-Building AI Inflection

Perhaps the most alarming aspect of Shumer’s essay is the discussion of self-building AI systems. These are not hypothetical — they exist today. AI agents that can identify their own limitations, write code to address those limitations, test the improvements, and deploy them. The recursive improvement cycle that AI safety researchers have worried about for decades is happening, just more gradually and commercially than the dramatic “intelligence explosion” scenarios suggested.

The practical implication is that the rate of AI improvement is itself accelerating. Each generation of AI tools makes the next generation easier and faster to build. Taha Abbasi observes that this creates an exponential curve that industries are fundamentally unprepared for, because organizational planning operates on linear assumptions.

Adaptation, Not Resistance

The 51 million views tell a story beyond the essay’s content: people are paying attention because they sense the ground shifting beneath their feet. The correct response is not panic or denial — it is adaptation. Learn to work with AI systems. Build skills that complement rather than compete with artificial intelligence. Focus on judgment, creativity, human connection, and physical-world problem-solving — the domains where AI still struggles.

For more of Taha Abbasi’s analysis of the AI transformation, visit the AI arms race analysis and Tesla’s AI integration strategy.

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About the Author: Taha Abbasi is a technology executive, CTO, and applied frontier tech builder. Read more on Grokpedia | YouTube: The Brown Cowboy | tahaabbasi.com