Why Writers Will Survive AI

The best writing isn't just producing words. It depends on judgment, context, and the implicit knowledge AI struggles to replicate.

Photo by Florian Klauer on Unsplash

Some people expect AI to eliminate writers. After all, if AI can generate great text, why would we need humans putting words on pages?

This misunderstands what writing actually is and how people consume it.

How People Actually Read

To see why AI won’t simply replace writers, start with how people actually discover what to read.

Yes, AI will change how we browse the internet. AI might become many people’s interface with the web. There will be less Googling for articles, less stumbling onto whatever writer the algorithm serves up.

But that’s not how most reading happens anyway. Most reading is curation by people you trust.

I didn’t Google to find the Abundance book, progress studies, nor my favorite writing book. These were flagged to me by writers I trust. I followed their judgment.

This pattern has been stable throughout internet history: Patreon, Substack, traditional subscriptions. People follow and pay for writing because they want to support specific institutions, angles, or voices they trust and want to amplify. Today’s information landscape depends on these structures.

And they’re proving more resilient than expected. Many predicted AI-generated deepfakes would destroy our ability to trust media, that we wouldn’t be able to tell real from fake, that information ecosystems would collapse. That didn’t happen. Rather than drowning in billions of deepfakes and AI slop articles, people still get their news from institutions and voices they’ve followed over time. Trust structures held.

Even Substack writers, who lack an institutional home, build audiences the same way: one piece at a time, earning trust through consistent judgment about what matters.

This trust is what AI needs to displace, not just text generation capability.

What Makes Writing Stick

The writing that builds trust is, at its core, about connection.

Writers write about what lights them up. Writers build audiences made up of people who light up from the same things. And, often, the writing resonates because readers share some of the writer’s “implicit knowledge” about what matters.

Implicit knowledge is information you possess but can’t easily explain, often learned from experience or social interactions. A developer knows which architectural decisions will cause problems six months later. A longtime transit advocate will know what energizes her local allies the most. It’s accumulated pattern recognition from thousands of experiences.

AI struggles with implicit knowledge. Anthropic points to this as a primary bottleneck to AI utility and adoption. This knowledge lives “in the minds of account executives, marketers, and external contacts” and can’t be easily transferred into databases to train or inform AI.

But implicit knowledge isn’t just a business problem. It’s how audiences form. Consider Matt Yglesias, the center-left political writer. His readers don’t just agree with his positions. They sense something beneath the arguments, a worldview or set of instincts they share but couldn’t quite name until they found his work. I recognize my own unspoken thinking in his words.

This is what makes writing powerful: it transforms the implicit into the explicit.

“The Housing Theory of Everything,” published in Works in Progress, did this for me too. The article synthesized ideas about zoning into one argument that reorganized how I understood the world. I needed a day just to process it. The authors took knowledge that existed nowhere else in that form—part explicit research, part implicit intuition about how systems connect—and made it legible.

This is also how trust gets built. Ezra Klein and Derek Thompson spent years conducting interviews, writing essays, following their curiosity across topics. By the time they published Abundance, readers had watched them think in public long enough to know: these writers share my implicit intuitions about how the world works.

That accumulated trust is what lets them challenge prevailing opinions and actually be heard.

Why AI Doesn’t Clearly Replace the Writer’s Role

Even in a world where AI solves many problems, we’ll still have genuine disagreements. People will likely still disagree about whether abortion is murder, which drugs should be legal, and whether San Francisco should have skyscrapers. They’re contests between worldviews.

Someone still has to decide which worldview to advance. AI doesn’t wake up thinking “here’s why everything bagel liberalism is the problem.” It has no skin in the game, no convictions about what message matters.

But choosing the message isn’t enough. For writing to shift how people think, rather than just collect engagement, you need the kind of work that uncovers neglected topics, explains complex issues clearly enough to change minds, earns trust through balance and rigor. Alarmism gets clicks. Persuasion requires something harder.

This difficulty explains why great writers increasingly resemble senior software engineers, who became more valuable as AI learned to write code.

AI handles the routine, repetitive code. Senior engineers provide what AI can’t: knowing which approach actually fits the problem, understanding unwritten context from years of experience, making judgment calls.

The parallel holds for writing. AI generates clean text on any topic. But the writing that shifts worldviews depends on judgment, context, implicit knowledge, the skills AI struggles with most.

Writing will still be a tough market. But I expect writers will still get cited, still get subscribed to, still change minds. The skills that make writing powerful are precisely the ones AI isn’t replicating.

What I’m Very Uncertain About

Maybe AI solves implicit knowledge transfer soon. Maybe it learns to recognize which new ideas deserve synthesis. Maybe smart glasses capturing everything we see and say provide enough context to close the gap.

I don’t think it’s impossible. But these capabilities might prove much harder than language generation did.

AI excels at tasks with clear evaluation metrics: solve this equation, debug this code, summarize this document. Clear metrics are critical for training AI.

The skills writers rely on don’t have clear metrics. Knowing which implicit knowledge to surface and which topics will shift how people think are harder to grade quickly or objectively. Engagement metrics exist, but optimizing mostly for likes and comments rewards outrage over the harder work of informing and persuading.

The writing that changes worldviews requires something harder to measure. And thus harder to train AI on.

I don’t know what being a writer will mean in ten or twenty years. But the evidence isn’t there yet to assume the worst, that writers will be obsolete¹.

1. My essay applies to nonfiction research writers. I’m uncertain about how AI impacts fiction writers.