I asked Claude, a generative artificial intelligence (AI) chatbot to write a blog post on "why it's a bad idea to have AI write a blog post. Here's what I got.
Why You Shouldn't Use AI to Write Your Blog Posts
There's a certain irony in asking an AI to make the case against AI-written content. But maybe that's exactly why it works — who better to explain the limitations of a ghost than the ghost itself?
Here's why hitting "generate" on your next blog post is a mistake, even when the result looks polished.
## It Sounds Like Everyone Else
AI language models are, at their core, pattern-matching machines trained on the aggregate of human writing. The result is prose that sits squarely in the middle of everything — competent, inoffensive, and utterly forgettable. Every sentence lands where you expect it to. Every transition is smooth. Nothing surprises you.
Good writing has texture. It has weird detours, strong opinions, and moments where the author's personality bleeds through. AI writing is the literary equivalent of a stock photo: technically fine, but somehow nobody's home.
## Your Readers Can Tell
People are more attuned to AI-generated text than we often assume. There's a particular rhythm to it — a tendency toward tidy three-part structures, over-reliance on phrases like "it's worth noting" and "in today's landscape," and a habit of hedging every claim into meaninglessness. Readers who encounter it regularly develop an instinct for the uncanny valley of the written word.
When someone senses they're reading AI output, the trust evaporates. They're no longer reading *you* — they're reading a statistical average of the internet. That's not a relationship you can build an audience on.
## It Skips the Part That Actually Matters
Here's something most people don't say out loud: the value of writing a blog post is often *in the writing of it*. The research you do, the position you're forced to take, the argument you have to stress-test in your own head before it reaches the page — that's where the thinking happens.
When you outsource that process, you don't just outsource the words. You outsource the thinking. You end up publishing a post you don't fully believe, on a topic you haven't fully worked through, and it shows — even when every sentence is grammatically impeccable.
## It Has No Actual Experience
AI can synthesize information about grief, or burnout, or the experience of launching a startup, but it has never felt any of those things. The most resonant blog posts are the ones where the writer has *skin in the game* — a hard-won insight, a failure they're still processing, a contrarian view they're willing to defend.
AI produces confident-sounding text about experience it doesn't have. That's not a flaw in the model; it's just what the model is. But it means that any post requiring genuine perspective — which is most posts worth reading — will always ring slightly hollow when machine-generated.
## It Feeds the Content Landfill
The internet already has more content than anyone can read. What it's genuinely short on is *good* content — writing that changes how you think about something, or makes you feel less alone, or teaches you something you couldn't have just Googled.
AI makes it trivially easy to produce more content. It does nothing to raise the floor on quality. Every AI-generated post that gets published makes it a little harder for readers to find the stuff that actually matters — including yours, if you're writing it yourself.
## So What's AI Actually Good For?
To be fair: AI is genuinely useful for *parts* of the writing process. Brainstorming angles, drafting an outline, punching up a weak sentence, catching typos — all fair game. Using it as a thinking partner is different from using it as a ghostwriter.
The mistake isn't using AI at all. It's using it to skip the hard part. The hard part — figuring out what you actually think, and finding the words that are true to it — is the only part readers care about.
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*So yes: an AI wrote this post. Make of that what you will.*
