How Much of my Writing is AI-Generated?
Writing is learning. LLMs remove that component.
In early 2026 a barrier was crossed: the majority of LinkedIn posts were now AI-generated. 53.7% to be specific. Other feeds like X or Reddit are unlikely to fare any better.
And now you’re reading this article. So a fair question is: is there a real person with their own experience and views behind it? Assuming the answer is “yes”, why would that matter?
What follows is my list of ingredients for Code for Humans and Machines. It explains how I work with AI as well as the consequences of outsourcing writing to it. Ultimately, it ties into the purpose of writing, which should go deeper than content production.
Does it matter if content is AI-generated?
Yes.
AI-written content has a peculiar flavour. LLMs employ several advanced stylistic devices. These give AI content its tell-tale signs, serving as mental cues to immediately scroll past. It’s not about quality per se. More like: If it was effortless to produce, it simply carries less value.
That reaction is not just me. Research shows that we rate identical works as more valuable when we think a human, rather than an AI, created them: Humans versus AI: whether and why we prefer human-created compared to AI-created artwork.
Feelings aside, my main problem with AI-generated content is that it is so bland. Yes, individual sentences can be expressive, even snappy. But the overall effect is repetition, verbosity, and a lack of sharpness. Impressive in the small, exhausting at length.
Losing the benefits
Consuming LLM content is one thing. It poses an even larger challenge for the writer.
For decades, I’ve used writing to explore and understand various topics. Writing is an active process, and the very act of expressing an idea in text is itself a valuable way to learn.
I often start writing about topics I’d like to think I already master. Still, I frequently discover a gap in my understanding or an edge case I hadn’t considered. Writing is learning. LLMs take away that component.
That, too, is backed by research: writing is not just a way to report thought, but a way to develop it.
How much AI do I use?
There’s a crucial difference here: I do use AI a lot, but not to generate articles.
Iterating on sample code
Most of my articles contain code samples. Historically, those samples have been time-consuming. Not only do I have to find relevant examples; the code also needs to exhibit a specific design problem. Coming up with artificial code examples is hard enough. Coming up with examples that are “bad” in a specific way is next-level hard.
AI largely automates that process. I can iterate on sample code, instruct the agent to make it more or less complex, and even ask it to amplify some code smell for illustrative purposes. I love that.
Research assistance
I’ve always made it a point to base my recommendations on research. The real, peer-reviewed kind.
In the past, a lot of that work was repetitive searches on Google Scholar and university databases, trying to identify relevant papers. After skimming too many not-quite-what-I-need papers, reviewer fatigue would kick in.
An agent is, of course, a superb support for these types of tasks. I use AI a lot to narrow down my search. I probably spend the same amount of time in total, but now the bulk of that time is spent reading and understanding relevant material.
Review and feedback loop
This is where AI shines. It’s good at identifying inconsistencies, and offers a rapid feedback loop.
90% of my writing is rewriting. The first draft is usually quick, but I do multiple iterations where I tweak, clarify, and try to improve the flow and structure. Continuous feedback is useful.
Unblocking writer’s block
I have a tendency to get stuck on certain parts of a text. I know what my message should be, but I cannot get into the proper writing flow. Here, AI is wonderful: I type down a stream of consciousness and ask the AI to refine it.
Ultimately, I tend to throw most of that generated text away. Occasionally, I keep parts that I tweak. But getting a starting point — even if imperfect — helps more often than not.
Indirect influence
AI impacts my work in other ways, too. I mentioned earlier how LLMs mimic advanced stylistic writing patterns. Think of lines like “It’s not only an X. It’s a Y,” or the classic em dash.
I actively minimize my use of these tricks. The LLM tendency to overuse the em dash in particular is a tragedy — I employed it heavily in my pre-GenAI writing.
Why I write
Writing with AI support is a more enjoyable process. However, writing that is meant to be read is still 95% human effort. Any attempt to short-circuit that process comes with a cost: bland text and a lost learning opportunity. It’s self-defeating.
At the end of the day, the personal question each writer has to ask is:
Why do I write?