Judge the Work, Not the Tool

An em-dash is not evidence, and "slop" is a verdict, not a category.

When I published Code is Design, I posted a short announcement on Hacker News. It drew very few comments. One of them was about the blurb. I had used an em-dash, and the commenter said something like: the em-dash shows it was “obviously” written by AI.

That was the whole review. Nothing about the argument, the structure or whether the book had anything to say. An em-dash was found, a verdict was reached, and the label went on: AI slop.

I didn’t care then, and I don’t care now, whether people think the book was written by a human or by a machine. What annoyed me was that the work wasn’t judged on its merits. It wasn’t judged at all.

It’s happening to better writers than me

The winner of this year’s Commonwealth Short Story Prize was accused of using AI, with AI-detection tools used to make the case, even though the prize’s own investigation found the work was human-authored.^[1] One of the judges, Louise Doughty, warns against “frivolous or malicious accusations of AI being used to derail a writer’s career”, and notes that the accusation “will always be easier to level at new authors”.^[1]

The same article lists the “tells” readers are supposed to watch for. They include “’It’s not X, it’s Y’ constructions” and “Always giving three examples”.^[1] I read that list with some amusement. I use em- and en-dashes as a matter of course. I like contrasting constructions: it might be this, but it might also be that. And I will happily give you three examples to make a point, because two often isn’t enough and four is showing off. By that checklist, half of what I’ve written over forty years would be flagged.

Closer to home, Substack itself has added an AI detector, from a company called Pangram. Lisa Kostova has gathered what writers on the platform think of it, and one line she quotes, from Dr Sam Illingworth, puts the problem exactly: “the person under suspicion is left proving a negative to a room already leaning towards the machine.”^[2]

Real slop exists. That’s not the point

Let me be clear about what I’m not defending. There is genuine slop: mass-produced, careless, padded content that nobody stands behind. The ABC describes online sellers “flooded with AI ‘slop’ books”.^[1] I won’t read that, and nobody should have to.

But humans are perfectly capable of producing slop all by themselves, and always have been. I’ve read plenty of it: unclear, rambling, full of errors, or simply not enjoyable. When I hit something like that, I put it aside. Whether it was written by a person, a machine or some cooperation between them has nothing to do with how I judge it.

The word was useful when it meant low effort and no care. It has drifted into meaning a machine was involved, and that is a different claim altogether.

How the label drifted

In October, the r/opensource community on Reddit banned every project that “uses AI, is made by AI, or is intended for AI”, regardless of quality.^[3] To his credit, the moderator who announced it admitted, “There’s no ‘objective’ way to implement this policy.” The same rules shut out people who write in a second language, because the moderators “cannot distinguish AI-written content from AI-translated text”.^[3]

Martin Fowler, someone I’ve read and respected for years, wrote a thoughtful piece about what he calls “LLM voice”. When he senses it, he says, “my desire to read on atrophies, sometimes to the point of revulsion”.^[4] He’s honest that this is a reaction rather than a test, and he adds: “I’m also suspicious of my own ability to accurately recognize LLM voice.”^[4] I appreciate the honesty. But a reaction to the surface of the prose is not a judgement of the work.

Who pays for it

A label that judges the tool instead of the work lands hardest on the people who can least afford it:

• New writers, as Doughty says, because they have no reputation to fall back on.

• People for whom the tool is access. Fowler’s own examples include a colleague, Jim Highsmith, who finds an LLM essential “to overcome the bane of Parkinson’s disease”, and colleagues for whom English is a second or fourth language.^[4]

• People who put in the real work and then find nobody will look at it. Simon Willison, writing about games built with AI, expects that “some players will refuse to have anything to do with games that were built in this way”.^[5]

We’ve been here before, sort of

Early in my career, the snobbery ran along language lines. If you wrote in BASIC, whether the interpreted BASIC on the pre-IBM home computers or later Visual Basic, or in COBOL, your work was somehow unimportant or bad. Real programmers wrote in C. 4GLs and code generators got some of the same treatment.

The intensity was never what it is now. But the shape was the same: judge the work by the tool that produced it, and you can skip the harder job of reading it.

How I actually work

So let me be open about my own process.

I have AI agents scouring the internet for ideas related to my interests and background. I use AI to propose outlines and structures, and sometimes to generate an initial draft. When I wrote Code is Design, I developed it by iterating on the central message, asking for research and advice about sequencing and emphasis. Now and then, when I was struggling to find the right words, I explored a passage with various AI tools. Occasionally I used one of the suggestions verbatim, because it sounded like me and I couldn’t improve on it.

But the articles are mine, and so are the books. They exist because of me. They carry my message and my thoughts. I generate the idea, I guide the message, I write the material or edit a generated draft, and I decide what is written about and what gets published.

The fact that AI is used as a tool tells you nothing about whether the work is any good.

There’s a separate complaint, that AI is built on other people’s work without permission. I’ve written about that in a previous article “AI, Copyright, and the Scale Problem” and it deserves its own answer. It isn’t what ‘slop’ means.

What should replace the label?

I’m not convinced anything should. We don’t label an essay “created with Microsoft Word”, or an image “edited in Photoshop, not drawn by hand”. Nobody asks an engineer whether they used a CAD package. Nobody asks a novelist whether they used a thesaurus.

There’s perhaps one logical argument for labelling: keeping AI-generated material out of the data used to train future AI. Even that is shaky. Good material, produced by people with the help of AI, is perfectly valid training material. Slop, whoever or whatever produced it, needs filtering out either way.

There is a better model, and it already exists. As The Register reports, the Linux kernel’s approach is to hold developers responsible for the code they submit, whatever tools they used.^[3] That puts accountability on a person, not suspicion on a tool. It’s also the principle I spent a career arguing for in software: tools change, and responsibility for the design doesn’t.

A letter to the Guardian in October made a similar point about the PHP vulnerabilities I wrote about in “Free to Use, Not Free to Keep”. The writer said the flaws “were found because an AI tool was used to check the PHP source code, which is a good use of AI”, and that the real failure was a human leaking the details before they were fixed.^[6] I’d put it more simply: judge what was done, and who stands behind it.

A verdict, not a category

So here’s what I’d ask. Read the thing first. If it’s unclear, padded, careless or wrong, call it slop, and you’ll get no argument from me. That’s a verdict, and you’ve earned the right to it by reading.

But an em-dash is not evidence. Three examples are not a confession. And “obviously AI” is not a review.

Also on the blog since last week’s issue:

Nowhere to Scribble in the Margin Forty years ago a statistician told me the problem with a computer screen is that you can’t scribble a note in the margin. The algorithm that now decides home support for older Australians has the same flaw, and it has nothing to do with AI.

Leaving Some Room Pema Chödrön’s advice for when the ground gives way is to stay with the uncertainty rather than rush to a plan. It’s also the hardest discipline in a requirements workshop, where everyone hurries towards a signed-off specification that only looks like certainty.

The Report That Couldn’t Add A $166,000 report on merging three Western Australian universities turned out to have sums that don’t add up, one of them $260 million out. A computer-produced number is only as good as whoever checked it.

Zero Points, and Still Cut Off A man with no mutual obligations was cut off Centrelink payments and spent more than three years without income support. $53,000 in back pay doesn’t give those years back, and it’s what happens when nobody is allowed to scribble in the margin.

The Slap on the Back of the Head Dostoyevsky faced a firing squad and was pardoned at the last moment. My own wake-up call came more quietly in 2013, and it took Maria and me five years to act on it.

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^[1] Aoife Hilton, “How Australian publishers tell if a book has been written by AI”, ABC, 28 October 2026.

^[2] Lisa Kostova, “What 19 Substack Authors Think of AI Detection - Guide (Part 2 of 2)”, 18 October 2026.

^[3] The Register, “Reddit’s r/opensource bans AI slop, and quite a few humans for good measure”, 26 October 2026.

^[4] Martin Fowler, “LLM Voice”, 29 October 2026.

^[5] Simon Willison, “The October inflection point for vibe game development”, 28 October 2026.

^[6] David Gibson, letter, “Credit where it’s due to AI for uncovering the PHP flaw – and discredit to the leaker”, the Guardian, 30 October 2026.