AI product copy you approve before it goes anywhere

Blank descriptions are one of the most common and most expensive gaps in a catalogue. A product page with nothing on it converts worse, ranks worse, and on some marketplaces is not eligible for listing at all. And the reason it is blank is never that the merchant did not care — it is that a thousand descriptions is a month of work with no single day where it is the most urgent thing.

This is precisely the shape of problem worth automating: high volume, low individual stakes, consistent structure.

Attributes in, prose out

Generation works from what you already hold — the product name, brand, category, specification, variant attributes. That matters, because a description invented from a name alone is a guess dressed up as a fact, and a confident wrong claim about a product is worse than no claim.

The output is a draft. It arrives against the product for you to accept, edit or reject, and it does not go anywhere until it has been accepted.

Why nothing is auto-published to a marketplace

Two reasons, and both are about the fact that marketplace APIs have no undo.

The first is that your existing listings are worth more than the copy on them. A listing that has sold for six years carries ranking and feedback attached to a title written specifically for how buyers on that marketplace search. Replacing it with something a model wrote this morning can cost real position, and it cannot be put back.

The second is that generated copy is occasionally, confidently wrong — about a material, a compatibility, a size. On your own storefront that is embarrassing. On a marketplace it is a policy problem.

So marketplaces stay on stock-only sync unless you deliberately hand Qwikr the content, and generated copy is a draft on your side of that line.

A consistent voice across a catalogue

The advantage a model has over a rushed human is not eloquence, it is consistency. Two thousand descriptions written by one person over a year are not in the same voice; two thousand generated against the same instructions are. That consistency is what makes a catalogue feel like a shop rather than a spreadsheet.

Where AI is not allowed near

Copy is a judgement call with a wide range of acceptable answers, which is exactly where a language model is useful. Several other jobs are not, and they are kept away from it deliberately:

• Stock levels. There is one right answer and it comes from a sale, not an inference.
• Prices. Repricing is arithmetic against a floor you set, not a judgement.
• Compliance checks. Whether an image meets Amazon’s rules is measurable. A plausible-sounding “looks fine” is worse than no answer.

The rule underneath is simple: a model may draft, and it may propose. Anything irreversible waits for a person.