The difference between a template and a generated message is not language quality. A template says the same thing to everyone; a model can say different things — if it has something to work from.
What it works from
Whatever is known about the person: which chat they came from, what they wrote there, what their profile says. The thinner that is, the closer the result to an ordinary template — and the less point there is in generating.
Hence: AI personalisation pays off on a narrow, well-built list and gives almost nothing on a bulk export.
What not to expect
- That it will invent a reason. With no reason available, a model will make one up, and it shows.
- That it replaces relevance. A well-written message to the wrong person is still a message to the wrong person.
- That it is undetectable. In short business messages the difference is usually invisible, but models tend towards a smoothness people do not have.
What to check
The first fifty messages, by eye. A model can invent a fact about the person, get their gender wrong, use the wrong name. That message is worse than a template: a template is merely impersonal, this one contains something untrue.
On the limits of trust — what not to trust a model with.
What to put in the instruction
Tight boundaries: length, tone, what may not be promised. «Write a persuasive sales message» produces exactly what everyone recognises in the first line.
How Neurogram does this
Everything above is manual work that runs into the number of hours in a day. Neurogram does it on your own accounts and without you: it collects channels and audiences, writes comments and replies with a language model, and keeps limits and quiet hours so the accounts survive. See pricing or look at your case.