Unmetered Software · Media version
What happens when readers bring their own AI to your journalism
Every publication has a comment section, or has killed one. Both are admissions of the same thing: the readers with the most to say are rarely the ones you want to hear from, moderating it costs real money, and the good arguments — the ones from people who actually read the piece — mostly never get made at all.
Here is the part that should change how you think about it. The argument is happening anyway. It is happening in group chats, in screenshots, and increasingly in a chatbot somebody pasted your headline into with none of your context, none of your sourcing, and none of your caveats. You are not hosting that conversation. You are also not in it.
So frame the prompt yourself. Ship each piece with a handoff that carries what the story actually claims, what it does not, and where the documents are. A reader takes that to whatever AI they already use, and your framing goes with them. It costs nothing to run, because you are not the one paying for the model.
What comes back is an artifact rather than a comment — a considered take, a thread, a counter-argument the reader built by working through the material. That is a better thing to be shared than a link somebody posted without finishing, and it carries your reporting inside it rather than pointing at it.
We will do it live on a real published piece: hand the room the prompt, and read back what different readers' AIs make of the same article — including where they push back, and including a reader checking a claim against the public record themselves. Editors leave with a clearer view of which reader interactions are worth hosting and which are better handed off, what it means that the argument about your work is already happening somewhere you cannot see, and why framing the prompt is the only lever you have over it.
Tell me the date and who is in the room, and I will tell you whether it fits. I adapt it to the audience — see below.
Useful in a first email: the date, the city, roughly how many people, and what they do all day.
The technical version — how the handoff actually works, and why the return leg costs nothing at any scale.
Monthly notes on AI-assisted development — what I'm shipping, what I'm learning, and which tools actually earn their place. It's also where the next talk and the next office hours get announced.
Talks · Reports · Survey of Software · ivantohelpyou.com
Model Citizen Developer · Ivan Schneider · [email protected]