A new feature called the "discuss skill" is shipping in the world of AI-assisted workflows, and its premise is blunt: you are bad at explaining what you know. On an episode of Unsupervised Learning, host Daniel Miessler described it as a fix for what he calls writer's blindness or expert blindness — the gap between what you actually know about a subject and what you manage to put into words when you sit down to write instructions.

"Another way to think about this, it's called writer's block or writer's blindness or expert blindness where you try to explain something, you try to write a book or something and it's just a garbage book because you haven't explained actually the stuff that you know, right?"

The problem is real and recognisable. When you give an AI assistant a task, the quality of what comes back depends on the quality of what you put in. If your prompt leaves out the details you carry around in your head — the standards you expect, the edge cases you know about, the shape of a good answer — the assistant has no way to fill them in for you. Experts are often the worst at this, precisely because their knowledge is so automatic they forget it needs to be said.

The discuss skill works by flipping the process. Instead of demanding a perfect written specification up front, it notices when your instructions are thin and starts asking questions. The conversation runs back and forth, and the answers get folded into what Miessler calls an Ideal State Artifact — a running document that captures what "done well" actually looks like for your task.

"Well, the ideal state document and the discuss skill is designed to fill that in. Right? And it actually triggers now at this point if you don't have enough detail it actually triggers discuss and has a conversation with you back and forth which then fills in the ISA more and more."

The honest caveat for non-developer readers: this lives in developer tooling. The Ideal State Artifact and the discuss skill are part of a workflow for building things with AI coding assistants — the "requirements" being extracted are specifications for software, not a shopping list or a wedding plan. If you don't work with code, this particular tool isn't aimed at you.

That said, the idea behind it travels well. Most AI assistants you can talk to today will already answer clarifying questions if you ask them to — before you start, ask me whatever you need to know to do this well is a prompt anyone can use. What's different here is that the trigger is automatic: the system detects a thin specification and starts the interview itself, then writes the results down somewhere persistent instead of letting them evaporate when the session ends.

Is it usable? According to Miessler, it is shipping — this is a feature that exists, not a proposal. What is not public is how well the automatic trigger works in practice: how it judges "not enough detail," how annoying the interrogation becomes on simple tasks, and whether the accumulated Ideal State Artifact actually improves output or just grows longer. Miessler doesn't address those limits.

Who it's for: people whose prompts keep failing because they leave things out, and who would rather be interviewed than write a brief. If that sounds like you, the mechanism is the point — get the knowledge out of your head and into writing before the assistant guesses.