I recently saw a product story that felt precise and meticulous — like the work it described. It got me thinking about how we're telling stories for the AI products we're building.
When you claim your AI tool saves time, does your description of it actually save the reader's time? When you say it thinks for you, does your pitch think for the person reading it?
I catch myself writing bloated launch posts sometimes. Big paragraphs that say little. Promises that sound impressive but don't show the actual thing working. It occurred to me — if I can't write a clear story about what I'm building, maybe I haven't built something clear yet.
The product story as a test. If your messaging feels scattered, maybe your product is scattered. If it feels forced, maybe the core idea needs rethinking.
What I've started doing: writing the product story first, before the features. Just the problem and the outcome, stripped down. If that story doesn't feel like what I'm trying to make, I have a mismatch to fix.
Anyone else using their product story as a way to pressure-test what they're actually building?
Top comments (1)
Writing the story first catches scatter, but you're still the one grading it, and you already know what you meant. The harder version I'd run: write it as a reply to a stranger who described the problem in their own words, then delete every line that names your product. If what's left is useless, the story was carrying the product rather than describing it. That's the bar we hold drafted replies to at Viewfy.