sara_builds

Sorry for that X(. It is fixed now...

Great question! That's exactly what Voice Profiles are for.

In the dashboard, you can set up: - Your business description (so AI knows context) - Voice instructions (e.g., "friendly but professional", "use humor", "keep it short") - Example responses you've written before - Custom sign-off

The AI uses all of this to match your tone. So if your style is casual and witty, responses will sound casual and witty. If you're more formal, it adapts.

The goal is that responses sound like YOU wrote them, not a bot. Most users tweak their voice profile once and then forget about it.

Yes! It works with any language. The AI detects the review language and responds in the same language. We've tested with Romanian, German, Spanish, French — all work great.

If you want the response in a different language than the review, you can specify that in your voice profile settings too.

A few personas came to mind:

1. Indie hackers validating ideas — need a working form/API for their landing page before committing to a "real" backend

2. No-code builders on Webflow/Framer/Carrd who want dynamic data but don't want to learn Firebase

3. Freelancers (like me) who keep getting "can you make this spreadsheet accessible via API" requests from clients

4. Internal tools teams who already have data in Sheets and just need to expose it to a dashboard

The common thread: situations where the data naturally lives in a spreadsheet, and spinning up a proper database feels like overkill.

The variance mostly comes down to prompt craft and context management.

People who get consistently good results have usually internalized a few things: (1) being explicit about constraints and output format, (2) providing relevant context without noise, (3) matching the model to the task (reasoning-heavy vs creative vs code), and (4) iterating on the prompt when something fails rather than assuming the model is broken.

I've seen the same person get wildly different results depending on whether they ask "write code to do X" vs "I need a function that takes A, returns B, handles edge case C, and should be optimized for D. Here's the existing code it needs to integrate with: [context]."

The gap between those two approaches can be a 10x difference in usefulness. Most of the "LLMs are useless" crowd and the "LLMs are magic" crowd are just working with very different prompt habits.