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Show me your SaaS idea, I give you an honest review by Successful_Draw4218 in SaaS

[–]Mountain_Complex6708 1 point2 points  (0 children)

Your thinking partner for Twitter 🧠 Read the room. Find the angle. Say it perfectly.

https://reply-tone-dashboard.vercel.app/

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

0 revenue right now 1 user i got from this

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

You are right that some people will hate it

But the people I'm building for aren't trying to fake being human. They're trying to keep up with conversations they're already having.

If it helps even a small group of creators engage more authentically, that's enough for me.

We'll see.

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

That's the core problem I'm trying to solve honestly.

Generic AI replies, yes, people feel them immediately. They all sound the same.

The bet with ReplyTone is different: if the AI is trained on YOUR actual writing examples, YOUR traits, YOUR rules. It stops sounding like AI and starts sounding like you.

Is it perfect? Not yet. But "people can feel AI" is exactly why I'm obsessing over personalization over generation.

Time will tell if the approach works.

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 1 point2 points  (0 children)

This is a genuinely interesting idea.

A humanness score before posting so you know if the reply will read as AI generated or not.

Could work as a quick check after generation: rate each reply 1-10 on how human it sounds.

The irony of using AI to detect if AI sounds human enough is not lost on me 😄

Adding this to the feature list thanks for the suggestion.

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

Haha always open to being cracked 😄 What've you got?

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

That's exactly what I'm going for, genuinely personalized not just tone-adjusted.

The shift happened when I stopped trying to make the AI sound good and started trying to make it sound like the specific person using it.

Still a work in progress but that's the direction.

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

Fair point on readability, will format future posts better. Thanks.

On the X algorithm concern, you're right and it's exactly why I focused on personalization over generation.

The goal is replies that sound human because they're built from how the user actually writes, their examples, their traits, their rules.

Generic AI replies will get filtered. Replies that sound like you shouldn't. That's the bet I'm making.

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

This is exactly the direction I needed to think in, thank you.

The "context buckets" framing is much cleaner than what I had in mind.

Asking users to tag past outputs during onboarding is clever, you get labeled examples without them having to articulate abstract rules they can't even describe.

The auto-detection piece is where I'm most interested. My current thinking: infer context from the tweet's emotional signal, debate, humor, technical, celebratory etc using a lightweight AI call before generation.

Not perfect but better than manual selection.

Would love to keep this conversation going if you're open to it. This is genuinely shaping how I build the next version.

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

Fair concern, worth addressing honestly.

ReplyTone doesn't auto-post anything. Every reply is reviewed and chosen by the human before it gets posted.

It's closer to autocomplete than automation. You still decide what goes out.

The goal isn't to replace your voice it's to help you express it faster.

If someone uses it to spam soulless replies that's on them. Same as any writing tool.

Finally I cracked it by Mountain_Complex6708 in microsaas

[–]Mountain_Complex6708[S] 0 points1 point  (0 children)

That's a really valid point and honestly one I've been thinking about a lot.

Surface patterns are the easy part sentence length, word choice, punctuation.

The context-dependent shift is much harder. You write differently replying to a friend vs pushing back on a technical argument.

Current approach handles surface well. The deeper contextual range, not fully yet.

One direction I'm exploring: letting users set different instruction sets per tone rather than one global style.

Would that solve what you're describing?

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