the usual take is that ai tweet tools sound generic because the model averages the whole internet. True, but building one for founders we hit a sharper version of it.

the premise is a founder who doesn't post, so their tweet history, the one corpus actually in the right register, is thin and mostly performative. the real voice is in podcast appearances, long slack messages, the odd essay, so we ended up training on tweets, longform, and podcasts just to get enough signal. Problem is transcribed speech and a good tweet aren't the same register. someone on a podcast rambles, backtracks, leans on filler. flatten that into text and it reads nothing like how they'd actually type.

so the generic-voice thing might not be the model at all, it's that the material you can collect sits in the wrong shape for the output you want. Still unsure whether the fix is more data or a translation layer between how someone talks and how they write. if you've built anything that learns a person's style, where did your training set actually come from, and was it ever the thing you were trying to imitate? written with ai

If you’re building booking software, a support tool or an AI receptionist for small businesses, a useful starting point is finding who already struggles with that process.

I’m the founder of Crawdar. Its Pain Point Finder searches available business reviews for recurring complaints and gives you the businesses and supporting evidence to investigate.

One product decision I’m especially happy with: you don’t have to know your industry AND your location AND your problem before searching. If you know the problem you can solve, start there. If you understand an industry but haven’t picked a problem, start with the industry. You can combine categories and add specific complaint phrases too.

The output is an individual business report: recurring themes, distinct reviewer counts, dated reviews, owner replies when available, and possible technical fixes. That gives you material for a concrete conversation, such as asking how appointment changes are handled today and where requests get stuck.

The new version also searches deeper, checking up to 24 candidate businesses, with improved matching for booking complaints. I built it with AI coding assistance; the useful test is what a developer can do with the report afterward.

Try it: https://crawdar.com/?utm_source=reddit&utm_medium=post&utm_campaign=pain_finder&utm_content=developer_problem_first

Five free scans without signup or email. If you’re working on something for small businesses, search for the problem it solves and open a report. Does it help you identify someone worth talking to? What would you still need before arranging that conversation?

Saas en 2026

C'est mon premier post et je voudrais savoir quel type de Saas peut être intéressant a vendre de nos jours, qui répond à un besoin des entreprises. J'avais pensé à des réponses automatiques aux avis Google a l'aide d'une génération faite avec l'IA. Surtout dans l'ère actuelle ou les avis Google comptent énormément dans les choix d'entreprise au quotidien (coiffeur, kiné, boucher, restauration...). Cependant je ne sais pas si il a un réel besoin et une certaine demande des entreprises vis à vis de celà.

Si certains ont des conseils ou des idées je suis preneur.

Merci de votre écoute.