Clades – an organic approach to social media

Hacker News

Bottom Line: Clades is a very early stage reddit-like platform that aims to tackle the bot problem without algorithms or an army of mods. Basically, every user is an invite of another user and those invites accrue over time making it very difficult to build up a malicious presence while simultaneously making it very easy to prune entire branches of users and content. Right now, users have to wait a week before inviting another user and they can only store a maximum of 10 invites at any time. For the next 2 days, I'm opening up registration so Hackernews users can test it out if anyone wants to. It's very much in a beta stage so data will likely be wiped before an official release. Go Crazy Clades started as a pandemic project that sat on the backburner for a long time before I realized that there may interest for it and I started polishing it up. The idea behind it is to foster the growth of small, niche communities either centered around where you live or things you're interested in. The goal is not to become the next big platform but rather to provide a quiet place where a community doesn't have to worry about brigading, drive by vandalism, or the ever present bot menace. Clades is designed to not store sensitive information like emails and tries to have a minimal data footprint while still supporting passwordless logins...if the database were compromised, no personal information could be retrieved besides usernames. I'm just a single hobby dev with a full time non-software job and I haven't really launched anything successfully yet so this is all new to me. Feedback is much appreciated.

Visit product View on Hacker NewsSep 5, 2022

Share card

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, email · Missing: mac, agents, macos

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, users · Missing: mobile apps, ios, entrepreneurs

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

SocialQ77%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Applying AI to organic Social Media Growth

Indie Hackers2$70/moai

AntiPerfume – Organic Social Distancing51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AntiPerfume – Organic Social Distancing

Hacker News1

Your Social Media Fingerprint (maybe NSFW)39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your Social Media Fingerprint (maybe NSFW)

Hacker News911

FAQ Off – Mitigate Mob Harassment on Social Media34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

FAQ Off – Mitigate Mob Harassment on Social Media

Hacker News1

Social Media Defaults for Mindfulness32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Social Media Defaults for Mindfulness

Hacker News1

Combat social media addiciton with foreign wikipedias38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Combat social media addiciton with foreign wikipedias

Hacker News1

Vers – Social Media as It Should Be32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vers – Social Media as It Should Be

Hacker News1

This is what social media could be41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

This is what social media could be

Hacker News123

Unbundling Microlearning from Social Media26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Unbundling Microlearning from Social Media

Hacker News2

Mizo49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Social Media Handled

Product Hunt+1

Browse all products Analyze your launch