A Directory of 500 HN Side Projects

Hacker News

I loved this recent "Show and Tell" thread about side projects posted on HN: https://news.ycombinator.com/item?id=42373343 It inspired me to build a mini directory that aggregates over 500 side projects posted to HN since 2017. You can filter by year, category, or revenue level. Thank you Cursor + Next.js for making this insanely fun to build. Hopefully you discover hidden gems or find inspiration in what the HN community is creating. Happy browsing!

Visit product View on Hacker NewsDec 17, 2024

Share card

Actual performance

15points

4comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: cursor, new · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

20%20% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

wheretosubmit60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A curated directory of 500+ backlink and can tracked.

Indie Hackerscommitment-side-project

Made With JEV10%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The #1 directory of projects built with Jev.

TrustMRRArtificial Intelligence

500 TILs and Counting48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

500 TILs and Counting

Hacker News2

I made an open source directory of where to showoff your projects66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made an open source directory of where to showoff your projects

Hacker News185

Directory of Breeding Birds in Puerto Rico36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Directory of Breeding Birds in Puerto Rico

Hacker News1

Directory of NextJS Starters and Boilerplates35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Directory of NextJS Starters and Boilerplates

Hacker News2

I made a directory of directories (seriously)36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made a directory of directories (seriously)

Hacker News5

Directory of mashups36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Directory of mashups

Hacker News2

escort directory39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

escort directory

Indie Hackers

escorts directory9%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

escorts directory

Indie Hackers

Browse all products Analyze your launch