I built a place to stash your naughty links

Hacker News

Show HN: I built a place to stash your naughty links My name is Andrew and I built this site on a whim I had while vacationing for the holidays. Ever find good porn but can't get to it right away? What about something you really enjoyed, where do you save it? If you're like me, you don't want naughty stuff in your browsing history and especially not in your bookmarks. So I built http://xstashed.com/hn/ (clickable in comments) - a place to stash your NSFW links. While it's a minimal viable product, I do have a basic road map that can be viewed here http://xstashed.com/todo/. As you can see a homepage is on todo list. I'll be getting to that this weekend. I just wanted to get this in the hands of potential users to get feedback early on. On the tech side of things I've built this thing nimble so that I can quickly shape the site from your feedback. For those who are interested in the technical site of xstashed, it's a custom Django (Python) application continuously deployed with Chef. MySQL for database, Celery for background task, and Redis for cache and Celery broker.

Visit product View on Hacker NewsJan 23, 2013

Share card

Actual performance

5points

11comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

87%87% 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.

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

66%66% 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 HuntOn track for Day 1 leaderboard · Strong signals: user · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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.

Incorrect prediction on native model

Similar products

The Weed Stash46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Weed Stash

Hacker News1

Tentang70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

All Your Links in One Place

Indie Hackers1communication

GoLinks32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Manage your links in one place

AppSumo

Stash It – Simple bookmarking app55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Stash It – Simple bookmarking app

Hacker News2

Cloudsurf28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A better place to share links

Indie Hackerscommitment-side-project

Firepad-based editor for Stash66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Firepad-based editor for Stash

Hacker News2

Unzeef my links47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Unzeef my links

Hacker News1

Bitly is expensive so I made a tutorial on shortening links with Mnesia37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bitly is expensive so I made a tutorial on shortening links with Mnesia

Hacker News3

Squaresend - Less annoying mailto links49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Squaresend - Less annoying mailto links

Hacker News95

Most mentioned links on HN62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Most mentioned links on HN

Hacker News3

Browse all products Analyze your launch