Hoodmaps Meets 4chan

Hacker News

I made this as a pair programming exercise with o1-preview. o1 did most of the heavy lifting, through high level prompts, but eventually I needed to diverge from it to get to completion. My initial prompt was: --- I'm making a web app: It's like 4chan, but each thread starts with a gps coordinate. People can only post text and images. I want to build it with flask and sqlalchemy. I want just the backend and data model that supports these threads, anonymous users, and users that can register a permanent username. Write as much of it as you can for me. --- This produced a fully scaffolded Flask app running on sqlite. After that, it took a few (casual) evenings of iteration to dockerize everything, implement postgres instead of sqlite, and use a bucket for storage. On my own, this would have easily taken me 10x the time.

Visit product View on Hacker NewsSep 23, 2024

Share card

Actual performance

8points

2comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

80%80% 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: io · Missing: https docs, excited, just released

74%74% 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: model, user, dock · Missing: mac, agents, macos

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

19%19% 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

StumbleUpon Meets ProductHunt50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

StumbleUpon Meets ProductHunt

Hacker News1

TechCrunch Meets the Onion46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TechCrunch Meets the Onion

Hacker News3

OpenVino - Yelp meets OpenTable for Wine53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

OpenVino - Yelp meets OpenTable for Wine

Hacker News2

VerticalChange, SurveyMonkey meets Highrise (and a LOT of AngularJS)47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

VerticalChange, SurveyMonkey meets Highrise (and a LOT of AngularJS)

Hacker News16

Sevenfold31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tetris meets crosswords

Indie Hackers1games

InstaRoasts37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Where Humor Meets the Heat! 🔥

Product Hunt+6

ArcRefinery49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Storytelling meets AI

Product Hunt+7

Google Goggles meets Beer Goggles57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Google Goggles meets Beer Goggles

Hacker News4

Meets Participants Manager44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Keet track of participations on Google Meets

Indie Hackerscommitment-side-project

Collatz^Reich – when the 3n+1 conjecture meets Clapping Music47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Collatz^Reich – when the 3n+1 conjecture meets Clapping Music

Hacker News2

Browse all products Analyze your launch