a Chrome extension to see other users browsing the same websites as you

Hacker News

I was once reading some comments on HN, and someone was talking about a Chrome extension they had made for themselves to write memos/notes on any website they browsed. I thought this was brilliant! This idea immediately clicked in me, and my first thought was: "Why not make it so others can see your notes as well?". And soon it transformed into something much more complex where users could not only write notes, but also interact directly with other users of the extension through chat, gis, and cursors! It took me a few weeks, but I was able to read through docs, work on the extension itself (content script and service worker), socket.io, node, build up a website, publish it in the Chrome store. I've introduced it to my coworkers and a few other devs, and so far, each one of them came up with a different usage for the extension, but loved the idea of adding a social aspect to browsing. I thought it would be great sharing it with everyone around here and gather feedback from the HN crowd!

Visit product View on Hacker NewsAug 31, 2023

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Launch Intel predictions

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

87%87% predicted probability of success on Product Hunt, 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

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

46%46% 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

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, introduce · Missing: web3, crypto, cryptocurrency

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

Correct prediction on native model

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