AI browser ninja that can complete any task on Chrome

Hacker News

Hey folks, so I built a chrome extension called [name redacted], an AI assistant that automatically completes your browser tasks for you. You simply enter your task, and [name redacted] uses GPT-4V to figure out the best browser action to perform next repeatedly until the task is accomplished. The idea is that you can delegate your personal tasks like online shopping or making reservations to [name redacted]. You can also use him professionally to find leads on LinkedIn, send status updates to your boss, or research your competitors and write an analysis document. I’m wondering if you would use [name redacted] as part of your daily routine? Would he be more useful in a personal or professional setting? What concerns do you with using a productivity tool like this? I'm also planning to add voice support and the ability to schedule tasks soon. Do either of these features interest you? If you want to try [name redacted], download the chrome extension and let me know what you think. It's completely free with no sign up required!

Visit product View on Hacker NewsDec 15, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: tasks, using · Missing: mac, agents, macos

85%85% 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.

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

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

39%39% predicted probability of success on TrustMRR, 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

38%38% 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 · 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.

Incorrect prediction on native model

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