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I built an extension that let AI controls my web browser

Hacker News

I built an extension that let AI controls my web browser

Hey Hackers! I've had this idea stuck in my head for a while: what if an AI could actually use my browser for me? I mean, not on some virtual machine in the cloud like ChatGPT agent, but right on my own browser. I finally decided to just build it and see what would happen. I wrote a quick MVP, and honestly, I didn't expect much. But then... it started doing things. On its own. It figured out how to use search engine to find what I needed, read a webpage to answer my questions, and even it can organize my chaotic mess of tabs into neat groups. It was a genuine "whoa" moment for me. That's when I knew I was onto something potentially cool. I roped in a designer friend to help me make it usable (so it doesn't just look like my personal science project!), and now I think it's ready for some fresh eyes. This is super, super early. It can be a bit wonky, and some tasks might fail. To be completely honest, I haven't even figured out the "killer" use case myself yet. And that's the whole reason I'm posting it here. I'm just incredibly curious to see what happens when other people get their hands on it. What will you even use it for? You can leave a feedback here or send a feedback on the extension. Thanks!

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agent, new · Missing: agents, macos, cursor
96%96% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
53%53% predicted probability of success on AppSumo, 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
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
41%41% 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
12%12% 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 · 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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