A disposable AI assistant for social commerce

Hacker News

I believe an AI assistant should be as disposable as an instant ramen cup. It should be easy to use and help us get the job done. One task where an AI assistant can be very useful is avoiding the hassle of bargaining or selecting the best prospect when we try to sell or buy anything on social media. I mean using our personal accounts on Facebook or Instagram to write a simple post to sell or buy something. I know Facebook provides an AI bot for business users or Facebook Pages, but it is too much hassle to set up. I see a lot of people selling or buying stuff on their personal accounts on social media, and I bet they feel annoyed when they have to reply to many people asking the same information or trying to haggle over the price. That's how I feel when I'm trying to sell my old stuff on Facebook. So I spent the last 4 weeks building socool.ai. This can help us create a link with an AI assistant to handle selling or buying a product on social media. Then all of the prospects can negotiate with our AI via the link, which can save us so much time. So, I would love to hear what you guys think about a disposable AI assistant for social commerce. Thanks

Visit product View on Hacker NewsJul 16, 2024

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best fitHighest predicted score across all platforms for this description.

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

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

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

47%47% 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

29%29% 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

28%28% 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

18%18% 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

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