I

I was tired of people dmming me just "hi", so I made this - NoGreeting

Hacker News

I was tired of people dmming me just "hi", so I made this - NoGreeting

most people on social media don't know how to text they think starting with a greeting and waiting for a response is kind because that's telephone etiquette, but don't understand that doing that over text is like someone calling you, saying "hello," then putting YOU on hold. literally making the other person do extra work to find out what you want. so I made this website Instead of spending time explaining them this concept (and maybe coming off as very rude), I just keep this in my bio or send them this link when they do. Pick your name. Pick the greeting trigger. Get a link. (optionally select one of the 16 languages) They get a friendly explanation of why leading with context matters. You save 10 minutes. Everyone wins. Train your network to respect your time by being clear about what you need. Life's too short for message ping-pong with strangers. PS: this builds on the legacy of nohello.net but adds the option of other greetings and adding custom names in the messages also open source! https://github.com/Kuberwastaken/nogreeting

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: context, open, plain · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, io · Missing: https docs, excited, just released
40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
38%38% 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 · 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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