WAYF – A Simple Scheduling App

Hacker News

A dead-simple web app to find the best time for your next meetup with friends. No logins, no bloat. Schedule with a link. --- When trying to schedule events with my friends, we often have a long text thread of sporadic dates and the group has to mentally combine all the messages to produce a date that works for all. There are plenty of apps out there to coordinate scheduling, but I found many of them were bloated with features that didn't matter to us, required user sign ups and app downloads. This friction is enough for us to prefer rudimentary long text threads. I wanted something that I could post in the thread once, my friends can add their availability on their own time (and can edit), and we can continue on our conversation. WAYF (When are you free?) is a fun side project that solves this issue. Bare-bones scheduling for what days you are free. No user accounts, no downloads, just paste a link and anyone can schedule. It's completely free. I hope you like it and find it useful, I would love feedback.

Visit product View on Hacker NewsJan 27, 2024

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

83%83% 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.

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

42%42% 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

41%41% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

40%40% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% 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

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.

Incorrect prediction on native model

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