WebReducer.dev instant stateful endpoints with replayability

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Hey everyone, WebReducer is a project I've been working on since last December. You can read about my process here: https://offbyone.us/tags/micro-business/ Send some data to WebReducer. Then, write a reducer function to retain some state. You can change the reducer function as much as you want and recreate that state. Still working on how to explain it. It's a tiny FaaS platform. It's a tiny database. It's "redux" on the server as a service. It's a backend for tiny personal projects. It's a place to send your webhooks. I'm looking for feedback on the following: - Do you get what it is? - What would you use it for? - What would I need to iron out for you to seriously consider trying this?

Visit product View on Hacker NewsJun 28, 2022

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

82%82% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

65%65% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, 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.

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

22%22% 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

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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