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Mailrecipe limits the number of emails you send to a user to 1 per day

Hacker News

Mailrecipe limits the number of emails you send to a user to 1 per day

Last week, I spammed my users with emails by mistake. I had written an idempotent method to do a transaction and send a confirmation email. I didn't realize the email call is not idempotent. So, when the transaction failed, it retried again and again and spammed the entire user base with emails. I was so embarrassed and wrote an API layer on top of my email delivery service (SendGrid) to ensure that my users won't get more than 1 email per day, irrespective of my architecture or mistakes. I am publishing it as a public API, in case anyone else needs it: https://rapidapi.com/mailrecipe/api/mailrecipe Have you run into this problem? How did you solve it?

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Indie HackersFits the IH revenue-focused audience · Strong signals: mistakes · Missing: supports, reddit linkedin, podcasting
71%71% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, email · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · 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 · Strong signals: arr · Missing: mrr, revenue, profit
15%15% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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