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ExactOnce – API for actions that can only happen once

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ExactOnce – API for actions that can only happen once

I kept rebuilding the same pattern across products (idempotency keys, Redis TTLs, unique constraints) just to avoid duplicate side effects from retries and race conditions. Eventually I turned it into a focused API. ExactOnce lets you create an action and consume it exactly once. The transition from active → consumed is enforced atomically via a DynamoDB conditional write. Under concurrency, one request succeeds; the rest deterministically get a typed 409 already_used. No distributed locks, no cross-service transactions. Use cases: + magic login links + coupon redemption + webhook deduplication + one-time download links + ticket scanning + license activation Try it without signing up: curl --request POST https://api.exactonce.com/v1/demo That returns a temporary action (5‑minute TTL) and a reveal URL. Open it once — it consumes. Open again — already used. Docs: https://exactonce.com/api-docs How it works: https://exactonce.com/how-it-works Private beta is free. Happy to answer questions about the DynamoDB implementation or the atomic consume pattern

Visit productView on Hacker NewsFeb 26, 2026
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
74%74% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
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
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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