I built an agent that uses email as a file system

Hacker News

Hey HN, We're building Supafax an agent that uses email as its memory and config store. Here's how it works: - You email yourself to talk to the agent - The agent uses that slice of your outbox as it's inbox and short term memory - It can insert emails into your inbox to store routines, reminders, and rules for itself Email is such a good primitive because it's essentially an append-only immutable record of all the valuable context about you and your relationships, and agents thrive on this highly structured surface. The tricky bit is users are very reluctant to share that data with companies. So instead of storing your email in a sql or vdb we leverage your inbox to be that storage space and Supafax stores nothing. Think we're the only AI email assistant not storing your emails :)

Visit product View on Hacker NewsJun 30, 2026

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

93%93% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, io · Missing: https docs, excited, just released

42%42% 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: users · Missing: plus, platform, intuitive

36%36% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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