better-env – A Secure, Developer-Friendly Alternative to .env

Hacker News

I’ve always hated how archaic .env files feel. Plaintext, easy to leak, and once they hit git history… you’re cooked. After accidentally committing secrets a few too many times, I finally asked myself: why don't we encrypt secrets just like passwords? So I built better-env: a local, encrypted way to manage secrets without exposing plaintext all over your machine. One place for secrets, nothing sensitive in git, your secrets get directly loaded at runtime, project-wise. It’s early, local-first, and still rough around the edges, but it already removed a whole category of stress from my workflow. I’d love feedback on whether this feels useful beyond solo devs, and what you’d want for team/CI setups. It's open source too! ( https://github.com/HarishChandran3304/better-env )

Visit product View on Hacker NewsNov 23, 2025

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

90%90% 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

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, ide · Missing: https docs, excited, just released

50%50% 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: friendly · Missing: plus, platform, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

48%48% predicted probability of success on TrustMRR, 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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