Cuenv (CUE for to replace direnv, Just, and more)

Hacker News

Cuenv uses CUE configuration files to define environment variables and project tasks. When you cd into a project directory, the environment defined in *.cue is loaded automatically, and cleaned up on exit. It supports variable interpolation, secret resolution (e.g. from 1Password or GCP Secrets Manager), per shell hooks, and secure sandboxed execution via cuenv run. It integrates with Nix, devenv, and more. It’s also monorepo native, due to how CUE works by default Check it out: https://github.com/cuenv/cuenv Feedback welcome; especially on real world usage, shell integration, or improvements to the UX.

Visit product View on Hacker NewsNov 29, 2025

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

70%70% 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 · Strong signals: supports · Missing: reddit linkedin, podcasting, created

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

33%33% 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

28%28% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: real world · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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