Sloppie – Agentic development environment for Linux

Hacker News

Hi! In my own development work I have noticed I less and less reach for Emacs and rather need the combo of a coding agent + git diff viewer + a stack of code-review comments to handle later. There's a lot of apps that do more or less that but mostly for Mac, heavy churn and too much features I don't need, arranged in a way that makes for a noisy and distracting interface. So, I wrote my own. Not as a throw-away project but one to actually use daily. It's tailored for my own needs and probably not useful as-is for others, but maybe something for inspiration or customization.

Visit product View on Hacker NewsAug 24, 2026

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

94%94% 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.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

61%61% 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: interface · Missing: plus, platform, intuitive

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

20%20% 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.

Incorrect prediction on native model

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