Mach, a new systems language that focuses on being simple and explicit

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Hey guys. Mach is a pet project of mine that I've been designing and implementing for the better part of two years now. It's a C-like systems programming languages that takes inspiration from and attempts to combine the best parts of languages like C, Rust, Zig, and Golang in particular. Modern systems programming languages focus so much on "features" like fancy memory management, large amounts of syntax sugar for less typing, unique type systems, fancy interop, and more that just gets in the way. Mach is an attempt to bring all that back down to earth. In practice, Mach should feel like writing C with a few extra nice-to-haves. The project is in a very alpha stage, but does have a fully operational bootstrap compiler implementation as well as a full (scrappy at best) language documentation. I'm looking right now to involve people that would like to contribute or nitpick the project. It's not perfect -- far from it, but the philosophy is sound. Take a look and let me know what you think, or, better yet, join the discord and tell me what you hate about it there. Mach is at the phase right now where what it needs is heavy scrutiny and criticism to lock it down into a distinct forward path. If you can provide that, please do!

Visit product View on Hacker NewsOct 31, 2025

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

84%84% 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

77%77% 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

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

55%55% 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

40%40% 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

13%13% 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.

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