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I'm the creator of Mach (https://github.com/octalide/mach or https://machlang.org). Two days ago, we finally achieved full self hosting. I wanted to make a post here to show off the language since this is a big milestone for us.

## TL;DR about the language for those curious:

- There are no external dependencies anywhere in the pipeline. This includes LLVM, libc bindings, or anything of the sort (save for the historical bootstrap compiler, which requires any C compiler and has been phased out completely).

- Mach is extremely opinionated and very anti-magic. WYSIWYG is a core principal for the language. There are no hidden behaviors, implicit type conversions, or "automatic features". Simplicity and stripping away ambiguity are core principals that this language upholds.

- Performance currently lags behind C by about a factor of only 4x at the time of writing, almost entirely due to the lack of deep compiler optimizations like autovectorization, which have not been fully implemented yet. Eventually, Mach will be at least on par with C.

## Why did I build this?

I love low level systems languages like C, Zig, Go, and (sometimes) Rust, but I wanted something that actively discourages "cleverness" in favor of long-term maintainability and overall clarity. Mach is highly opinionated and explicitly demands verbosity in ways that other languages are afraid to. Computers aren't magic, and code you write should not pretend they are. This project initially started out as a learning opportunity for myself, but grew into a fully featured language as time went on. There is still a lot I have to learn, however, and I'm excited to be able to do so as this project continues to grow into the future.

## Why do I (the reader) care?

If you like C, you'll probably like Mach. Mach takes heavy inspiration from the "vibe" of writing C, but improves on much of the syntax, lacks quite a few footguns, "unhides" a lot of internal mechanisms, and has a FAR better dependency management system.

If you want to play around with a language that is fully capable of replacing C, and especially if you would like to contribute to its development, then PLEASE stop by and mess around.

## Where should I go to check it out?

The github repository has a link to our discord if you'd like to chat with myself or our few other regular users. My personal account has all of the tooling that exists as well as a few example repos if you feel inclined to try it out.

## Will this project by dead in X months?

I've been working on this in the background for over 2 years now. This is a long term project that I plan to maintain into the indefinite future, with or without a userbase. If you like the language at all, I highly encourage you to get involved in its development because it WILL be sticking around in some capacity forever.

I know this was a bit "rambly", but let me just say that it's been a great joy to work on this project and I would love any and ALL opinions and contributions, ESPECIALLY if you hate the language or find a problem that needs fixing. Let me know what you guys think!

Last year, we set to answer the question “If AI can write code 100x faster, then why aren’t you shipping 100x faster?” What we learned shocked us — even fairly nontechnical people and solo founders told us they were spending more than half of their development time reading the AI-written code. And much of the rest of the time was spent either de-slop-ping it, or wishing they had done so.

As luck turns out, our last two products were a tool that quickly onboards people to large codebases ( https://x.com/0xjimmyk/status/1873357324229984677 ) and trainings that taught deep concepts of code quality to CEOs, YC founders, and engineers at top companies ( mirdin.com ), so we were extremely well-positioned to solve these problems.

Command Center is an agentic coding environment focused on quality. With a few keypresses, you can start building 3 features at once and soon have 3 diffs ready, each consisting of 2000 changed lines across 50 files….

This is normally the point where you think “Crap, what now?”

With Command Center, at this point you simply click “Refactor,” and watch the vibed slop turn into readable robustness. Then you click “Generate Walkthrough,” and then suddenly, to read a 2000 line diff, instead of scrolling up and down trying to make sense of it, you just press the right arrow key 200 times. See something you don’t like? Click on line 37, type “Do this and all other network fetches in the background Cmd+Enter,” and you have a few more agents getting your code into final shape. Click or type “Commit,” “Push,” “Create PR” — you just shipped a high quality, non-slop feature

We’re striving to be the best at every step of the pipeline, but can just try Command Center in pieces wherever you feel your current workflow is weakest. We have users who do all their coding in Zed or the Codex app, and then jump over to Command Center for a walkthrough when it finishes running. There’s even a skill that will pop open a Command Center walkthrough from the environment of your choice. Or you can just keep Command Center running while you do your work elsewhere, and if your AI deletes anything, you have Command Center’s snapshots to the rescue.

We launched quietly last year and have been refining since. The quality and usability have kept going up, and Command Center is now ready for a lot more attention.

Since our quiet launch, we’ve seen at least a dozen other agentic coding environments appear….approximately all of which have the same feature set focused on the part which is already easy (generating the first version of the code) and with at best a shoddy answer to the hard part (everything that comes after). Command Center’s focus is making the hard parts easy.

Here’s what our users have to say:

“[The refactorings] give your LLM taste. I’ve never seen an LLM write code this good before.” — Doug Slater, Staff Engineer, Climavision

“With Command Center walkthroughs, I can get through a 400-line diff in less than half the time.” — Prateek Kumar, Platfor Engineer, Sumo Logic

This product is not for everyone. If you’re someone who preaches “the prompt is the source, the code is the compiler output,” then you probably won’t enjoy Command Center.

But if you want to uphold traditional engineering discipline while also shipping 20 PRs a day, then this is the environment for you.

What is a bit unique is: 1) we built it in Rust and 2) the website is a little odd. Its design is inspired by CLIs (e.g., fzf, broot, vim) instead of web apps, and as such, lacks some affordances that you might typically expect in favor of keyboard-driven instant navigations (we have the very ambitious goal of an FCP of 100ms). In case you're curious, here's how we we built it: https://gitdot.io/designs

We recognize that we're making some bold claims here and are also well aware that we have much to learn. Building software is still hard, and that's a fact we seem to relearn everyday.

But we wanted to share what we built so far nonetheless.

Cheers, thank y'all for reading, and till the next —paul & mikkel.

hope you enjoy

https://intunedhq.com). We’re building a platform for building, deploying, and maintaining browser automations.

Customers primarily use the Intuned AI agent to automate websites that don't expose APIs. Common use-cases include scraping data, pulling reports, and submitting forms. As the website changes, our agent also helps automatically heal the automation.

On Intuned, browser automations are created by an AI agent and run as code. Our infra captures the context of every run, allowing our agent to debug and maintain the underlying code - to keep the automations working over time. This way, we’re able to offer the predictability, speed, and cost of code, without the painful parts of writing and maintaining it.

Here’s a demo of building a scraper on Intuned: https://youtu.be/ruZP73bK4FU

Here’s a demo of using AI to maintain a project: https://youtu.be/e4R4hLdHBro

Backstory: we were accepted into YC for a completely different idea. During the batch, because of Faisal's background at UiPath, several batchmates asked us whether RPA tools could fill API gaps in their products by automating websites without APIs. When it was time to pivot, we went back to those founders to dig deeper. (RPA in this context is referring to using UI automation to do complete non-testing tasks)

We discovered that the actual hard problem in browser automation is maintenance. Websites change, selectors break, and failures can be painful to reproduce and fix. So in early 2024, we decided to take a crack at this problem with a handful of customers. It needed a fair number of iterations before we landed on our current code-first approach.

How it works: Intuned is infra + agent, deeply integrated.

On the infrastructure side, Intuned is a managed runtime for browser automation code. Projects are usually Playwright-based TypeScript or Python. Users can write them directly in our online IDE, or hand the work off to the agent. Either way, once deployed, the platform runs each project in its own isolated machine and handles auth/session reuse, scheduling, batch execution, concurrency, observability, and the other plumbing around running browser code.

On the agent side, it took us a few iterations to get to the current approach. Our initial attempts were rigid pipelines: collect requirements, inspect the site, generate code, then try to patch whatever broke. It looked reasonable on paper, but real websites are too messy for fixed paths. Late last year, we were planning to ship that version when stronger models landed and harnesses like Claude Code and Codex showed what a more open-ended coding agent could do. We built a prototype on the Claude Agent SDK, it felt much better than what we had, and we scrapped the release and decided to rebuild the agent.

The rebuild came down to three pieces around the SDK: an execution environment for running long agent sessions reliably, a CLI that exposes the platform to the agent so it operates Intuned the way engineers do, and a custom plugin (skills + MCP) built around what we've learned building browser automations.

The infra-agent integration is where the product gets more interesting. The runtime doesn't just run the automation; it captures the context needed to debug it when it fails: params, results, traces, logs. That enables features like Fix with AI, where you can open a failed run and have the agent investigate and prepare a fix.

The same integration powers a feature called self-healing. For configured projects, the platform detects failures, starts an agent session with the relevant context, and either proposes a fix for review or deploys it automatically. Demo: https://youtu.be/IVHIXw0lYMs

We recently also packaged the infra and agent as an API called Web Task API, here is a demo: https://youtu.be/1olRn3l95vw

We strongly believe that browser automations can and should be faster, cheaper and more predictable. Check us out at https://app.intuned.io/, we have a free tier with trial credits for your first few automations. Excited to hear your thoughts, questions, and feedback!