Writing code that respects freedom, exploring hardware that others left behind.

Hi there! Welcome to my digital backyard.

I'm a 19 y.o developer obsessed with what happens under the hood of our devices. I transitioned from writing simple Bash scripts to diving deep into system kernels and firmware. Whether it's building secure environments or finding exploits in closed systems, I love the process of dissecting complex technology.

When I'm not making commits, I'm likely reviving discarded electronics, poking holes in iOS security mitigations, and delving into the internal mechanisms of other operating systems.

If something has a bootloader, I probably want to unlock it. 🔓

I believe in open ecosystems, right-to-repair, and that one person's electronic trash is another's weekend project.

• Diving into Linux / AOSP and researching GrapheneOS, QubesOS and SecureBlue.
• Tinkering with coreboot to liberate hardware firmware.
• Exploring iOS internals and jailbreak techniques.
• Proudly collecting "e-waste"s — giving vintage electronics a second life. 💖

Feel free to reach out for tech discussions, open-source collaborations, or if you have some cool electronic junk to share!

I use LLMs in my workflow. If that concerns you, read this first:

AI is neither a messiah nor a boogeyman; it is simply a tool. Like an IDE or a compiler, it scales the intent and capability of its operator—outputs garbage for the lazy, scales brilliance and scaffolds masterpieces for the disciplined.

Code has no origin; it only has quality. Correctness and maintainability are the ONLY metrics that matter, regardless of whether it was typed by human fingers or generated by a neural network. Even there's a cat walking on a keyboard—Does it compile? Does it pass tests? Is it secure? Is it maintainable? That's all that matters.

Blindly opposing AI is not just outdated dogma; it is an active security liability. Entities like Cellebrite and various threat actors are already weaponizing AI at scale to hunt 0-days. Blindly banning AI in open-source development isn't "protecting" anything; it's burying our heads in the sand and disarming ourselves. To defend effectively, we need AI to scale our code reviews, write comprehensive tests, and deploy patches faster.

If you see hallucinated function calls, broken control flows, or off-topic issues, that is not an LLM fault—that is a human problem. It’s the failure of the human operator to review their own work. The model may have generated the mistake, but the person submitting it owns the change. Blame the meatbag who copy-pasted it without reviewing, not the matrix math. AI is not a scapegoat.

I can sympathize if you are pestered daily by terrible AI-generated requests; you are right to reject submissions that are unreviewed and untested by the sender. However, “AI-generated” is not, by itself, a complete quality assessment. Dismissing functional software as "AI slop" without reading a single line of code is not quality control. It is the laziest possible gatekeeping. The drive-by label itself is the real slop.