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lingyicute/README.md

Hi, I'm lingyicute / lyi 梨 👋

enfp & les / 92li.uk / 漫漫星河,有一颗是我。

🍐 × 💻 = ❤️ | Open Source Enthusiast, Developer & Security Researcher

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, the right to repair, and the idea that one person's "e-waste" is another's weekend project.

🛠️ Behind the screen:

  • Diving into Linux / AOSP and researching GrapheneOS, QubesOS and SecureBlue.
  • Fascinated by niche open-source POSIX systems like OpenIndiana and Haiku, currently administering Haiku's Simplified Chinese localization.
  • Tinkering with coreboot to liberate hardware firmware.
  • Exploring iOS internals and jailbreak techniques.
  • Proudly collecting "e-waste" — giving vintage electronics a second life. 💖

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

📬 Reach out:

GitHub Email Telegram

🤗 Thoughts on AI & Code Quality

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 if 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Blindly opposing AI is not just outdated dogma; it is an active security liability.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's 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.

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