Welcome to my technical journal. This blog serves as a dedicated engineering space to document architectural decisions, low-level optimizations, and real-world lessons from building developer tooling and backend infrastructure.
What to Expect Here
In upcoming posts, I will be deep-diving into the mechanics behind my open-source projects:
-
Rust & Systems Computing:
- Building local development servers using Tokio and Axum with < 5ms startup.
- Compiling perceptual color models (OKLCH, APCA, spectral CVD matrices) to WebAssembly.
-
AI Protocols & Developer Tooling:
- Architecting native Model Context Protocol (MCP) JSON-RPC 2.0 servers.
- Enabling IDE AI assistants to reason over codebase ASTs and design tokens.
-
Infrastructure & Hardening:
- Idempotent Linux cloud baselines for Ubuntu 24.04 LTS.
- Container orchestration with Docker, UFW firewall rules, Fail2ban, and Caddy TLS.
Code Example: Color Math in Rust
Here is a quick glimpse of how Colorust processes bidirectional OKLCH space conversions:
#[derive(Debug, Clone, Copy, PartialEq)]
pub struct Oklch {
pub l: f32, // Perceptual Lightness [0.0 .. 1.0]
pub c: f32, // Chroma [0.0 .. ~0.4]
pub h: f32, // Hue in degrees [0.0 .. 360.0]
}
impl Oklch {
/// Convert an sRGB color into perceptual OKLCH color space
pub fn from_rgb(rgb: &Rgb) -> Self {
let oklab = Oklab::from_rgb(rgb);
Self::from_oklab(&oklab)
}
}
Image & Asset Support
Astro natively supports full image optimization with zero layout shifts, automated WebP/AVIF conversions, and responsive scaling:

Stay tuned for in-depth technical breakdowns and benchmarks.