Zen Mascot

I build simple solutions
for complex problems.

Hi, I'm Ghazi. I build lightweight tools for developers, focused on performance, clarity, and privacy-first systems.

See my projects
file_type_python file_type_mysql
Currently Building

docmd

Build production-ready documentation from Markdown in seconds. No React, no bloat, just content.

DocumentationMarkdownCLIBunNode.jsTypeScript
Check it out →
docmd

memoryblock

Private AI workspaces that run locally, using fewer tokens and less compute.

AILLMPrivateLocalWeb AppCLILibraryBunTypeScript

AIMonitor

Native macOS menu bar app for monitoring AI usage, quotas, and provider status in real time.

macOSSwiftAIMenu BarOpen Source

Latest Rollups

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Sep 25, 2026

Speculative Decoding Meets Vision: LFM2.5-VL Gets the Speed Treatment

Liquid AI's DSpark draft model accelerates vision-language inference by 2.3x on-device and 20x on GPU, but Amdahl's law reveals the real bottleneck.

Sep 25, 2026

Docker Sandboxes Give AI Agents Real Boundaries

Docker's new Sandbox Kits and Cloud Sandboxes create reproducible, isolated environments for AI agents. Here's why that matters for the future of autonomous tooling.

Sep 25, 2026

Professional Skepticism in an AI-Driven Testing World

Why developers need healthy skepticism when adopting AI agents, test-driven development for agentic systems, and what flaky tests really tell us about our code.

Sep 25, 2026

Google's AI Video Co-Director Solves the Long-Form Generation Problem

Google researchers introduce a multi-agent framework that maintains visual consistency across minutes-long AI videos, tackling character drift and cascading failures in generative pipelines.

Sep 24, 2026

Speculative Decoding Hits Vision Models: What Developers Need to Know

Liquid AI's DSpark draft model accelerates vision-language inference 2-3x on edge devices and 20x on H100s. Here's what it means for your stack.

Sep 24, 2026

Building Fast Diff Surfaces: How GitHub Handles Million-Line Pull Requests

Inside the architecture behind rendering massive pull requests with hundreds of comments performantly. A deep dive into virtualization, geometry, and engineering trade-offs.