Most coding platforms train engineers to solve isolated algorithm problems. But in real engineering, you rarely reverse linked lists. You debug production systems. You trace issues across files. You deal with incomplete logs, unexpected states, and systems you didn’t write. so I built something around that. Recticode is a platform focused on real-world debugging challenges. Instead of algorithm pu
The Challenge: Beyond the "Lift and Shift" Fatigue The real fear isn’t migration itself—it’s operational fragmentation: different tools, different processes, and different failure modes between the data center and the cloud. After deep-diving into the Nutanix ecosystem, I realized that the goal shouldn't be just moving VMs, but achieving operational symmetry. This is where Nutanix Cloud Clusters
First Release of LDL 0.1 — A Small Library with a Big Soul. One API for 30 Years of Computer History Hello, developers! I'm excited to announce the first public release of the LDL library. LDL (Little Directmedia Layer) is more than just a cross-platform library — it's a bridge between different eras of software development. It lets you write code that runs just as well on Windows 95 as it do
TL;DR macsh is a tiny menu-bar app that mounts SFTP, S3-compatible, and FTP/FTPS servers as native macOS volumes. Open them in Finder, drag files in, edit in place. No macFUSE, no kernel extension, no Recovery-mode reboot. Apache-2.0, free. Heads up: macsh is built with Claude Code. I'm the designer, tester, and maintainer; the implementation is AI-written under my direction. Bugs and decisions
Book: Hexagonal Architecture in Go Also by me: Thinking in Go (2-book series) — Complete Guide to Go Programming + Hexagonal Architecture in Go My project: Hermes IDE | GitHub — an IDE for developers who ship with Claude Code and other AI coding tools Me: xgabriel.com | GitHub You sit down to write the first test for a new Go service. Reflex kicks in. You reach for mockgen, or mockery, o
We all understand that free services from a company that is spending billions on computing power won't remain free. It's inevitable. But the reality is we are all already using Codex. OpenAI recently announced that Codex was made available in ChatGPT for free, but access was limited. At the moment, developers can use code completions, refactorings, or generate entire functions without spending any
I assumed chunking was a solved problem. Pick a text splitter, set 512 tokens, add some overlap, move on. After running structured experiments across three different data types, that assumption collapsed. The best chunker for markdown documentation actively hurt performance on code. The winner changed completely depending on what I was chunking. Data type Winner Headline metric Markdown doc
Python has optional type annotations - also called "type hints". Like this: def entry_to_dict(entry: Entry) -> dict: return { 'title': entry.title, 'num_likes': entry.num_likes, 'url': entry.url, } The annotations here being "Entry" as the type for the "entry" argument, and "dict" as the return type. In fact, there are at least 3 ways type annotations can be us