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
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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
Book: AI Agents Pocket Guide: Patterns for Building Autonomous Systems with LLMs 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 A support agent answers "no, your order shipped on time" with full
Book: RAG Pocket Guide: Retrieval, Chunking, and Reranking Patterns for Production 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 When the embedding API itself collapses, the moments-based detec
Book: Prompt Engineering Pocket Guide: Techniques for Getting the Most from LLMs 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 A finance team at a mid-sized SaaS feeds 40,000 expense receipts a
The Autonomous Paradox In 2026, we’ve moved past simple chatbots. We are building Production-Grade RAG pipelines and autonomous agents that can plan, execute, and iterate. But as an architect, I’ve noticed a glaring hole in our "Agentic" future: Identity Sprawl. We are giving agents non-human identities (NHI) with "Full Admin" permissions just to ensure the RAG works smoothly. We are effectively
Fortifying APIs: Data Validation with Pydantic When building backend services, a fundamental principle stands above all others: never implicitly trust incoming data. Client applications, whether web, mobile, or third-party integrations, are inherently unpredictable. A seemingly innocuous input field expecting an integer for "age" might instead transmit "twenty-five". Without robust safeguards, s