In my last article, I mentioned that my SAST tool uses regex-based pattern matching instead of AST parsing, and that this was a deliberate tradeoff. A few people asked me to go deeper on that decision — because on the surface, it sounds like I took a shortcut. I didn't. Or rather — I did, but it was an informed shortcut, and there's a meaningful difference. Let me explain what AST parsing actually
All Algorithms implemented in Python
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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
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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