Note: This guide is based on technical research from authoritative security sources, NIST publications, MITRE ATT&CK documentation, and open-source security automation frameworks. The techniques described are technically sound and based on documented production implementations. Readers should adapt these approaches to their specific security requirements and compliance needs. Security Operations Centers (SOCs) face an overwhelming volume of security alerts. According to the Ponemon Institute’s 2023 Cost of a Data Breach Report, organizations receive an average of 4,484 security alerts per day, with SOC analysts able to investigate only 52% of them. AI-powered automation offers a path to handle this alert fatigue while reducing mean time to respond (MTTR). ...

I’ve been running My Battles With Technology as a WordPress site since December 2020, after starting on Kubernetes with a custom nginx+PHP+git-sync deployment. While WordPress served me well for content management, I kept hitting the same pain points: plugin updates breaking things, security concerns with PHP, and the overhead of managing a database for what’s fundamentally a read-heavy content site. After reading about static site generators and seeing Hugo mentioned repeatedly in infrastructure circles, I decided to migrate. Here’s what that journey actually looked like. ...

Note: This guide combines personal experience from writing deployment scripts across macOS, Linux, and Windows environments with patterns documented in the Python pathlib documentation, Git documentation, PowerShell cross-platform guidance, Python subprocess module, and GitHub Actions runner images. A deployment script that works on macOS. A colleague runs it on Windows. It fails immediately. The culprit? A hardcoded forward slash in a file path. I’ve seen this exact scenario play out multiple times over the past five years, and it’s almost always preventable. ...

This is Part 4 of “The Centaur’s Toolkit” series, the finale. We’ve covered collaboration fundamentals, security applications, and calibrating trust. Now we tackle the question that ties it all together: is this actually working? You’ve been using AI as your coding partner for three months. You feel faster. More productive. Like you’re getting more done in less time. But feelings lie. That sense of productivity might be real. Or it might be the satisfaction of constant activity masking the fact that you’re shipping buggier code, accumulating technical debt, or slowly losing skills you used to have. ...

This is Part 3 of “The Centaur’s Toolkit” series. We’ve covered AI pair programming fundamentals and building AI-assisted security tools. Now we tackle the hardest skill: knowing when to trust what AI tells you. Last week, I asked an AI to help me understand a library I’d never used. It gave me a confident, detailed explanation of the validateSchema() method, complete with parameter descriptions and example usage. The method doesn’t exist. The AI invented it. The explanation was coherent, the examples looked plausible, and if I hadn’t tried to actually use the code, I might have wasted hours debugging a function call to something that was never real. ...