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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LLMs hallucinate. That's not news. What's underdiscussed is how that failure mode behaves in long working sessions: confident reconstruction that looks fluent, cites specifics, and feels right — until three sessions later when something supposed to be true turns out not to be. This is week 5 of an 8-week deep dive on CRAFT for Cowork, a structured working environment for Claude. The QA framework t
You don’t notice the problem right away. Everything runs smoothly in MySQL… until a new report shows up. Then queries slow down, dashboards lag, and you start realizing you’re stretching the database beyond what it’s good at. That’s usually when BigQuery enters the picture. So the real question becomes: How do you actually move data between them without turning it into a side project? Let’s w
Where It All Began: 2019 re:Invent AWS CDK had just gone GA that year with TypeScript and Python support. At re:Invent 2019, I saw AWS present how to contribute to CDK for the first time. There was no AI back then — everything was manual. Clone the entire monorepo, figure out the Lerna project structure, manually build dependent packages, write L2 constructs, write tests, submit a PR. Every step
Generate a CycloneDX SBOM and deterministic, audit-ready risk report from your package-lock.json. You run npm audit. It says “47 vulnerabilities.” Cool. Which ones actually matter? The one in your production bundle? You don’t know. So you either: Ignore everything → ship anyway Either way, you lose signal. The real problem isn’t vulnerabilities — it’s decision-making Most tools answer: “What is wr
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