Watch, Read, Listen
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If you build on AWS long enough, you’ll eventually face the same question: Where should we store secrets and configuration? Keeping stuff in a local env file or applications.properties means either those files are going to get checked in, or even worse, casually shared between engineers. And what if your builds are made in a
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Executive Summary On-demand cloud workstations unlock powerful, cost-efficient computing for engineering teams. But as organizations scale beyond a handful of machines, a new challenge emerges: consistency. Manually configuring Windows systems through portals, scripts, and remote desktop sessions introduces drift, delays, and operational risk. This paper explores how Terraform and Infrastructure as Code (IaC) transform Azure-based
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Executive Summary Engineering teams increasingly need access to powerful computing resources, but not always on a continuous basis. Many modern workloads — from large builds and simulations to data processing and 3D rendering — are intense, short-lived, and highly variable. In these cases, traditional rack-mounted servers often lead to low utilization and high fixed costs.
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File extensions matter more than we like to admit. They’re not just a technical footnote — they’re a shared language. When you see .jpg, you expect an image. When you see .py, you expect Python. When you see .md, you expect Markdown. And that’s exactly the problem. Right now, the vogue in AI tooling is
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Over the last several days, we’ve been trying to solve what initially felt like a very reasonable problem: Can we use an AI assistant as a reliable, step-by-step installer assistant to a human for a moderately complex toolchain? On the surface, this seemed like a perfect use case for AI. The setup process is linear.
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Most people think “AI” means neural networks, training data, and a lot of math. Tic-Tac-Toe is a great counterexample. You can build a perfect Tic-Tac-Toe AI without learning, randomness, or guesswork—just logic, structure, and a clear way of evaluating outcomes. This post explains how an AI Tic-Tac-Toe engine works conceptually, without code, using plain language.
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If you’ve been following agentic AI systems like Codex-style coding agents, you’ve probably seen references to things like agents.md, skills.md, or “tool catalogs.” At first glance, these can look like extra ceremony — more files, more config, more abstraction. They’re not. They’re the reason agentic systems work at all. This post explains what agents and
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What Is n8n? If you haven’t heard of n8n yet, don’t worry — it’s nowhere near widespread adoption yet. But it’s coming fast. n8n is an open-source workflow automation platform that lets you connect APIs, services, scripts, and humans into long-running, stateful workflows. Think of it as a developer-friendly alternative to tools like Zapier, but
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If you spend any time doing remote development over SSH—especially with tools like VS Code Remote—eventually you hit the same annoyance: You know SSH keys are the right answer,you know passwordless login is possible,but the setup always feels more manual than it should. For years, I handled this by copying keys around by hand, editing
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Using AI to accelerate development is amazing—agents can write code, open pull requests, fix bugs, and keep your project humming. But giving your AI the same permissions you give trusted human maintainers is a silent disaster waiting to happen. Here’s the simple truth: your AI should always log into your repository with an account that