A first-principles critique of the AI Code Review Bench methodology, arguing that AI code review has split into two distinct problems — human comprehension and machine verification — that no single benchmark can yet capture.
As developers, we trust Git with our code, our configs, even our notes, but never our money. Here's what happened when I found a tool that treats your finances exactly like a codebase: plain text, versioned, and diffable
Learn how neural networks work in PyTorch by building one from scratch.
You've probably built a project where one NodeMCU talks to your laptop over WiFi and thought this is great. But what if we need 10 sensors across a large building? And that's where the issues appear. In this article, we'll discuss what happens after
A first-principles critique of the AI Code Review Bench methodology, arguing that AI code review has split into two distinct problems — human comprehension and machine verification — that no single benchmark can yet capture.
As developers, we trust Git with our code, our configs, even our notes, but never our money. Here's what happened when I found a tool that treats your finances exactly like a codebase: plain text, versioned, and diffable
Learn how neural networks work in PyTorch by building one from scratch.
You've probably built a project where one NodeMCU talks to your laptop over WiFi and thought this is great. But what if we need 10 sensors across a large building? And that's where the issues appear. In this article, we'll discuss what happens after
Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. Star git-lrc to help devs discover the project. Do give it a try and share your feedback for improving the project. You'
A practical look at why AI token prices can feel both expensive and rapidly cheaper, and how falling inference costs change what customers should expect from AI products.
If your team uses a mix of Cursor, Claude Code, and Copilot, things can get messy fast. In this article, we explain how to set up a system to standardize your products, keep your design system consistent, and ensure every AI agent plays by the exact same rules.
Learn what MCPs are, how AI tools interact with them, and how to build and test your own MCP server with a hands-on example.
Why teams using AI-generated code still need lightweight verification, and how a 60-second micro-review habit with git-lrc can build institutional memory without reading every line.
Nomad is a flexible workload orchestrator that enables an organization to easily deploy and manage any containerized or legacy application using a single, unified workflow. Nomad can run a diverse workload of Docker, non-containerized, microservice, and batch applications. With powerful features, it becomes very important to secure the Nomad cluster.
Why AI-generated code needs lightweight verification, and how micro code reviews with git-lrc can improve software stability and developer comprehension.
Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. Star Us to help devs discover the project. Do give it a try and share your feedback for improving the product. I remember