With the rapid growth of generative AI, we have a new great model coming out every month. It makes it hard to keep track of all the different kinds of models and choose the right one for your task. In this article, I will cover the best generative AI models at the doors of 2026. I hope to make your selection of a model at least a bit easier.
Traditional machine learning creates a significant bottleneck: manual labeling can cost millions of dollars for large-scale projects, require months of expert time, and remain prone to human error and inconsistency. Unsupervised learning offers a fundamentally different approach, allowing algorithms to discover structure and patterns in visual data without any human-provided labels. In this article, we will discuss unsupervised approaches used for training image models, with no labels given a priority.
In this series, every other Wednesday, I pick one trending repo and take it apart piece by piece. This week, I pulled out one key component of the entire GasTown engine, the thing without which the agents are basically useless. That component is Beads.
Adam Kaczmarek will break down an article, "Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free," featured in NeurIPS 2025. He will also explain the background for this paper: different types of attention and gating mechanisms.
Every other Wednesday we pick one trending project and break it down into its core pieces. Not another React framework or even an agent framework - but something fresh, something that helps us understand where our industry is heading. Today’s pick: BloopAI/vibe-kanban. A tool written in Rust that tries to bring order to the chaos of working with coding agents.
This guide explains how developers can craft small, precise rules that make AI coding tools more reliable. It shows practical techniques for structuring, organizing, and enforcing rules to achieve consistent, production-grade output.
Agentic systems require a new testing paradigm focused on evaluating trajectories, not just outcomes. This post details core test types, metrics, and tools.
I've always claimed there's no better way to learn anything than to build something with your own hands... and the second best way is to do a Code Review of someone else's code. Today, we are taking on a project that made waves on Twitter (or X) and GitHub, not so much because of the complexity of the code, but because of the philosophy behind it, and above all, because of its author, Andrej Karpathy. And in this article, we'll discuss his AI consensus mechanism called llm-council.
Every other Wednesday, we’ll pick one trending repository from the previous week and give it some focused attention by preparing a tutorial, article, or code review – learning from its creators in the process. Today, we’re taking a look at a project that tackles one of the most embarrassing yet universal problems in our industry: f/git-rewrite-commits.
We’re taking the next step in the evolution of TypeOps: bringing type-safe integration to the level of full microservices. This generalization of the original design opens the door to something larger – a platform that can grow into an ecosystem of SDKs, plugins, and protocol connectors.
Welcome to the fourth article in the This Month We AIed series. In this edition, we will demonstrate how a simple CLAUDE.md file can transform chaos into clarity, reveal how to use ChatGPT to transform a lightning talk into presentation-as-code, and take you on a journey from chaotic vibe coding to disciplined specification-driven development.
If you're a developer exploring AI coding assistants, you might have encountered Claude Code and wondered how it actually works under the hood. What's the relationship between the command-line tool you install and the large language model that powers it? How does the AI decide when to read your files or run commands? And how do those CLAUDE.md instruction files actually get interpreted? This article will walk you through these questions by clarifying a fundamental distinction that often gets overlooked when people first encounter Claude Code.
