AI-generated code creates cognitive debt as developers accept code they don't understand. Learn how this hidden risk threatens teams and how to fight back.
As AI accelerates code generation, many teams are discovering that speed gains often come with hidden costs in review, validation, and complexity. We sat down with Krzysztof Romanowski to unpack what’s really happening inside modern engineering organizations.
As developer experience (DX) becomes a competitive advantage, many organizations are investing in internal platforms and tooling. However, building and maintaining DX capabilities in-house is costly and complex. This raises a key question: when should organizations manage developer productivity internally, and when is it more effective to engage external partners?
Shipping a working interface has never been easier. Design tools, AI, component libraries, and modern scaffolding have dramatically lowered the barrier to getting something on screen. This article is a practical, hands-on collection of workflow improvements, UX patterns, and implementation-level pro tips - all from a frontend developer’s perspective. No lengthy theory lectures (though a few concepts need a quick explanation to make sense). Jump in and try these techniques in your own projects to measurably improve how your interface feels.
Your interface may look right in a static mockup - but users don’t experience static pages. They see content appear, load, and shift. Perceived performance often matters more than raw performance metrics. A page that loads in 800ms but shows a blank screen feels slower than one that takes 1.2 seconds but shows skeleton placeholders from the first frame.
All the interactions discussed so far need to work across devices - and on mobile, they face a different set of constraints. More than half of all web traffic comes from mobile devices, yet many developer-built interfaces are designed cursor-first and touch-optimized as an afterthought. Mobile isn’t a smaller desktop - it has its own interaction model, constraints, and opportunities.
Open any README in your repository. That flagship one. The one that's 800 lines long with a "Getting Started" section written in 2022. Read it with fresh eyes - as if you were a new developer, or better yet - as an AI agent who's never been to a standup, never seen Slack, never heard the legend of why we don't touch the InvoiceReconciler class in the payment service. Now ask yourself one question: based on this README, can you safely modify anything in this service?
Discover how TypeScript is becoming the language of intent, reshaping engineers into system designers who define contracts while AI handles code.
You've probably heard about the first METR study from July 2025 - it made the rounds at every conference and every newsletter. 16 experienced open-source developers, a proper randomized controlled trial (not a vendor survey), and the result: 19% slower with AI. In this article, Artur argues that the problem lies in the environment, not the model. Read on to find out exactly.
Welcome to GitHub All-Stars, our biweekly series where we pick a trending or freshly minted open-source project and put it under the microscope. We focus on new, relatively unknown gems - not another breakdown of the latest React release (because let's be honest, the world has enough of those). This time, we're looking at a project that lives at an unusual intersection of prepper culture, self-hosting enthusiasm, and edge computing philosophy. And it just exploded on Hacker News.
For years, the industry moved away from monorepos toward microservices and smaller repositories. Recently, however, the conversation has started to shift again - and AI may be one of the reasons. As AI tools become part of everyday development workflows, the way engineers interact with large codebases is changing. Piotr Kukiełka shares his perspective on how large codebases work in practice and why AI might influence how companies think about monorepos.
Monorepo keeps coming up in conversations about large-scale software architecture. For some organizations, it’s a way to bring order to a growing ecosystem of applications. For others, it raises a lot of concerns. We spoke with Bartek Sądel, an expert who works with enterprise monorepos, about how this approach works in practice, what questions companies ask, and what the real benefits and challenges are.
