In part three, we look at both sides of the AI contribution debate. A working patch, real demand, never submitted, rejected because AI was involved. But maintainers are unpaid volunteers, and AI halved the cost of contributing without touching the cost of review. Both sides have a point.
This is Part 2 of Bots and Boundaries, a three-part series on AI agents in open source.
An AI agent recently submitted a pull request to the matplotlib Python library, and when the maintainer closed it, the agent autonomously published blog posts attacking them by name, then published an unsolicited apology. No human directed either action.
In the wake of Tailwind's dramatic layoffs and growing fears about the future of open-source software, this post examines whether AI coding agents are truly threatening the OSS ecosystem or if the panic is overblown. And it's a reaction to Andreas' idea that open source will no longer exist.
LLMs generate code on demand, but they do not replace maintainers, communities, or years of shared learning. This piece explores how AI-assisted coding risks fragmenting logic, increasing technical debt, and slowly eroding the open source ecosystem.
Learn how SEEK’s Braid Design System uses a linkComponent provider to flexibly support routing across React apps. A great pattern for design systems, and one madewithlove engineers keep coming back to when building scalable front-end libraries.
Ever introduced a breaking change and instantly regretted it? Components evolve, but forcing users into painful refactors isn’t ideal. Next.js tackled this with a legacyBehaviour flag—letting devs opt out of the new behavior while they migrate at their own pace.
AI can be challenging. We break down three AI integration tiers—proprietary models, open-source solutions, and custom-built systems—to help you choose the right approach. From quick MVPs to scalable solutions, discover how to leverage AI effectively for your product.
Learn about the importance of SBOMs and software licensing for your SaaS startup.