Conductor by Melty Labs makes parallel agent workflows practical by running multiple agents with separate tasks simultaneously. The trade-offs are real but manageable, and this is where development is heading.
A couple of months ago, I was copy-pasting prompts into ChatGPT. Now I'm shipping features, running tests, managing branches, and keeping documentation alive, with a team of agents doing the heavy lifting. All by myself.
Legacy codebases are messy, undocumented, and full of decisions nobody remembers making. But if you can explain it to a new developer, you can onboard an AI and that changes everything.
Agile was supposed to free us from bureaucracy. Many teams just rebuilt it with better branding. Now, AI-driven development is forcing the uncomfortable question: Were we ever truly agile, or just managing slow feedback loops?
This is Part 2 of Bots and Boundaries, a three-part series on AI agents in open source.
AI made writing code faster, but the real economics of software engineering were never about typing code in the first place.
Founders juggle endless demands, investors, sales, suppliers, and employees, all while building the plane mid-flight. But with engineering often being your biggest expense, there's one responsibility you can't delegate: ensuring your team builds the right thing.
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.
AI won't make software engineers redundant. It will expose what engineering was always supposed to be about: understanding systems, not just writing code.