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.
We smile at the 18th-century crowd for being swept up by a box with a man inside, yet today it's easy to hand ChatGPT a vague idea and treat the PRD it returns as gospel. Generative AI is genuinely powerful. We get the best from it when we bring both enthusiasm and a critical eye.
The machines aren't replacing developers, they're promoting them. You're no longer just writing code; you're managing agents, reviewing output, and setting standards. Three Claudes walk into a codebase, and suddenly you're a manager.
Managing multiple Claude Code accounts across machines gets messy fast. Jean-Claude keeps the useful parts in sync, separates account-specific config, and makes switching between personal, team, and client setups far less painful.
Last week, we deleted 16,000 lines of code, rewrote 11,500, migrated frameworks, ripped out React, and swapped our entire CSS setup with AI. It took less than 6 hours.
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.
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.