February 24, 2026
Keyboard warriors assemble
Code has always been the easy part
AI’s making code cheap — devs clap back: “Easy for who?”
TLDR: A tech lead says AI is making code cheap and reminds everyone the real battle is people and product, not typing. The crowd splits: some say AI speeds up thinking and resets the game, others argue coding still requires expertise—and wonder why it paid so much if it was ever “easy.”
A veteran Etsy leader says the quiet part out loud: code was never the hard part. With AI tools cranking out software faster and cheaper than ever, he argues the real challenge is people, process, and product—then drops a wry joke about “nice” old-school funders like the Department of Defense. Read the post here.
Cue the comment section meltdown. One camp cheers that AI isn’t just writing code—it’s shrinking thinking time too. “AI reduces the thinking time,” says one user, basically declaring the age of the turbo dev. Another fires back with the gatekeeping zinger of the day: it only works “to the person who knows how to code,” reminding everyone that tools don’t replace know-how. And then the existential angst hits: if code’s so “easy,” why were developers paid so much? Is the craft suddenly worthless, or are we just seeing what machines are good at and humans aren’t?
The hottest take: when building goes from months to minutes, everything else—product ideas, sales, design—gets forgiven because you can pivot on a dime. Translation: speed erases sins. Meanwhile, someone throws shade with the ultimate drive-by—“maybe you’re just working on a boring CRUD app”—and the crowd goes wild. It’s part therapy session, part roast, and fully 2026 tech drama.
Key Points
- •At Etsy, a two-year architectural rewrite produced no customer features until the team standardized on PHP, which unlocked progress.
- •The article argues code has long been the easier part of software; recent AI tools like Claude Code are rapidly driving code production costs toward near zero.
- •These AI advances are already changing team dynamics, making review burdensome and prompting rethinking of social contracts and collaboration.
- •Past technology waves (web, CI/CD, large-scale sites, mobile, SPAs, machine learning/data) similarly forced teams to reinvent workflows.
- •The author aims to creatively integrate humans into AI-accelerated development and notes skepticism due to AI hype and funding ethics.