February 22, 2026
Perl flashbacks, quantum side‑eyes
Write-Only Code
AI code nobody reads? Devs argue, joke, and side‑eye
TLDR: A bold prediction says future software will be AI‑written and rarely read by humans, shifting engineers to risk and accountability roles. The crowd fought back: skeptics doubt adoption, veterans joke about Perl, and pragmatists say AI works only in low‑stakes areas—for now.
The hot claim: we’re racing toward “write‑only code”—software spat out by AI that no human ever reads line by line. Cue chaos in the comments. One camp is rolling its eyes at the hype, with philipwhiuk insisting adoption isn’t anywhere near the level to say “AI writes the code” across big companies. Old‑school devs chimed in with nostalgia and snark: jeffreygoesto had instant Perl flashbacks and called the whole thing an overblown extrapolation. Others took the “where it matters” angle: aatd86 says AI‑generated code will flourish in low‑risk corners, but today’s models can’t handle the strict, scalable logic real systems need.
Still, there’s a twist: svilen_dobrev dropped a 2005 throwback, describing a pipeline that auto‑generated mountains of code—proof that write‑once, read‑never isn’t new, just now upgraded with chatty AIs. The article itself argues humans won’t vanish; they’ll shift to owning outcomes, risk, and incidents, while the old SDLC (software development lifecycle) bottleneck—manual reviews—breaks. The community vibe? Split between “this is happening” and “calm down.” Jokes flew, nerves showed, and credit for the term went to LocalStack cofounder Waldemar Hummer. The meme of the day: “AI writes it, humans answer for it” in bold, slightly terrified font.
Key Points
- •The article introduces “Write-Only Code,” predicting a growing share of production code will not be read or reviewed by humans.
- •It claims human review has been the main bottleneck in AI-assisted development but is likely to disappear due to recent model capability improvements.
- •Emergent techniques enable AI agents to plan, execute, and self-correct, producing complex, working software at scale.
- •Humans remain essential for accountability, owning system outcomes, performance, and incident response.
- •The engineer’s role is reframed around risk reduction, requiring a fundamental rethink of culture, processes, and tools in the SDLC.