I Didn’t Become a Developer to Review AI Slop: The True Cost of "Almost Right" PRs

Kenneth Macharia — Sun, 31 May 2026 08:38:09 +0000

The barrier to writing code has completely vanished with modern AI agents spinning up massive repository branches from a single prompt, but engineering teams are quickly realizing that writing lines of code and building scalable, trustworthy architecture are two entirely different things. Recent industry data shows that AI-generated pull requests sit waiting for review over four times longer and face massive rejection rates because while automated tools are brilliant at quick syntax, they are terrible at context—often passing basic local tests while silently violating end-to-end type safety and injecting technical debt that haunts a codebase for months. Most production crashes happen when the client frontend makes an assumption about data that the backend server or the database didn't actually fulfill, and if senior engineers have to manually patch these hallucinations every single time an automated assistant pushes a branch, they spend all day reviewing junk instead of shipping features. The modern invention that completely fixes this bottleneck is a strict architectural shift toward a unified schema layer using Next.js Server Functions paired with type-safe database engines like Supabase, which forces the frontend and backend to read from a single source of truth and creates a compilation-level brick wall that automatically fails a build before a human reviewer ever has to waste time opening the code panel.

DEV Community: Kenneth Macharia

I Didn’t Become a Developer to Review AI Slop: The True Cost of "Almost Right" PRs