YC-Backed Startups Were “Vibe Coding Crap” Way Before LLMs — Here’s What It Means for SWEs

• Y Combinator startups reportedly practiced "vibe coding" long before AI tools arrived
• AI now writes 95% of code for 25% of YC startups according to recent reports
• Software engineers face new challenges as low-quality code generation becomes mainstream

The revelation that Y Combinator startups were producing questionable code quality before AI entered the scene adds an amusing twist to current debates about AI-generated programming. While everyone's busy panicking about robots writing bad code, it turns out humans were already doing a pretty stellar job of that themselves. This historical context suggests the current AI coding crisis might be less about artificial intelligence corrupting pure programming practices and more about amplifying existing shortcuts that startups were already taking.

For software engineers, this creates a peculiar professional landscape where distinguishing between human-generated mediocrity and AI-generated mediocrity becomes increasingly difficult. The fact that 25% of YC startups now rely on AI for 95% of their code suggests we're witnessing an acceleration of existing trends rather than a fundamental shift in startup culture. Engineers who previously competed against rushed human coding now face the additional challenge of standing out in a market flooded with algorithmically generated solutions that prioritize speed over craftsmanship.

The broader implications extend beyond individual career concerns to the entire startup ecosystem's relationship with technical debt. If startups were already cutting corners on code quality in pursuit of rapid growth, AI tools may simply be the latest instrument in an ongoing symphony of strategic technical compromises. This raises questions about whether the industry's focus should shift from preventing AI adoption to establishing better standards for code quality regardless of its origin. The challenge isn't necessarily stopping the robots from coding badly, but rather teaching everyone involved to code better in the first place.