Stop calling it vibe coding

Summary

Remember when Andrej Karpathy coined “vibe coding” a lifetime ago, back in February 2025? He nailed what that brand new moment felt like: you fully give in to the vibes, embrace exponentials, and forget that the code even exists. You don’t look at it; you just let it rip.For a lot of us, that’s exactly how we started. The term captured something real about those early days of handing trust to something that might hallucinate your entire authentication system (nbd).But a year of daily use changes things. The way most engineers I know actually work with these tools now—myself included—has evolved into something different. We’ve all collectively figured out what sustainable AI-assisted development looks like, and it turns out to be more structured than those early vibes.I’m looking at most every implementation. I’m catching the 1 out of 10 outputs that’s subtly wrong, the approach that will fall apart at scale, the pattern that doesn’t match how we think about the codebase. The amount of times I’ve had to redirect Claude Code away from an embarrassing PR and toward an approach that will hold up for years, I couldn’t count. That’s not vibes, it’s skilled supervision.James Ide put it well in a recent thread: LLMs accept imprecision and create imprecision. You need to already have a vision for the end state and use the LLM to automate getting there faster. Experts who understand a problem will be amplified in positive directions. Novices who trust LLMs will be amplified in negative directions, becoming confident in wrong solutions.This framing resonates with me. Everyone will use AI to write code, that’s not the question anymore. The question is whether you have the expertise to know when the output is wrong.Here’s what that looks like in practice: while writing this post, I asked Claude to build an interactive demo for this section. It created a “spot the bug” quiz—three code snippets, one with a subtle syntax error, click to reveal. Technically impressive. Completely mi...