LLMs, Vibe-Coding, and Where I Draw the Line

I have been orbiting the LLM and GenAI world for a while, reading the hot takes, watching the demos, and, yes, using these models almost every day. It is everywhere, on every timeline, in every meeting. But if you ask whether I let an LLM “vibe-code” my work, that is a hard no.

Do not get me wrong. LLMs are genuinely helpful. I lean on them for all sorts of things. They are fantastic for summarizing dense documents, helping me grasp new concepts, brainstorming approaches, and debugging through bugs. Sometimes, I will toss a codebase at an LLM and ask it to explain the architecture, or I will use it to double-check my code. For all that, these tools are genuinely helpful. It’s like having a supercharged Stack Overflow and a patient if occasionally hallucinating, coworker on tap.

But when it comes to actually writing production code for me, that is where I draw the line. The “vibe-coding” experience, where the LLM generates code that appears plausible but is often overly complicated, subtly incorrect, or just plain weird, does not work for me. I have seen it spit out walls of code that solve the wrong problem or introduce bugs that are a nightmare to debug. Sometimes, it feels like the AI is trying to impress me with volume instead of clarity. Honestly, it can feel like it is charging by the token.

The community shares these sentiments. The memes serve as a collective nod of understanding:

• “Tell me you charge by the token without telling me you charge by the token.”
• “You are absolutely right!” (AI-speak for “I have no idea what you are talking about, but here are 200 lines of code anyway.”)
• The “Rick Rubin Headphones” meme, where the dev just vibes while the AI does the work.
• “Vibe-coding is like vibe-cooking. Sometimes you get a meal, sometimes you get food poisoning.”
• The “Desert Dilemma” meme: vibe-coding is easy, debugging is a nightmare.

These are not just memes. They are real pain points and a reflection of the skepticism and humor in the community. It is funny, but it is also a real productivity trap. I do not want to spend my day reviewing and rewriting code that was supposed to save me time.

My Approach

What I actually want from these tools is support, not autopilot. I want to learn faster, understand more deeply, and receive a nudge when I’m stuck. I want to analyze a new library, not have the AI build it for me from scratch. I want a second set of eyes, not a ghostwriter.

Here is where I draw the line. I use LLMs for learning, research, brainstorming, and code review. I do not let LLMs write production code for me or trust AI-generated code without a thorough review and verification. Vibe-coding is fine for prototypes but not for the real thing. I want to understand, trust, and maintain my code.

There is a lot of hype about LLMs replacing programmers, but the real value is in augmentation, not automation. The best moments I have had with LLMs are when they help me see something I missed or explain a tricky concept in a new way, not when they try to take over the project.

So yes, I use LLMs. But I am not here for the vibe-coding. I am here for the learning, the rubber ducking, and the occasional ‘aha’ moment. The rest, I will write myself, thanks.

And, as always, take all this with a grain of salt. The tech, the memes, and even my own opinions are all evolving.