Much Ado About Vibe Coding
Lauren Goode convinced her editors at Wired to let her spend a couple of days at a tech company called Notion learning how to vibe-code (i.e. AI-assisted computer programming): Why Did a $10 Billion Startup Let Me Vibe-Code for Them — and Why Did I Love It?
Expanding a mermaid diagram or alphabetizing a list of dog breeds hardly seemed like sticking it to the coding man. But during my time at Notion I did feel as though a trapdoor in my brain had opened. I had gotten a shimmery glimpse of what it’s like to be an anonymous logical god, pulling levers. I also felt capable of learning something new — and had the freedom to be bad at something new — in a semi-private space.
Both vibe coding and journalism are an exercise in prodding, and in procurement: Can you say more about this? Can you elaborate on that? Can you show me the documents? With our fellow humans, we can tolerate a bit of imprecision in our conversations. If my stint as a vibe coder underscored anything, it’s that the AIs coding for us demand that we articulate exactly what we want.
During lunch on one of my days at Notion, an engineer asked me if I ever use ChatGPT to write my articles for me. It’s a question I’ve heard more than once this summer. “Never,” I told her, and her eyes widened. I tried to explain why — that it’s a matter of principle and not a statement on whether an AI can cobble together passable writing. I decided not to get into how changes to search engines, and those little AI summaries dotting the information landscape, have tanked the web traffic going to news sites. Almost everyone I know is worried about their jobs.
One engineer at Notion compared the economic panic of this AI era to when the compiler was first introduced. The idea that one person will suddenly do the work of 100 programmers should be inverted, he said; instead, every programmer will be 100 times as productive. His manager agreed: “Yeah, as a manager I would say, like— everybody’s just doing more,” she said. Another engineer told me that solving huge problems still demands collaboration, interrogation, and planning. Vibe coding, he asserted, mostly comes in handy when people are rapidly prototyping new features.
These engineers seemed reasonably assured that humans will remain in the loop, even as they drew caricatures of the future coder (“100 times as productive”). I tend to believe this, too, and that people with incredibly specialized skills or subject-matter expertise will still be in demand in a lot of workplaces. I want it to be true, anyway.
A very interesting read. Over the past several months, I have been reading a lot about LLMs and coding, particularly pieces by experienced coders who have switched to using LLMs to code. There is a lot of silly (and perhaps dangerous) hype around AI, but over the past several months, LLMs and supporting tools have gotten unnaturally good at programming, when directed properly. Here are some of the things I’ve read recently in case you’re curious about what’s possible now:
- My LLM codegen workflow atm
- Waterfall in 15 Minutes or Your Money Back
- An LLM Codegen Hero’s Journey
- Basic Claude Code
- How I Use Claude Code
- Amp Is Now Available. Here Is How I Use It.
- Claude Code is My Computer
- Claude Code Experience
- Stevens: a hackable AI assistant using a single SQLite table and a handful of cron jobs
- As an Experienced LLM User, I Actually Don’t Use Generative LLMs Often
- AI Changes Everything
- Agentic Coding Recommendations
- Become an AI-augmented engineer
- Using the plan/execute cycle with agentic LLMs
- Baby steps into semi-automatic coding
- Vibe Coding and The Illusion of Progress
I’m curious to know if any experienced (or inexperienced) coders among you have tried any of the recent suite of AI-assisted coding tools and what your experience has been. (Your general thoughts about AI — particularly its potential downsides, which have been amply documented elsewhere — are best left for some other time & place. Thx.)
Tags: artificial intelligence · Lauren Goode · programming
Lauren Goode convinced her editors at Wired to let her spend a couple of days at a tech company called Notion learning how to vibe-code (i.e. AI-assisted computer programming): Why Did a $10 Billion Startup Let Me Vibe-Code for Them — and Why Did I Love It?
Expanding a mermaid diagram or alphabetizing a list of dog breeds hardly seemed like sticking it to the coding man. But during my time at Notion I did feel as though a trapdoor in my brain had opened. I had gotten a shimmery glimpse of what it’s like to be an anonymous logical god, pulling levers. I also felt capable of learning something new — and had the freedom to be bad at something new — in a semi-private space.
Both vibe coding and journalism are an exercise in prodding, and in procurement: Can you say more about this? Can you elaborate on that? Can you show me the documents? With our fellow humans, we can tolerate a bit of imprecision in our conversations. If my stint as a vibe coder underscored anything, it’s that the AIs coding for us demand that we articulate exactly what we want.
During lunch on one of my days at Notion, an engineer asked me if I ever use ChatGPT to write my articles for me. It’s a question I’ve heard more than once this summer. “Never,” I told her, and her eyes widened. I tried to explain why — that it’s a matter of principle and not a statement on whether an AI can cobble together passable writing. I decided not to get into how changes to search engines, and those little AI summaries dotting the information landscape, have tanked the web traffic going to news sites. Almost everyone I know is worried about their jobs.
One engineer at Notion compared the economic panic of this AI era to when the compiler was first introduced. The idea that one person will suddenly do the work of 100 programmers should be inverted, he said; instead, every programmer will be 100 times as productive. His manager agreed: “Yeah, as a manager I would say, like— everybody’s just doing more,” she said. Another engineer told me that solving huge problems still demands collaboration, interrogation, and planning. Vibe coding, he asserted, mostly comes in handy when people are rapidly prototyping new features.
These engineers seemed reasonably assured that humans will remain in the loop, even as they drew caricatures of the future coder (“100 times as productive”). I tend to believe this, too, and that people with incredibly specialized skills or subject-matter expertise will still be in demand in a lot of workplaces. I want it to be true, anyway.
A very interesting read. Over the past several months, I have been reading a lot about LLMs and coding, particularly pieces by experienced coders who have switched to using LLMs to code. There is a lot of silly (and perhaps dangerous) hype around AI, but over the past several months, LLMs and supporting tools have gotten unnaturally good at programming, when directed properly. Here are some of the things I’ve read recently in case you’re curious about what’s possible now:
- My LLM codegen workflow atm
- Waterfall in 15 Minutes or Your Money Back
- An LLM Codegen Hero’s Journey
- Basic Claude Code
- How I Use Claude Code
- Amp Is Now Available. Here Is How I Use It.
- Claude Code is My Computer
- Claude Code Experience
- Stevens: a hackable AI assistant using a single SQLite table and a handful of cron jobs
- As an Experienced LLM User, I Actually Don’t Use Generative LLMs Often
- AI Changes Everything
- Agentic Coding Recommendations
- Become an AI-augmented engineer
- Using the plan/execute cycle with agentic LLMs
- Baby steps into semi-automatic coding
- Vibe Coding and The Illusion of Progress
I’m curious to know if any experienced (or inexperienced) coders among you have tried any of the recent suite of AI-assisted coding tools and what your experience has been. (Your general thoughts about AI — particularly its potential downsides, which have been amply documented elsewhere — are best left for some other time & place. Thx.)
Tags: artificial intelligence · Lauren Goode · programming
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