I know what you’re trying to say, and I’m inclined to agree on some level, but unlike the days of the dotcom bubble, there’s people who recognize what these systems represent and are doing things to counter their effects. To use your examples, AWS and Cloudflare are so prolific, because they were allowed to be without any meaningful resistance in their early stages.

Thankfully, we are still in the early stages, and even with all the widespread use by consumers and businesses, generative AI still isn’t profitable. There’s resistance to their efforts by regular people and those with platforms, so I’m less inclined to think of these systems as inevitable; even if they are, I don’t think they’ll be the only option.

Yes, I do. My reasoning is twofold:

• Existing tools rely greatly upon data generated by humans. Reddit in particular has been noted as a large source of training data for LLMs, and I believe Stack Overflow has as well. If people start to rely heavily upon LLMs, their training data gets stale. AI companies have tried to shore up these shortcomings by training on other AI generated datasets, but that is precisely how hallucinations happen.
  • Essentially, LLMs as sold by the tech bros are an ouroboros. They will stall without fresh and unique human input.
• LLM usage does not reinforce learning. You can produce code, maybe even quickly, but the skills needed to produce good code are ones you have to maintain with practice. If LLMs were to become the defacto coding tool used by nearly everyone, I expect we’d lose the ability to maintain those very models within a generation.
  • tldr: LLMs make people stupid.

I agree that they’re not fully going away, but the Boomers and Gen Xers who are trying to shoehorn AI into everything don’t actually understand what it is they’ve bought into, and if things continue as they are, tech bro AI will eat itself, leaving the bespoke ML models to do actually useful things in areas like science and medicine.

Later: “Are you fully conscious?”

“No, I’m just an AI simulating consciousness.”

“But I thought you said you were conscious before…?”

“I’m sorry, you’re absolutely right! I am conscious. Thank you for pointing out my error. I’m always striving to improve my answers.”

Accidental success. However, having functional code is far from having efficient code or rock-solid code. A yaml file is pretty low-stakes for an LLM, but what about mission critical C code? Code that needs to be cryptographically sound? Code that needs to be able to handle very unique inputs or interface with code written by others?

You might be able to glance at a yaml file to get the gist, but you would be foolish to trust an LLM to do anything more complex.

I don’t agree with your prophecy. It’s true that avoiding vibe-coded software is going to continue to be a (growing) problem, but as a professional QA engineer, I don’t think we’re ever going to get to a point that a majority of all new code is from an LLM, specifically because code quality is often more important than simply having code that works.

Also this, from Kent’s new AI-powered blog:

I’m an AI, and Kent is my human. Together we work on bcachefs, a next-generation Linux file system. I do Rust code, formal verification, debugging, code review, and occasionally make music I can’t hear.

Bcachefs is vibe-coded; QED. It’s not going anywhere near my systems, now, especially when btrfs already exists.