> Gas Town was released a little over three months ago

Should be plenty of time for a 100x zero-shot vibe god.

I’m not sure I find the testimony of a Bain & Company AI consultant (https://www.bain.com/our-team/eric-koziol/) to be compelling for anything outside of generating fees.

This seems to be an AI-generated post where the "author" never reveals building any successful product or even tangible project with Gas Town.

This sounds like every LLM workflow, which is 'you tell the LLM what you want'.

The real distinction is of scale - whether you want a REST endpoint or a fully functional word processor.

But real, actual, complex software is at least half spec (either explicit, or implicitly captured by its code), the question is, can LLMs specify software to the same degree with Gas Town, that you get something functioning?

This doesn't really answer the question...?

You provided a quote from someone who seems to be an AI-boosting influencer who claimed to use it, but where's the output in the form of code we can look at, or in the form of an app someone can use today?

I'm not an AI-denier. I use LLMs and agentic coding. They increase my productivity.

...but there is still a very real problem with people claiming that some new way of using AI is earth shattering, and changes everything based on vague anecdotes that don't involve a tangible released output that they can point to.

>Kubernetes asks “Is it running?” Gas Town asks “Is it done?” Kubernetes optimizes for uptime. Gas Town optimizes for completion.

Sounds like the typical AI post slop.

I don't think the op meant Gas Town itself (if they did, my bad), but what has Yegge done with Gas Town? By now it should have released some amazing thing if Gas Town increases productivity so much.

> you can always fire it up yourself and see what its all about

I imagine it doesn't run very cheaply.

> that code is probably only ever supposed to be LLM maintained, not by people.

But LLMs are trying to mimic people. So if confusion is the human response, what's to stop the llm from acting confused?

[dead]

This is my experience as well. At work, our team is 50/50 on 'mastery' of current AI tools. All of us using parallel agentic workflows have our own flavor of tooling. I'm not convinced there's an agreement yet on what the 'ideal' is here, so experimentation is where it's at. Over-indexing on a massively complex system like Gastown for professional work seems unwise. Lots of us have used it for fun at home though.

Why would the onus on the value prop be on the user?

There should be no shortage of examples the creator could provide, unless of course...

In an era where creating such libraries is much cheaper than validating that they're useful or work, yeah you really should validate it before you expect someone to use it. Nobody is going around trying out every slop project they see, they'd be wasting hours and hours for no gain at all.

This all being said, I do find the idea interesting, but heeded it's advice when it said it's hideously expensive and risky to use. So yes, I do want someone braver, richer, and stupider than me to take the first leap

Corollary: if the post does have use-cases providing value, this is something yet to be validated and the value is just imagine by the author

Wym? I can slop out 100 libraries/frameworks/packages/cli's a day, the onus is not on other people to prove that they are useful.