> The reality is it's insanely hard to convince people (/especially/ consumers. //especially// technical consumers) to pay up to use software.

The industry is in an extremely bimodal situation, which drives most of that rot.

You have the startups and small businesses who can't get businesses or customers to pay up. And you have the SaaS giants, who already have their customers and can charge whatever they want.

And this is where the "rotten software industry" and doubts about AI feasibility intersect: Both of these business archetypes lack a clear use case for AI.

If you're small, congratulations you can now spend thousands a month on tokens and still have $0 of revenue. AI doesn't really help you "catch up" to customer expectations as now you're also having to compete with the myriad of slop-shops and in-house AI software development.

If you're a giant, well... why bother? Why give OpenAI or Anthropic a million dollars in tokens? They don't need to make the software better nor do need any "AI efficiency" to do layoffs.

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vanuatu 4 hours ago | parent [-]

I'm curious as to where your perspective comes from.

My view is they both have a clear use case for AI, because every business has a use case for more intelligence on tap. Enterprises big and small already shell out billions upon billions for AI so I'm not sure how your premise holds

In fact AI has resulted in more startups than ever starting to take market share from the incumbent software companies (and the market has started to price that in)

	▲	bigyabai 3 hours ago \| parent \| next [-]
		> Enterprises big and small already shell out billions upon billions for AI so I'm not sure how your premise holds By your logic, shouldn't these enterprise's cash flow be expanding due to AI instead of shrinking?
	▲	bigstrat2003 3 hours ago \| parent \| prev \| next [-]
		Every business has a use case for more intelligence on tap, but it is abundantly clear that LLMs are not in any way intelligent. They still frequently make egregious errors in what they do, because they are just token predictors with no intelligence or understanding of what they are doing. Yes, even the state of the art frontier models. This in turn means you have to either baby sit them, or accept a much higher rate of failures than a human would produce. Either option kills any potential productivity gains.
	▲	pessimizer 2 hours ago \| parent \| prev [-]
		> My view is they both have a clear use case for AI, because every business has a use case for more intelligence on tap. They all do, but for small companies it won't be a benefit, it will be table stakes. It will also not increase revenue for them, it will reduce it because more competitors will be introduced, and customers won't be able to easily differentiate the true slop from the expert-guided and curated slop. The only alternative will be to become more of a slop shop, i.e. replace expensive programmers with cheaper AI, lowering your quality. Or to shut down. For big companies who have always had terrible quality that didn't matter at all to their bottom line, of course it's a good investment. They can fire programmers. Do buybacks.