alt Hacker NewsI'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)
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> 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?
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.
> 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.
> because every business has a use case for more intelligence on tap.
This is the part I would contest.
Obviously there's some disagreement about how much AI is actually meaningfully intelligent for any given task, but even outside of that:
Turning "intelligence" or staff skill into revenue is not automatic or trivial. You can hire the smartest process engineer on the planet, but if your assembly line has no major inefficiencies, they just can't do anything. They can build you a 2nd assembly line but if there's not the market demand to buy that much product, it's pointless.
For software development: "More code" does not really translate into "more revenue".
If you are a SaaS giant, you don't need "More code". You're not in the business of doing software development. You're in the business of rent seeking. No need to replace people with AI, you can just fire them and replace them with nobody.
And if you're a small firm, code isn't your USP. Everyone has code. Good god especially now with AI, every dumbass' startup can have a trillion lines of code. As has oft been observed (long before AI), the code is a liability. There's not really much efficiency to be had by using AI, because the devs are already minimally writing code.