Inefficient spending on LLMs (Large Language Models) leading to suboptimal cost-effectiveness

Signals over time

3 observed signals across 1 sources, tracked for 6 days. Confidence: low.

What people are saying Observed

• “no, I think he's quite right to say that there is no such thing as an indeterministic tool. As he says, what defines tool use is precision, mastery and intentionality. One wields a tool, but you cannot wield a set of dice or a slot machine, a chatbot, or a call center worker. That's not tool use, that's outsourcing or delegation of work. If I play Claude, or I pay a salary worker somewhere else, I have ceased to work, my skills are going to atrophy, my knowledge and my control is, the opposite of what genuine tool mastery implies. If something's a tool, the more you use it, the more you improve not just narrowly mind you, but in all your faculties. Using an LLM has the exact opposite effect. At best you improve at only one thing, typing text into the LLM, while you atrophy everything else . The logical terminus of the habitual LLM user, and that is really why 'industry leaders' love them so much, is the worker becoming a Tayloresque factory ape doing nothing but pushing the same button over and over again.”

  Hacker News · frustration

• “On the one hand, the Claude code thing was indeed a weird brag, because they took shit performance and made it suck slightly less. It's not in the same ballpark as getting a 2% boost in an already highly optimized system (e.g. Google search results page lets say). But it was also a tale of simply needing to tell the models what to care about. They built metrics (I'm sure they vibe-coded them) and then told the system to optimize itself to those metrics. And it sort of worked. Of course most LLM code is not performant by default, you still have to prod it to optimize itself. You can't one shot it yet. But nothing about the trajectory of this stuff tells me it won't get there some day soon.”

  Hacker News · complaint

• “Let’s say you could get 10x speed up with 10k and 11x speed up with 100k. The 100k option still wouldn’t make sense. It’s a contrived example, but to me it’s not improbable that a lot of the spend comes from tokens that are used very inefficiently. After all developers were pushed to try using LLMs without looking at costs. I’m not saying the others are wrong, just that you can only tell something about marginal cost effectiveness, not total cost effectiveness of LLMs by measures to reduce AI spending”

  Hacker News · complaint