Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech. Subscribe for daily updates.
As someone that works in tech, this doesn’t really surprise me at all.
Stuff like Claude Code is very useful to me both professionally and sometimes with tech hobby projects. But outside of that it is just a worse, albeit faster, version of a standard web search.
The problem is, the places where it could be the most effective are places where we already have processes in place, like the medical field and engineering.
I’m sure LLMs are helping sift through ideas in those fields, but they don’t reduce the amount of work that needs to be done by actual people to produce actual results; they just help select the best potential new idea.
Most stuff in life is already solved, and so AI can’t contribute there.
I work in tech and the biggest use case for AI for me is searching for information about the codebase. Essentially a fuzzy search and finding related information (ex: how does X service do Y operation).
I find if I use it for coding tasks it frequently does a worse job and ultimately slower than me doing it myself. But I also have over a decade of experience just in the language I’m using. Sometimes I use it to write a shell script of repetitive work, or writing some unit tests, but rarely larger more complex things. I really try to avoid using it for things that I can do myself in vim or whatnot because of the environmental impact that a LLM has.
As someone that works in tech, this doesn’t really surprise me at all.
Stuff like Claude Code is very useful to me both professionally and sometimes with tech hobby projects. But outside of that it is just a worse, albeit faster, version of a standard web search.
The problem is, the places where it could be the most effective are places where we already have processes in place, like the medical field and engineering.
I’m sure LLMs are helping sift through ideas in those fields, but they don’t reduce the amount of work that needs to be done by actual people to produce actual results; they just help select the best potential new idea.
Most stuff in life is already solved, and so AI can’t contribute there.
I work in tech and the biggest use case for AI for me is searching for information about the codebase. Essentially a fuzzy search and finding related information (ex: how does X service do Y operation).
I find if I use it for coding tasks it frequently does a worse job and ultimately slower than me doing it myself. But I also have over a decade of experience just in the language I’m using. Sometimes I use it to write a shell script of repetitive work, or writing some unit tests, but rarely larger more complex things. I really try to avoid using it for things that I can do myself in vim or whatnot because of the environmental impact that a LLM has.
– Diogenes, probably