Here is a disturbing look at what the absolute knobs at Y Combinator (and elsewhere) are preaching/pushing, with commentary from Primeagen: https://www.youtube.com/watch?v=riyh_CIshTs
Watch the whole thing, it's hilarious. Eventually these venture capitalists are forced to acknowledge that LLM-dependent developers do not develop an understanding and hit a ceiling. They call it "good enough".
The use of LLMs for constructive activities (writing, coding, etc.) rapidly produces a profound dependence. Try turning it off for a day or two, you're hobbled, incapacitated. Competition in the workplace forces us down this road to being utterly dependent. Human intellect atrophies through disuse. More discussion of this effect, empirical observations: https://www.youtube.com/watch?v=cQNyYx2fZXw
To understand the reality of LLM code generators in practice, Primeagen and Casey Muratori carefully review the output of a state-of-the-art LLM code generator. They provide a task well-represented in the LLM's training data, so development should be easy. The task is presented as a cumulative series of modifications to a codebase: https://www.youtube.com/watch?v=NW6PhVdq9R8
This is the reality of what's happening: iterative development converging on subtly or grossly incorrect, overcomplicated, unmaintainable code, with the LLM increasingly unable to make progress. And the human, where does he end up?
But this is exactly what the higher ups want according to Braverman, they will insist on "know-how" being non-existent, and always push to tell workers what they - of course - know of the work, that we peons would ignore.
Watch the whole thing, it's hilarious. Eventually these venture capitalists are forced to acknowledge that LLM-dependent developers do not develop an understanding and hit a ceiling. They call it "good enough".
The use of LLMs for constructive activities (writing, coding, etc.) rapidly produces a profound dependence. Try turning it off for a day or two, you're hobbled, incapacitated. Competition in the workplace forces us down this road to being utterly dependent. Human intellect atrophies through disuse. More discussion of this effect, empirical observations: https://www.youtube.com/watch?v=cQNyYx2fZXw
To understand the reality of LLM code generators in practice, Primeagen and Casey Muratori carefully review the output of a state-of-the-art LLM code generator. They provide a task well-represented in the LLM's training data, so development should be easy. The task is presented as a cumulative series of modifications to a codebase: https://www.youtube.com/watch?v=NW6PhVdq9R8
This is the reality of what's happening: iterative development converging on subtly or grossly incorrect, overcomplicated, unmaintainable code, with the LLM increasingly unable to make progress. And the human, where does he end up?