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One option that didn't seem to be discussed in TFA is turning away from AI. There's an implicit assumption in the article that the coding models are here to st

One option that didn't seem to be discussed in TFA is turning away from AI. There's an implicit assumption in the article that the coding models are here to stay in development. It's possible that assumption is incorrect for multiple reasons. Maybe (as some research indicates) the models are as good as they are going to get. They're always going to be a cross between a chipper stochastic parrot and that ego inflated junior dev that refuses to admit a mistake. Maybe when the real (non-subsidized) economics present themselves, the benefit isn't there. Perhaps the industry segments itself to a degree. There's a big difference in tolerance for errors in a cat fart app and a nuclear cooling system. I can see a role for certified 100% AI free development. Maybe vibe coders go in one direction, with lower quality output but rapid TTM, but a segment of more highly skilled developers focus on AI free development. I also think it's possible that over time the AI hyper-productivity stuff is revealed to be mostly a mirage. My personal experience and a few studies seem to indicate this. The purported productivity boost is a result of confirmation bias and ridiculous metrics (like LOC generated) that have little to do with actual value creation. When the mirage fades, companies realize they are stuck with heaps of AI slop and no technical talent able to deal with it. A bitter lesson indeed. Since we're reading tea leaves, I think the most likely outcome is that the massive central models for code generation fade due to enormous costs and increased endpoint device capabilities. The past 50 years have shown us clearly that computing will always distribute, and centralized mainframe style compute gets pushed down to powerful local devices. I think it settles at an improved intellisense running locally. The real value of the "better search engine" that LLMs hold today reduces as hard economics drive up subscription fees and content is manipulated by sponsors (same thing that happened to the Google search results). For end users, I think the models get shoved into a box to do things they're really good at, like giving a much more intuitive human-computer interface, but structured data from that is handed off to a human developer to reason about, MCP will expand and become the glue. I think that over time market forces will balance between AI and human created content, with a premium placed on the latter. McDonalds vs a 5 star steakhouse.

godshatter 9mo ago
>Maybe (as some research indicates) the models are as good as they are going to get. They're always going to be a cross between a chipper stochastic parrot and that ego inflated junior dev that refuses to admit a mistake. Maybe when the real (non-subsidized) economics present themselves, the benefit isn't there. I'd put my money on this. From my understanding of LLMs, they are basically mashing words together via markov chains and have added a little bit of subject classification with attention, a little bit of short-term memory, and enough grammar to lay things out correctly. They don't understand anything they are saying, they are not learning facts and trying to build connections between them, they are not learning from their conversations with people. They aren't even running the equivalent of a game loop where they can even think about things. I would expect something we're trying to call an AI to call you up sometimes and ask you questions. Trillions of dollars have got us this far, how far can it actually take us? I want my actual AI personal assistant that I have to coerce somehow into doing something for me like an emo teen.
rcxdude 9mo ago
Assuming AI is at all useful it's likely to be used for safety-critical software development. Safety-critical processes aren't likely to care about LLM involvement much at all, much like they don't generally care about competence of those doing the work already.

godshatter 9mo ago

>Maybe (as some research indicates) the models are as good as they are going to get. They're always going to be a cross between a chipper stochastic parrot and that ego inflated junior dev that refuses to admit a mistake. Maybe when the real (non-subsidized) economics present themselves, the benefit isn't there. I'd put my money on this. From my understanding of LLMs, they are basically mashing words together via markov chains and have added a little bit of subject classification with attention, a little bit of short-term memory, and enough grammar to lay things out correctly. They don't understand anything they are saying, they are not learning facts and trying to build connections between them, they are not learning from their conversations with people. They aren't even running the equivalent of a game loop where they can even think about things. I would expect something we're trying to call an AI to call you up sometimes and ask you questions. Trillions of dollars have got us this far, how far can it actually take us? I want my actual AI personal assistant that I have to coerce somehow into doing something for me like an emo teen.

rcxdude 9mo ago

Assuming AI is at all useful it's likely to be used for safety-critical software development. Safety-critical processes aren't likely to care about LLM involvement much at all, much like they don't generally care about competence of those doing the work already.