Good analogy, but there's a key difference: mainframes were an institutional dependency, whereas the world's reliance on LLMs is consumer driven, ubiquitous, an uncapped (e.g. spend more on the same "loops"). Completely agree on the second point, though powerful local models are the inevitable next step, and they are arriving fast.
gemma4 and qwen3.6 are pretty capable but will be slower and wrong more often than the larger models. But you can connect gemma4 to opencode via ollama and it.. works! it really can write and analyze code. It's just slow. You need serious hardware to run these fast, and even then, they're too small to beat the "frontier" models right now. But it's early days
If the apple silicon keeps making the gains it makes, a mac studio with 128gb of ram + local models will be a practical all-local workflow by say 2028 or 2030. OpenAI and Anthropic are going to have to offer something really incredible if they want to keep subscription revenue from software developers in the near future, imo
does your table saw build you a bookshelf by itself? and then you build other things and get confident in it and say: ok build me a house and it tries but then the house falls over?
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