alt Hacker News"Ride the wave."
Or don't.
Most LLMs people are using to code are paywalled, and controlled by private, for-profit entities.
This is fundamentally different than the past, and diametrically opposed to the hacker.
If you're a hacker, which most of you are not (things have changed here over time), you will reject this.
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Even with locally runnable small "open" models you are relying on scraps of others. They are much worse at the LLM game and you don't know when they stop releasing the weights.
How can you go the opposite direction? Instead of using LLMs to produce more code, can you produce less, maybe higher abstraction code?
If you're a hacker, which most of you are not (things have changed here over time), you will reject this.
You'll also recognize that the problem is not AI in general or LLMs in particular, but the proprietary entities that control the best models.
That's the part HN'ers seem to have the most trouble with. They protest AI qua AI, as if that's somehow going to help, when they should be fighting for independent development and universal access.
You can accomplish quite a lot with smaller local models on reasonably priced pro tier hardware (not cheap hardware, but very attainable hardware for anyone making average software engineer money). Qwen 3.6 27B and 35BA3, Gemma 28B, and so on are incredibly beneficial even if Anthropic and OpenAI produce better options.
Failing that, GLM 5.2 is open weights, trades blows with current frontier models and widely available on commodity inference providers. And you could run it yourself if you do actually have the resources.