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enriquto • today at 1:55 PM • 1 reply • view on HN

> because of the stochastic nature of LLMs.

But is this "stochastic nature" inherent to the LLM? Can't you make the outputs deterministic by specifying a version of the weights and a seed for the random number generator?

Your vibe coding log (i.e. your source code) may start like this:

    fix weights as of 18-1-2026
    set rng seed to 42

    write a program that prints hello world
Notice that the first two lines may be added automatically by the system and you don't need to write or even see them.

Replies

neomantra • today at 2:41 PM

I see what you are saying, and perhaps we are zeroing in on the importance of ground truths (even if it is not code but rather PLANs or other docs).

For what you're saying to work, then the LLM must adhere consistently to that initial prompt. Different LLMs and the same LLM on different runs might have different adherence and how does it evolve from there? Meaning at playback of prompt #33, will the ground truth gonna be the same and the next result the same as in the first attempt?

If this is local LLM and we control all the context, then we can control that LLM's seeds and thus get consistent output. So I think your idea would work well there.

I've not started keeping thinking traces, as I'm mostly interested in how humans are using this tech. But, that could get involved in this as well, helping other LLMs understand what happened with a project up to a state.