Born Against: why hobby programming communities are against LLM usage

An essay prompted by a chess engine thread

On August 4, 2026, the blogger known as Fogus published an essay titled “Born Against, or why hobby programming communities are aggressively against LLM usage.” The trigger was a GitHub thread about chess engine development, and the reaction it provoked toward developers who use large language models.

According to the author, the hostility is not limited to chess engines. He reports seeing similar sentiment in OSDev, LangDev, TxtDev, EmuDev, RLDev, the demoscene and among code golfers.

The process is the product

His explanation is that the knowledge in these communities is hard-fought. In most of them, mastering a difficult field is itself the point; something that runs is, in his words, a nice-to-have.

The essay describes how respect is normally earned slowly: years of activity on community forums, sharing elegant code, displays of genuine curiosity and deep domain knowledge. These communities, he writes, do not care much whether your code works at all — they care that you know why and how it works.

Why early engagement soured

Even where niche communities engaged earnestly with LLMs early on, Fogus writes that “the well was quickly poisoned” by two forces: practitioners who lacked deep understanding, and a vitriolic subset that views the LLM enterprise as a form of cheating. He notes that these groups have historically been characterized by gatekeeping and slow progress, which can tempt newcomers to grab easy cachet.

A lever, not a surrogate

His own position: an LLM functions best as a force multiplier rather than a surrogate — a lever in the hands of an expert who already understands the domain deeply. In communities where the whole exercise is learning, using a model to generate the finished piece “doesn't make us craftsmen; it just robs us of the craft.” He adds one caveat: expertise offers no natural immunity against being fooled by LLMs.

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