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Re:Evaluating AGENTS.md: are they helpful for coding agents? by troupo on Tuesday February 17, 2026 @03:22AM (#47044970)
To reduce the number of variables to account for. To be able to finish the paper this year, and not the next century. To work with a familiar language and environments. To use a language heavily represented in the training data.

I mean, it's not that hard to understand why.

Re:Evaluating AGENTS.md: are they helpful for coding agents? by menaerus on Tuesday February 17, 2026 @03:27AM (#47045002)
Before you make such a stupid and uninformed comment without substance please learn something about how research is conducted and how distribution can skew the definition of "generalization".
Re:Evaluating AGENTS.md: are they helpful for coding agents? by troupo on Tuesday February 17, 2026 @05:42AM (#47045909)
All research is conducted in constraints. It's not hard to understand those constraints by simply thinking.

Besides, one could actually open the research, and scroll to section 5 where they acknowledge the need to expand beyond Python:

--- start quote ---

5. Limitations and Future Work

While our work addresses important shortcomings in the literature, exciting opportunities for future research remain.

# Niche programming languages

The current evaluation is focused heavily on Python. Since this is a language that is widely represented in the training data, much detailed knowledge about tooling, dependencies, and other repository specifics might be present in the models’ parametric knowledge, nullifying the effect of context files. Future work may investigate the effect of context files on more niche programming languages and toolchains that are less represented in the training data, and known to be more difficult for LLMs

--- end quote ---

Re:Evaluating AGENTS.md: are they helpful for coding agents? by menaerus on Tuesday February 17, 2026 @11:08AM (#47049047)
You still did not answer my question and you're still being a d*ck. I understand now why - because you have no idea what I am talking about.