Comment by zerof1l

> ... that these "reasoning" models can often produce incoherent, logically unsound answers when questions include irrelevant clauses or deviate even slightly from common templates found in their training data.

I have encountered this problem numerous times, now. It really makes me believe that the models do not really understand the topic, even the basics but just try to predict the text.

One recent example was me asking the model to fix my docker-compose file. In it, there's the `network: host` for the `build` part. The model kept assuming that the container would be running with the host network and kept asking me to remove it as a way to fix my issue, even though it wouldn't do anything for the container that is running. Because container runs on `custom_net` network only. The model was obsessed with it and kept telling me to remove it until I explicitly told that it is not, and cannot be the issue.

``` services:

  app:

    build:

      network: host

    networks:

      custom_net:

    ...

```