@pvncher@ignacioaal What would also be useful is a subagent auto-selection mode where you can define in advance what types of tasks should map to specific subagent models and reasoning levels, so that it doesn't need to guess. Since everybody has different workflows and preferences.
@66cjg@theinformation The capabilities are jagged, so in some areas it's already far past human level, in other areas it's lower than human level, so it's not an apples-apples comparison in the first place
@TinoWening That strategy won't work for open-ended tasks like network/kernel troubleshooting, where the issue could end up being very simple or very complex and usually you won't know until afterwards.
@thebuggeddev The benchmarks measure objective metrics, and this task is subjective, so I don't see the connection. And this model isn't known for its UI design abilities in the first place.
@plotarmordev@kimmonismus Because as the models get more capable they'll be used researchers for things like drug discovery and curing diseases, which would still benefit anyone who isn't using the models themselves