The useful divide in applied AI is between the mentally flexible and the team joiners. One camp treats tools, strategies and beliefs as revisable. The other picks a side and organizes its judgment around belonging.

Team joining offers a shortcut. It narrows what deserves attention and supplies ready-made explanations for why the chosen approach remains superior. Contradictory evidence becomes easier to dismiss when a community has already written the rebuttal. Judgment becomes advocacy.

The “Claude-pilled” version illustrates the problem. Someone uses Claude extensively, learns its strengths, adapts their prompts and becomes effective with it. That fluency can then be mistaken for proof of universal superiority. Other models receive less practice and less patience. Familiarity gets credited entirely to capability.

A useful test of mental flexibility is whether someone can recognize concrete value in a competing model. Can they explain where it wins? Can they name evidence that would change their preference? If every comparison must end with the same winner, the conclusion came before the evaluation.

In product development and research, that attachment creates an opening. Team joiners protect their priors. The mentally flexible are ready to abandon all priors when a better outcome demands it. They welcome the discovery that their understanding is obsolete: it means something previously out of reach may now be possible.

Team joiners have a position to defend. The mentally flexible have a result to improve. That difference is a source of alpha.