For the non-replying disagreers, let me try with a few more words. I think my comment is a pretty decent one-line summary of the Vibe-awareness section, especially in light of the sections that precede it. If you glance through that part of the post again and still disagree, then I guess our mileage does just vary.
But many experienced prompt engineers have reported that prompting gets more effective when you use more words and just “tell it what you want”. This type of language points to engaging your social know-how as opposed to trying to game out the system. See for instance https://generative.ink/posts/methods-of-prompt-programming/, which literally advocates an “anthropomorphic approach to prompt programming” and takes care to distinguish this from pernicious anthropomorphizing of the system. This again puts an emphasis on bringing your social self to the task.
Of course, in many situations the direct effect of talking to the system is session-bounded. But it still applies within the session, when prompt engineering is persisted or reused, and when session outputs are fed back into future sessions by any path.
Furthermore, as the models grow stronger, our ability to anticipate the operation of mechanism grows less, and the systems’ ability to socialize on our own biological and cultural evolution-powered terms grows greater. This will become even more true if, as seems likely, architectures evolve toward continuous training or at least finer-grained increments.
These systems know a lot about our social behaviors, and more all the time. Interacting with them using the vast knowledge of the same things each of us possesses is an invitation we shouldn’t refuse.
I don’t know whether this would be the author’s take, but to me it urges us to understand and “control” these AIs socially: by talking to them.
For the non-replying disagreers, let me try with a few more words. I think my comment is a pretty decent one-line summary of the Vibe-awareness section, especially in light of the sections that precede it. If you glance through that part of the post again and still disagree, then I guess our mileage does just vary.
But many experienced prompt engineers have reported that prompting gets more effective when you use more words and just “tell it what you want”. This type of language points to engaging your social know-how as opposed to trying to game out the system. See for instance https://generative.ink/posts/methods-of-prompt-programming/, which literally advocates an “anthropomorphic approach to prompt programming” and takes care to distinguish this from pernicious anthropomorphizing of the system. This again puts an emphasis on bringing your social self to the task.
Of course, in many situations the direct effect of talking to the system is session-bounded. But it still applies within the session, when prompt engineering is persisted or reused, and when session outputs are fed back into future sessions by any path.
Furthermore, as the models grow stronger, our ability to anticipate the operation of mechanism grows less, and the systems’ ability to socialize on our own biological and cultural evolution-powered terms grows greater. This will become even more true if, as seems likely, architectures evolve toward continuous training or at least finer-grained increments.
These systems know a lot about our social behaviors, and more all the time. Interacting with them using the vast knowledge of the same things each of us possesses is an invitation we shouldn’t refuse.