I find that some of my friends and acquaintances have gotten obsessed with prompting style, "prompt engineering", which skills to use, which skills to build, "context engineering", and a billion other variations on "how to write smart things so the model does good". Friends, look at the prompts that Anthropic's own people are putting into the machine: > A few hours after the first message, we found that Claude was st…
Been skeptical for quite some time that "using AI" is a real skill/genuine field of expertise. I think I need to start sharing that skepticism more loudly and publicly! (I'll caveat that by saying I think machine learning fundamentals are useful for evaluating any estimator. And an ML background can be good to give one an appreciation of how hard some tasks are to estimate, such as machine translation, summarization,…
Some people struggle to effectively use AI because they either have to spend a lot of time reading and thinking about the response or they have a hard time noticing when the model is subtly going off the rails. Others use it to good effect because they can anticipate which tasks would be better handled manually, or are good at catching that the way the model is describing something subtly indicates a misunderstanding.