You get exactly what you asked for. Not what you meant.<\/p>\n
I watch people write prompts like they’re Googling something. A few keywords, a vague direction\u2026 Then they’re frustrated when the output is generic, wrong, or just weird.<\/p>\n
But the model did exactly what you told it to do\u2026 and that’s the problem.<\/p>\n
The old genie story works because the genie isn’t malicious\u2026 it’s literal. “I wish for a million bucks” and a million male deer appear in your yard. The genie did exactly what you asked it, you just didn\u2019t think about your question.<\/p>\n
LLMs operate on the same principle, minus the malice and the deer (usually). When you prompt “write me a marketing email,” you’ve described approximately four billion possible outputs. The model picks one. You hate it. You try again with the same vague prompt. You hate it differently. You conclude the tool doesn’t work.<\/p>\n
The tool works fine. You made a genie wish.<\/p>\n
What changes everything is realizing that prompt engineering isn’t about clever tricks or magic words (usually). It’s about the same skill that makes someone effective in any leadership role: the ability to articulate what you actually want with enough specificity that another intelligent entity can deliver it.<\/p>\n
Tell it who it’s writing for. Tell it what tone. Tell it what success looks like and what failure looks like. Give it an example of something you loved and something you hated. Tell it what to leave out (the negative space is just as important as the positive).<\/p>\n
In other words: do the work you should have been doing with your human teams all along.<\/p>\n
The uncomfortable truth about prompt engineering is that it isn’t an AI skill. It’s a communication skill. The people who are bad at prompting are usually the same people who send their teams vague Slack messages and then get frustrated when the deliverable misses the mark.<\/p>\n
The genie didn’t get it wrong. It followed the rules exactly.<\/p>\n","protected":false},"excerpt":{"rendered":"
You get exactly what you asked for. Not what you meant. I watch people write prompts like they’re Googling something. A few keywords, a vague direction\u2026 Then they’re frustrated when the output is generic, wrong, or just weird. But the model did exactly what you told it to do\u2026 and that’s the problem. The old […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[195],"tags":[196,202,222,221],"class_list":["post-954","post","type-post","status-publish","format-standard","hentry","category-linkedin","tag-ai","tag-leadership","tag-prompting","tag-writing"],"_links":{"self":[{"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/posts\/954","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/comments?post=954"}],"version-history":[{"count":1,"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/posts\/954\/revisions"}],"predecessor-version":[{"id":987,"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/posts\/954\/revisions\/987"}],"wp:attachment":[{"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/media?parent=954"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/categories?post=954"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kitchencloset.com\/home\/bryan\/blog\/wp-json\/wp\/v2\/tags?post=954"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}