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  "text": "This is exactly why evals matter more than prompt or engineering skills alone....because instruction-following is measurable! \n\nWithout the eval layer, “I wrote a good skill” can become mostly (sometimes, even dangerous) bs.\n\nEvals mean you can turn things like a skill's \"hard prohibitions\" into automated checks that make model output quantifiable and testable; pretty much every flaw listed here in @lex_node 's tweet would qualify. Code-based evals would catch a lot of these deterministically; LLM-as-judge would handle the more semantic ones.\n\nSo what can you do to learn evals to fix these types of (literal) skill issues? Where do you start? Well, you can take @HamelHusain and @sh_reya 's excellent evals course! \n\nBut, to give you some appetite for your deep dive, let's drill into some step by step evals basics for beginners:",
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    "text": "this is my issue with AI x law. the last thing I want as a lawyer is anything non-deterministic in my documents lol. it doesn't obey the skills even if you wrote the skills to try to make it behave \n\ngive me a rigid docgen template and an AI that can't do anything but input variables into the docgen, over generalized legal AI, any day of the week . . .",
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