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by avaer
3 days ago
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The trend (and what TFA is arguing) is literally the opposite: be more implicit, don't waste time on details, and encode the high level concepts only. Because the rest has a billion examples in the model. You can argue against LLM's, but increasingly (unfortunately) you're not going to do better programming by prompting the LLM with code. The agent can find the interfaces it needs. |
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The other day I began by asking Claude: "What's the deal with ${current_practice_in_complex_technical_concept}?" and was talked down to like I was an idiot. Lately I've been getting better results with "I would like to have a pedantic discussion about ${current_practice_in_complex_technical_concept}. Please define the main terms of art, then I will ask my questions."
Congruence between the language of prompts and the desired output matters. Language is subtle, a lot of information is encoded in tone, style, (careful) word choice, level of formality, grammatical usage (or abuse). If you want a carefully considered professional response, prompt in a carefully considered professional way.
Every field has its shibboleths. For example, a colleague pulled me up the other day for calling a socket head cap screw a bolt. Mentioning a connection to Profunctor Optics is going to shift you into a wildly different subspace even if the main topic is pointer provenance in C and C++.