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Notes -
I find that frontier LLMs tend to be better than I am at writing code, and I am pretty good but not world class at writing code (e.g. generally in the first 1% but not first 0.1% of people to solve each day of advent of code back when I did that). What's missing tends to be context, and particularly the ability to obtain the necessary context to build the correct thing when that context isn't handed to the LLM on a silver platter.
Although a similar pattern also shows up pretty frequently in junior developers, and they often grow out of it, so...
LLM is great at writing code in area utterly unfamiliar to me and often better than reading documentation.
But nearly always rewrite/tweaking/fixing is needed, for anything beyond the most trivial examples.
Maybe I am bad at giving it context.
You, me, and everyone else. Sarah Constantin has a good post The Great Data Integration Schlep about the difficulty of getting all the relevant data together in a usable format in the context of manufacturing, but the issue is everywhere, not just manufacturing.
There's a reason data scientists are paid the big bucks, and it sure isn't the difficulty of typing
import pandas as pd.More options
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