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421 points briankelly | 1 comments | | HN request time: 0.204s | source
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necovek ◴[] No.43575664[source]

The premise might possibly be true, but as an actually seasoned Python developer, I've taken a look at one file: https://github.com/dx-tooling/platform-problem-monitoring-co...

All of it smells of a (lousy) junior software engineer: from configuring root logger at the top, module level (which relies on module import caching not to be reapplied), over not using a stdlib config file parser and building one themselves, to a raciness in load_json where it's checked for file existence with an if and then carrying on as if the file is certainly there...

In a nutshell, if the rest of it is like this, it simply sucks.

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rybosome ◴[] No.43575714[source]

Ok - not wrong at all. Now take that feedback and put it in a prompt back to the LLM.

They’re very good at honing bad code into good code with good feedback. And when you can describe good code faster than you can write it - for instance it uses a library you’re not intimately familiar with - this kind of coding can be enormously productive.

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1. BikiniPrince ◴[] No.43577317[source]

I’ve found AI tools extremely helpful in getting me up to speed with a library or defining an internal override not exposed by the help. However, if I’m not explicit in how to solve a problem the result looks like the bad code it’s been ingesting.