Your main target seems to be the view that software quality is a matter of 'aesthetic intuition,' but I see it differently.
Your main target seems to be the view that software quality is a matter of 'aesthetic intuition,' but I see it differently. I think because it's 'engineering,' there must be measurable indicators. Executable specifications Unit, integration, and property tests Official API documentation All of these provide ways to judge quality. There are so many metrics that the problem is actually choosing which ones to use. 1.Does it produce output A for input B? 2.Can it process 100,000 records within 5ms? 3.Is memory usage within the defined limit? 4.Does the protocol handle error conditions properly? You don't need to be an expert to test these. People forget that programming is one of the few fields where judgment criteria can be easily translated into machine executable tests. The biggest problem with epistemological objections is that they often assume a binary: 'experts can judge, non-experts cannot.' But in reality, it's a continuous process. You run the code, notice something odd, look up the terminology, compare it with official documentation and reference implementations, add tests, and gradually build up judgment in that area. Rewriting LLM generated code compresses that entire learning curve. In the past, entering an unfamiliar domain meant starting from a blank file and reading documentation. Now, you start with a working hypothesis and modify it. That's far cheaper than starting from scratch. If you treat LLM generated code as executable teaching material and a falsifiable hypothesis, it's a very powerful resource. I feel uncomfortable when people reduce programming to aesthetic quality alone. We were all trained to measure things.
Posted by jdw64 on Aug 3, 2026, 11:06 AM
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- I was skeptical, but this looks genuinely useful.
Raise real-world problems, find people facing the same issue, and discuss solutions.2,000 issues0 comments
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That's the biggest problem with iOS because Apple can be ordered to block them from the App Store and it would be instantly kill these pr...
NewI'm intrigued about the "Trip Planner" being a top-level app.
This asymmetry is IMO the biggest problem with AI-driven output.
This is one of the most important objectives in software today.
At least in Europe - these rouge corporations need to be reined in or just leave the market.
I was skeptical, but this looks genuinely useful.
Why has she gone through so many iPhones?
The biggest problem with Europe is the lack of innovation.
Your main target seems to be the view that software quality is a matter of 'aesthetic intuition,' but I see it differently.
Your main target seems to be the view that software quality is a matter of 'aesthetic intuition,' but I see it differently. I think because it's 'engineering,' there must be measurable indicators. Executable specifications Unit, integration, and property tests Official API documentation All of these provide ways to judge quality. There are so many metrics that the problem is actually choosing which ones to use. 1.Does it produce output A for input B? 2.Can it process 100,000 records within 5ms? 3.Is memory usage within the defined limit? 4.Does the protocol handle error conditions properly? You don't need to be an expert to test these. People forget that programming is one of the few fields where judgment criteria can be easily translated into machine executable tests. The biggest problem with epistemological objections is that they often assume a binary: 'experts can judge, non-experts cannot.' But in reality, it's a continuous process. You run the code, notice something odd, look up the terminology, compare it with official documentation and reference implementations, add tests, and gradually build up judgment in that area. Rewriting LLM generated code compresses that entire learning curve. In the past, entering an unfamiliar domain meant starting from a blank file and reading documentation. Now, you start with a working hypothesis and modify it. That's far cheaper than starting from scratch. If you treat LLM generated code as executable teaching material and a falsifiable hypothesis, it's a very powerful resource. I feel uncomfortable when people reduce programming to aesthetic quality alone. We were all trained to measure things.
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