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Silhouettetoday at 4:43 PM1 replyview on HN

If there is one good thing that the generative AI tools have shown beyond any doubt it's that the classic "good programming" practices are still useful and effective. Self-documenting code. Modular design. Clearly defined architecture. Incremental development. Coding standards. Automated tests. Automated everything.

If there's a second thing the generative AI tools have shown beyond any doubt it's that many of the more modern (relatively speaking) "best practices" that have always been over-hyped and questionably-evidenced really do tend to produce worse results. LLMs take these methods to their logical conclusions and show us the end result much sooner. You can't just iterate your way to a solution when you don't even know what problem you're trying to solve. If you don't have a clear spec then you don't know what a correct product looks like. You need to invest time in reviewing code properly. If you don't keep the big picture in mind then the big picture becomes a mess.

Maybe one day the LLMs will leave me out of a job but at least I'll feel validated first!


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skydhashtoday at 10:49 PM

> If there is one good thing that the generative AI tools have shown beyond any doubt it's that the classic "good programming" practices are still useful and effective

If you apply those practice, then quickly you find yourself using the agent as merely a writing boost. And there’s an inflexion point when coding is no longer a bottleneck. Instead, you spend more time on thinking about design. You can see it in open source projects where most PRs are just a few line diffs. The bottleneck is knowledge and problem solving talent.

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