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548 points kmelve | 3 comments | | HN request time: 0.001s | source
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rhubarbtree ◴[] No.45112846[source]
Does anyone have a link to a video that uses Claude Code to produce clean robust code that solves a non trivial problem (ie not tic tac toe or a landing page) more quickly than a human programmer can write? I don’t want a “demo”, I want a livestream from an independent programmer unaffiliated with any AI company and thus not incentivised to hype.

I want the code to have subsequently been deployed in production and demonstrably robust, without additional work outside of the livestream.

The livestream should include code review, test creation, testing, PR creation.

It should not be on a greenfield project, because nearly all coding is not.

I want to use Claude and I want to be more productive, but my experience to date is that for writing code beyond autocomplete AI is not good enough and leads to low quality code that can’t be maintained, or else requires so much hand holding that it is actually less efficient than a good programmer.

There are lots of incentives for marketing at the grassroots level. I am totally open to changing my mind but I need evidence.

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1. boesboes ◴[] No.45113184[source]
I've been using it to do all my work for the last month or two and have decided it's not worth it. I haven't made any recordings or anything, so this is purely my subjective experience: it's ok at greenfield stuff with some hand-holding to do things properly all the time. It knows the framework well, but won't try to use it correctly and go off on weird detours to 'debug' things that fail because of it. But on a bigger refactor of legacy code, that is well tested and the 'migration' process to the new architecture documented it just was very infuriating. One moment it seems to be doing alright and then suddenly I'm going backwards for days because it just makes things look like they work. It gets stuck on bad idea's and keeps trying them. Keeps making the same mistakes over and over, despite clear instruction on how to do it correctly..

I think it misses a feedback loop. Something that evaluates what went wrong, what works, what wont, and remembers that and then can use that to make better plans. From making sure it runs the tests correctly (instead of trying 5 different methods each time) to how to do TDD and what comments to add.

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2. sunnyam ◴[] No.45113559[source]
I have the same opinion, but my worry with this attitude is that it's going to hold me back in the long run.

A common thread in articles about developers using AI is that they're not impressed at first but then write more precise instructions and provide context in a more intuitive manner for the AI to read and that's the point at which they start to see results.

Would these principles not apply to regular developers as well? I suspect that most of my disappointment with these tools is that I haven't spend enough time learning how to use them correctly.

With Claude Code you can tell it what it did wrong. It's a bit hit-or-miss as to whether it will take your comments on board (or take them too literally) but I do think it's too powerful a tool to just ignore.

I don't want someone to just come and eat my cake because they've figured out how to make themselves productive with it.

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3. apercu ◴[] No.45114293[source]
I think of current state LLMs as precocious but green assistants that are sometimes useful but often screw up. It requires a significant amount of hand holding, still usually a net positive in my workflow but only (arbitrarily) a modest productivity bump (e.g. 10-15%). I feel like if I can get better at reigning in LLMs I can improve this productivity enhancement a bit more, but the idea that we can wholesale replace technical people is not realistic yet.

If I were a non-tech, non-specialist and/or had no business skills/experience and my job was mostly office admin I would be retraining however, because those jobs may be over except as vanity positions.