191–200 of 342 posts
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The one that does not convert C# at all and asks you to just optimize it in C# instead (and to use the appropriate build option) :D
I’m converting game logic from C# to UE5 C++. So far made great progress using ChatGPT4o and o1
I definitely respect David's opinion given his caliber, but pieces like this make me feel strange that I just don't have a burning desire to use them. Like, yesterday I made some light changes to a containerized VPN proxy that I maintain. My first thought wasn't "how would Claude do this?" Same thing with an API I made a few weeks ago that scrapes a flight data website to summarize flights in JSON form. I knew I woul…
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> That he says LLMs make him more productive at all as a hands-on developer, especially around first drafts on a new idea, means a lot to me personally. There is likely to be a great rift in how very talented people look at sharper tools. I've seen the same division pop up with CNC machines, 3d printers, IDEs and now LLMs. If you are good at doing something, you might find the new tool's output to be sub-par over wha…
Intersting. So engineers that like to iterate and explore are more likely to like LLMs. Whereas engineers that like have a more rigid specific process are more likely to dislike LLMs.
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I’m converting game logic from C# to UE5 C++. So far made great progress using ChatGPT4o and o1
Do you find these working out better for you than Claude 3.5 Sonnet? So far I've not been a fan of the ChatGPT models' output.
Biggest advantage is the o1 128k context. I can one shot an entire 1000 line class where normally I’d have to go function by function with 4o.
One interesting bit of context is that the author of this post is a legit world-class software engineer already (though probably too modest to admit it). Former staff engineer at Google and co-founder / CTO of Tailscale. He doesn't need LLMs. That he says LLMs make him more productive at all as a hands-on developer, especially around first drafts on a new idea, means a lot to me personally. His post reminds me of an…
I have also many years of programming experience and find myself strongly "accelerated" by LLMs when writing code. But, if you think at it, it makes sense that many seasoned programmers are using LLMs better. LLMs are a helpful tool, but also a hard-to-use tool, and in general it's fair to think that better programmers can do a better use of some assistant (human or otherwise): better understanding its strengths, ide…
I have actually found that from a documentation point of view, querying LLMs has made me better and explaining things to people. If, given the documentation for a system or API, a modern LLM can't answer specific questions about how to perform a task, a person using the same documentation will also likely struggle. It's proving to be a good way to test the effectiveness of documentation, for humans and for LLMs.
I definitely respect David's opinion given his caliber, but pieces like this make me feel strange that I just don't have a burning desire to use them. Like, yesterday I made some light changes to a containerized VPN proxy that I maintain. My first thought wasn't "how would Claude do this?" Same thing with an API I made a few weeks ago that scrapes a flight data website to summarize flights in JSON form. I knew I woul…
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> proprietary code outside the network Thought exercise: what would seriously happen if you did let some of your proprietary code outside your network? Oddly enough, 75% of the people writing code on HN probably have their companies code stored in GitHub. So there already is an inherent trust factor with GH/MSFT. As another anecdote - Twitch's source code got leaked a few years back. Did Twitch lose business because…
> Thought exercise: what would seriously happen if you did let some of your proprietary code outside your network Lawsuits? Lawful terminations? Financial damages?
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> Thought exercise: what would seriously happen if you did let some of your proprietary code outside your network Lawsuits? Lawful terminations? Financial damages?
Huh? No, i'm saying, what potential damage does an organization have? Not the individual who may leak data outside your network.
Other risks include leaking industrial secrets that may significantly damage company business or benefit competitors.
The killer feature about LLMs with programming in my opinion is autocomplete (the simple copilot feature). I can probably be 2-3x more productive as I'm not typing (or thinking much). It does a fairly good job pulling in nearby context to help it. And that's even without a language server. Using it to generate blocks of code in a chat like manner in my opinion just never works well enough in the domains I use it on.…
The autocomplete is mostly a nusance and maybe low percentage of the time it does right.
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If you don’t mind me asking: which popular LLM(s) have you been using for this and how are you providing the code base into the context window?
Not OP but Aider provides a repo map to the LLM as context, which consists of the directory tree, filenames, and important symbols in each file. It can use the popular LLMs as well as Ollama. https://aider.chat/docs/repomap.html Aider hosts a leaderboard that rates LLMs on performance, including a section on refactoring. https://aider.chat/docs/leaderboards/refactor.html