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> now infinitely more productive How much more productive do you feel you are coding with an LLM? As another HN user said, to me it's like a talking dog -- inc

> now infinitely more productive How much more productive do you feel you are coding with an LLM? As another HN user said, to me it's like a talking dog -- incredible yet useless.

fnordpiglet 3y ago
I feel it gives me about a 30% lift on mechanical tasks and a 60% lift on learning / unblocking in areas of ambiguity. I use GPT for the mechanical tasks and ChatGPT for the learning tasks. An example of the learning would be “explain to me the use of Box::pin in the context of rust futures” or some such, but also sometimes some common idiom I’m brain farting on. Searching Kagi will yield the answers, just more slowly and deeply embedded in some document or stackoverflow answer vomit requiring lot of wasted effort that fully distracts me from my flow. The fact I can ask follow up questions on areas of ambiguity is useful. When it hallucinates it generally means I’m in an area that’s either undefined as of yet, or is really niche. The nice thing about programming is hallucination feedback is basically instant so I then pull out Kagi and research a bit, and maybe 90% of the time it’s just not possible. There has been some work done on generating code in a feedback cycle to winnow out hallucinations and it seems to work fairly well [1]- I think 99% of the challenges LLM face are primarily related to a lack of constraint, optimization, agency, and solver feedback. As they get integrated into a system with the ability to inform and constrain and guide using classic AI techniques their true value will be attainable. But they’re pretty useful even today. N.b., I’m a 32 year veteran distinguished engineer level at FAANG and adjacent firms that programs daily. 1 https://voyager.minedojo.org https://voyager.minedojo.org
w0m 3y ago
> to me it's like a talking dog That's if you're explicitly asking it questions. Have you sat down and coded with Copilot offering suggestions as you went? It's honestly incredibly helpful, especially when leveraging a new language or stack.
StackOverlord 3y ago
I use GPT to write code sometimes instead of importing a library. For instance a function to breadth first traverse a directed acyclic graph and slice it into levels. Another one to find a node in a nested graph using partial paths. I could have written those functions, but GPT4 does it correctly and faster.
yi_xuan 3y ago
From my personal experience, it's quite useful but not as much as a lot of people thought it would be. The ability solving 'simple' questions is great. I used it more as a smarter google.
inopinatus 3y ago
One simply needs to think more laterally about the dog.
lannisterstark 3y ago
>incredible yet useless. I almost always begin my tasks with ChatGPT, by asking it for a framework. "Design a x request that gets me results in form of this JSON, and now display it on y table according to this criteria" It gives me framework, I adjust and expand upon it. Works wonderfully. I even have a 'bot' running on one of the IRC channels that was almost 100% self written by ChatGPT.

> now infinitely more productive How much more productive do you feel you are coding with an LLM? As another HN user said, to me it's like a talking dog -- incredible yet useless.

fnordpiglet 3y ago

I feel it gives me about a 30% lift on mechanical tasks and a 60% lift on learning / unblocking in areas of ambiguity. I use GPT for the mechanical tasks and ChatGPT for the learning tasks. An example of the learning would be “explain to me the use of Box::pin in the context of rust futures” or some such, but also sometimes some common idiom I’m brain farting on. Searching Kagi will yield the answers, just more slowly and deeply embedded in some document or stackoverflow answer vomit requiring lot of wasted effort that fully distracts me from my flow. The fact I can ask follow up questions on areas of ambiguity is useful. When it hallucinates it generally means I’m in an area that’s either undefined as of yet, or is really niche. The nice thing about programming is hallucination feedback is basically instant so I then pull out Kagi and research a bit, and maybe 90% of the time it’s just not possible. There has been some work done on generating code in a feedback cycle to winnow out hallucinations and it seems to work fairly well [1]- I think 99% of the challenges LLM face are primarily related to a lack of constraint, optimization, agency, and solver feedback. As they get integrated into a system with the ability to inform and constrain and guide using classic AI techniques their true value will be attainable. But they’re pretty useful even today. N.b., I’m a 32 year veteran distinguished engineer level at FAANG and adjacent firms that programs daily. 1 https://voyager.minedojo.org https://voyager.minedojo.org

w0m 3y ago

> to me it's like a talking dog That's if you're explicitly asking it questions. Have you sat down and coded with Copilot offering suggestions as you went? It's honestly incredibly helpful, especially when leveraging a new language or stack.

StackOverlord 3y ago

I use GPT to write code sometimes instead of importing a library. For instance a function to breadth first traverse a directed acyclic graph and slice it into levels. Another one to find a node in a nested graph using partial paths. I could have written those functions, but GPT4 does it correctly and faster.

yi_xuan 3y ago

From my personal experience, it's quite useful but not as much as a lot of people thought it would be. The ability solving 'simple' questions is great. I used it more as a smarter google.

inopinatus 3y ago

One simply needs to think more laterally about the dog.

lannisterstark 3y ago

>incredible yet useless. I almost always begin my tasks with ChatGPT, by asking it for a framework. "Design a x request that gets me results in form of this JSON, and now display it on y table according to this criteria" It gives me framework, I adjust and expand upon it. Works wonderfully. I even have a 'bot' running on one of the IRC channels that was almost 100% self written by ChatGPT.