201–210 of 498 posts
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The author’s main point is that there hasn’t been an uptick in total code shipped, as you would expect if people are 10x-ing their productivity. Whether folks admit to using AI in their workflow is irrelevant.
Maybe people are working less and enjoying life more, while shipping the same amount of code as before. If someone builds a faster car tomorrow, I am not going to go to the office more often.
While I like the self reflection from this article, I don't think his methodology adds up (pun intended). First there are two main axis where LLMs can make you more productive: speed & code quality. I think everyone is obsessed about the first one, but its less relevant. My personal hypothesis is that when using LLMs, you are only faster if you would be doing things like boilerplate code. For the rest, LLMs don't rea…
In case the author is reading this, I have the receipts on how there's a real step function in how much software I build, especially lately. I am not going to put any number on it because that makes no sense, but I certainly push a lot of code that reasonably seems to work. The reason it doesn't show up online is that I mostly write software for myself and for work, with the primary goal of making things better, not…
Same. On many days 90% of my code output by lines is Claude generated and things that took me a day now take well under an hour. Also, a good chunk of my personal OSS projects are AI assisted. You probably can't tell from looking at them, because I have strict style guides that suppress the "AI style", and I don't really talk about how I use AI in the READMEs. Do you also expect I mention that I used Intellisense and…
No, but I expect my software to have been verified for correctness, and soundness by a human being with a working mental model of how the code works. But, I guess that's not a priority anymore if you're willing to sacrifice $2400 a year to Anthropic.
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I've had great success with GPT5 in existing projects because its agent mode is very good (the best I've seen so far) at analyzing the existing codebase and then writing code that feels like it fits in already (without prompt engineering on my part). I still agree that AI is particularly good on fresh projects though.
Could be that there is a huge difference in the products. Last few companies have given me Github Copilot which I find entirely useless, I found the automatic suggestions more distracting than useful, and the fix and explain functions never work. But maybe if you burn $1000/day on Claude Code it works a lot better. And then companies see the results from that and wonder why they aren't getting it spending a couple of…
In case the author is reading this, I have the receipts on how there's a real step function in how much software I build, especially lately. I am not going to put any number on it because that makes no sense, but I certainly push a lot of code that reasonably seems to work. The reason it doesn't show up online is that I mostly write software for myself and for work, with the primary goal of making things better, not…
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What AI coding tools/models have you been using?
Let me guess ... they're holding it wrong, and the model they're using is older than 20 minutes.
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Those are fundamentally different. If people on this site really can't tell the difference then it makes sense why people on HN assume AI is a bubble. People paid a lot for beanie babies and various speculative securities on the assumption that they could be sold for more in the future. They were assets people aimed to resell at a profit. They had no value by themselves. The source of revenue for AI companies has inh…
The central issue here is whether the money pouring into AI companies is producing anything other than more AI companies. I think the article's premise is basically correct - if we had a 10x explosion of productivity where is the evidence? I would think some is potentially hidden in corporate / internal apps but despite everyone at my current employer using these tools we don't seem to be going any faster. I will adm…
The fundamental difference of opinion people have here though is some people see current AI capabilities as a floor, while others see it as a ceiling. I’d agree with arguments that AI companies are overvalued if current models are as capable as AI will ever be for the rest of time, but clearly that is not the case, and very likely, as they have been every few months over the past few years, they will keep getting better.
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Could be that there is a huge difference in the products. Last few companies have given me Github Copilot which I find entirely useless, I found the automatic suggestions more distracting than useful, and the fix and explain functions never work. But maybe if you burn $1000/day on Claude Code it works a lot better. And then companies see the results from that and wonder why they aren't getting it spending a couple of…
I use GitHub Copilot from work in agent mode with GPT5 and it’s great! I don’t use the suggestions, fix, or explain features, I agree they’re almost always not helpful.
I used to be a full-time developer back in the day. Then I was a manager. Then I was a CTO. I stopped doing the day-to-day development and even stopped micro-managing the detailed design. When I tried to code again, I found I didn't really have the patience for it -- having to learn new frameworks, APIs, languages, tricky little details, I used to find it engrossing: it had become annoying. But with tools like Claude…
When you consider this, "generate me a whole repo" is trivially garbage and not meeting the measurement metric. However having AI autocomplete "getUser(..." clearly IS productive.
Now is that a 0.1% increase, 1%, or 10%? That I can't tell you.