321–330 of 605 posts
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It's true for me. I type in what I want and then the AI system (compiler) generates the code. Doesn't everyone work that way?
Describing a compiler as "AI" is certainly a take.
clang doesn't "understand" the hints because it doesn't "understand" anything, but it knows what to do with them! Just like codex.
The memo itself is an excellent walk through historical bubbles, debt, financing, technological innovation, and much more, all written in a way that folks with a cursory knowledge of economics can reasonably follow along with. A+, excellent writing. The real meat is in the postscript though, because that's where the author puts to paper the very real (and very unaddressed) concerns around dwindling employment in a so…
The post script was pretty sobering. It's kind of the first time in my life that I've been actively hoping for a technology to out right not deliver on its promise. This is a pretty depressing place to be, because most emerging technologies provide us with exciting new possibilities whereas this technology seems only exciting for management stressed about payroll. It's true that the technology currently works as an e…
> It's kind of the first time in my life that I've been actively hoping for a technology to out right not deliver on its promise. Same here, and I think it's because I feel like a craftsman. I thoroughly enjoy the process of thinking deeply about what I will build, breaking down the work into related chunks, and of course writing the code itself. It's like magic when it all comes together. Sometimes I can't even beli…
Regardless of AI this has been years in the making. “Learn to code” has been the standard grinder cryptobro advice for “follow the money” for a while, there’s a whole generation of people getting into the industry for financial reasons (which is not wrong, just a big cultural shift).
> In many advanced software teams, developers no longer write the code; they type in what they want, and AI systems generate the code for them. What a wild and speculative claim. Is there any source for this information?
Wow, reading these comments and I feel like I've entered a parallel reality. My job involves implementing research ML and I use it literally all the time, very fascinating to see how many have such strong negative reactions. As long as you are good at reviewing code, spec-ing carefully, and make atomic changes - why would you not be using this basically all the time?
Kinda like having a child "help" you cook basically.
But for the child you do it because they actually learn. llms do not learn in that sense.
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Is it not sort of implied by the stats later: "Revenues from Claude Code, a program for coding that Anthropic introduced earlier this year, already are said to be running at an annual rate of $1 billion. Revenues for the other leader, Cursor, were $1 million in 2023 and $100 million in 2024, and they, too, are expected to reach $1 billion this year." Surely that revenue is coming from people using the services to gen…
> Surely that revenue is coming from people using the services to generate code? Right? Yes. And all code is tech debt. Now generated faster than ever.
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You should periodically ask Claude to review random parts of code to pump your metrics.
Has the net benefit that it points out things that are actually wrong and overlooked.
> In many advanced software teams, developers no longer write the code; they type in what they want, and AI systems generate the code for them. What a wild and speculative claim. Is there any source for this information?
Wow, reading these comments and I feel like I've entered a parallel reality. My job involves implementing research ML and I use it literally all the time, very fascinating to see how many have such strong negative reactions. As long as you are good at reviewing code, spec-ing carefully, and make atomic changes - why would you not be using this basically all the time?
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One important reason people like to write code is that it has well-defined semantics, allowing to reason about it and predict its outcome with high precision. Likewise for changes that one makes to code. LLM prompting is the diametrical opposite of that.
You’re still allowed to reason about the generated output. If it’s not what you want you can even reject it and write it yourself!
> You’re still allowed to reason about the generated output. If it’s not what you want you can even reject it and write it yourself!
You missed the key point. You can't predict and LLM's "outcome with high precision."
Looking at the output and evaluating it after the fact (like you describe) is an entirely different thing.