331–340 of 552 posts
Sorry this might be a dumb question but where are the prompts in the source code ? I was thinking like I prompt ChatGPT and it prints some code , there would be similar prompts. Is the readme the prompt?
Start at the bottom...they are in the commit messages, or sometimes the .md file
And OAuth is not particularly hard to implement, I did that a bunch of times (for server and the client side). It's well-specified and so it fits well for LLMs.
So it's probably more like 2x acceleration for such code? Not bad at all!
Sorry this might be a dumb question but where are the prompts in the source code ? I was thinking like I prompt ChatGPT and it prints some code , there would be similar prompts. Is the readme the prompt?
> Claude's output was thoroughly reviewed by Cloudflare engineers with careful attention paid to security and compliance with standards. So, for those of us who are not OAuth experts, don't have a team of security engineers on call, and are likely to fall into all the security and compliance traps, how does this help? I don't need AI to write my shitty code. I need AI to review and correct my shitty code.
…anyway, Gemini pro is a quite good reviewer if you are specific about what you need reviewed and provide relevant dependencies in the context.
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You run into knowledge collapse because nobody is socially reproducing that knowledge.
This seems an important thing that somebody should be concerned about. How do we get the next generation of engineers? And how will they even be able to do the senior engineer work of validating the LLM output if they haven't had the years of experience writing code themselves?
in software atleast but if you involve in hardware. good things AI cant just replace you outright
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> This is exactly the direction I expect AI-assisted coding to go in. Not software engineers being kicked out and some business person pressing a few buttons to have a fully functional app (as is playing out in a lot of fantasies on LinkedIn & X), but rather experienced engineers using AI to generate bits of code and then meticulously reviewing and testing them. There is a middle ground: software engineers being kick…
I'm not so sure that would work well in practice. How would the inexperienced developer know that the code created by the AI was correct? What if subtle bugs are introduced that the inexperienced developer didn't catch until it went out into production? What if the developer didn't even know how to debug those problems correctly? Would they know that the code they are writing is maintainable and extensible, or are th…
This is exactly the direction I expect AI-assisted coding to go in. Not software engineers being kicked out and some business person pressing a few buttons to have a fully functional app (as is playing out in a lot of fantasies on LinkedIn & X), but rather experienced engineers using AI to generate bits of code and then meticulously reviewing and testing them. The million dollar (perhaps literally) question is – coul…
It took me a few days to build the library with AI. I estimate it would have taken a few weeks, maybe months to write by hand. That said, this is a pretty ideal use case: implementing a well-known standard on a well-known platform with a clear API spec. In my attempts to make changes to the Workers Runtime itself using AI, I've generally not felt like it saved much time. Though, people who don't know the codebase as…
Code I know nothing about? AI is very helpful there
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> Not software engineers being kicked out ... but rather experienced engineers using AI to generate bits of code and then meticulously reviewing and testing them. But what if you only need 2 kentonv's instead of 20 at the end? Do you assume we'll find enough new tasks that will occupy the other 18? I think that's the question. And the author is implementing a fairly technical project in this case. How about routine L…
> But what if you only need 2 kentonv's instead of 20 at the end? Do you assume we'll find enough new tasks that will occupy the other 18? I think that's the question. This is likely where all this will end up. I have doubts that AI will replace all engineers, but I have no doubt in my mind that we'll certainly need a lot less engineers. A not so dissimilar thing happened in the sysadmin world (my career) when everyt…
There was another article posted somewhere that made a parallel between the AI hype and no-code, outsourcing and other waves that have come.
This is exactly the direction I expect AI-assisted coding to go in. Not software engineers being kicked out and some business person pressing a few buttons to have a fully functional app (as is playing out in a lot of fantasies on LinkedIn & X), but rather experienced engineers using AI to generate bits of code and then meticulously reviewing and testing them. The million dollar (perhaps literally) question is – coul…
> The million dollar (perhaps literally) question is – could @kentonv have written this library quicker by himself without any AI help? I *think* the answer to this is clearly no: or at least, given what we can accomplish today with the tools we have now, and that we are still collectively learning how to effectively use this, there's no way it won't be faster (with effective use) in another 3-6 months to fully-code…
I think these discussions need to start from another point. The techniques changed radically, and so did the way problems are tackled. It's not that a software engineer is/was unable to deliver a project with/without LLMs. That's a red herring. The key aspects are things like the overall quality of the work being delivered vs how much time it took to reach that level of quality.
For example, one of the primary ways a LLM is used is not to write code at all: it's to explain to you what you are looking at. Whether it's used as a Google substitute or a rubber duck, developers are able to reason with existing projects and even explore approaches and strategies to tackle problem like they were never able to do so. You no longer need to book meetings with a principal engineer to as questions: you just drop a line in Copilot Chat and ask away.
Another critical aspect is that LLMs help you explore options faster, and iterate over them. This allows you to figure out what approach works best for your scenario and adapt to emerging requirements without having to even chat with anyone. This means that, within the timeframe you would deliver the first iteration of a MVP, you can very easily deliver a much more stable project.
Earlier quoted context omitted.
> But what if you only need 2 kentonv's instead of 20 at the end? Do you assume we'll find enough new tasks that will occupy the other 18? I think that's the question. This is likely where all this will end up. I have doubts that AI will replace all engineers, but I have no doubt in my mind that we'll certainly need a lot less engineers. A not so dissimilar thing happened in the sysadmin world (my career) when everyt…
I think there's a huge huge space of software to build that isn't being touched today because it's not cost-effective to have an engineer build them. But if the time it takes an engineer to build any one thing goes down, now there are a lot more things that are cost effective. Consider niche use cases. Every company tends to have custom processes and workflows. Think about being an accountant at one company vs. anoth…
We assume quite a bit about the challenge when we say it’s getting feature out.
It’s sort of like saying we can sprint faster with these tools, when the race is a marathon.
Or a better example is Coke vs Pepsi.
How do LLMs impact long term project, firm, process viability ?