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Cloudlflare builds OAuth with Claude and publishes all the prompts

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Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#411
post #40

Earlier quoted context omitted.

> They can get halfway there and then struggle immensely. Restart the conversation from scratch. As soon as you get something incorrect, begin from the beginning. It seems to me like any mistake in a messages chain/conversation instantly poisons the output afterwards, even if you try to "correct" it. So if something was wrong at one point, you need to go back to the initial message, and adjust it to clarify the promp…

Chatbot UIs really need better support for conversation branching all around. It's very handy to be able to just right-click on any random message in the conversation in LM Studio and say, "branch from here".

Certainly in my version of LM Studio (0.3.15) it has a branch button at the end of every message [0]

[0] https://i.imgur.com/xZ2Fkn7.png

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#412
post #10

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…

That's not the million dollar question; anyone who's done any kind of AI coding will tell you it's ridiculously faster. I haven't touched JavaScript, CSS & HTML in like a decade. But I got a whole website created with complex UI interactions in 20 minutes - and no frameworks - by just asking ChatGPT to write stuff for me. And that's the crappy, inefficient way of doing this work. Would have taken me a week to figure out all that. If I'd known how to do it already, and I was very good, perhaps it would have taken the same amount of time? But clearly there is a force-multiplier at work here.

The million dollar question is, what are the unintended, unpredicted consequences of developing this way?

If AI allows me to write code 10x faster, I might end up with 10x more code. Has our ability to review it gotten equally fast? Will the number of bugs multiply? Will there be new classes of bugs? Will we now hire 1 person where we hired 5 before? If that happens, will the 1 person leaving the company become a disaster? How will hiring work (cuz we have such a stellar track record at that...)? Will the changing economics of creating software now make SaaS no longer viable? Or will it make traditional commercial software companies no longer viable? Will the entire global economy change, the way it did with the rise of the first tech industry? Are we seeing a rebirth?

We won't know for sure what the consequences are for a while. But there will be consequences.

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#413

Earlier quoted context omitted.

> How could that possibly be true!? (I'll assume you're not joking, because your post is ridiculous enough to look like sarcasm.) The answer is because programmers read code 10 times more (and think about code 100 times more) than they write it.

Yeah, but how fast can you write compared to how fast you think? How many times have you read a story card and by the time you finished reading it you thought "It's an easy task, should take me 1 hour of work to write the code and tests"? In my experience, in most of those cases the AI can do the same amount of code writing in under 10 minutes, leaving me the other 50 minutes to review the code, make/ask for any nece…

I don't know anyone who can think faster than they can type (on average), they would have to have an IQ over 150 or something. For mere mortals like myself, reasoning through edge cases and failure conditions and error handling and state invariants takes time. Time that I spend looking at a blinking cursor while the gears spin, or reading code. I've never finished a day where I thought to myself "gosh darn, if only I could type faster this would be done already".

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#414
If my future career consists of constantly prompting and code-reviewing a semi-competent, nonhuman coder in order to eventually produce something decent, then I want no part in that future, even if it's more "efficient" in the sense of taking less time overall. That sounds extremely frustrating, personally unrewarding, alienating. I've read the prompts and the commit messages, and to be honest, I don't have the patience to deal with a Claude-level coder. I'd be yelling at the idiot and shaking my fists the whole time. I'd rather just take more time and write the code myself. It's much more pleasant that way. This future of A.I. work sounds like a dystopia to me. I didn't sign up for that. I never wanted to be a glorified babysitter.

It feels infinitely worse than mentoring an inexperienced engineer, because Claude is inhuman. There's no personal relationship, it doesn't make human mistakes or achieve human successes, and if Claude happens to get better in the future, that's not because you personally taught it anything. And you certainly can't become friends.

They want to turn artists and craftsmen into assembly line supervisors.

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#415

Earlier quoted context omitted.

> Still saves a lot of time vs typing everything from scratch No it doesn't. Typing speed is never the bottleneck for an expert. As an offline database of Google-tier knowledge, LLM's are useful. Though current LLM tech is half-baked, we need: a) Cheap commodity hardware for running your own models locally. (And by "locally" I mean separate dedicated devices, not something that fights over your desktop's or laptop's…

> No it doesn't. Typing speed is never the bottleneck for an expert How could that possibly be true!? Seems like it'd be the same as suggesting being constrained to analog writing utensils wouldn't bottleneck the process of publishing a book or research paper. At the very least such a statement implies that people with ADHD can't be experts.

It seems fair to say that it is ~never the overall bottleneck? Maybe once you figure out what you want, typing speed briefly becomes the bottleneck, but does any expert finish a day thinking "If only I could type twice as fast, I'd have gotten twice as much work done?" That said, I don't think "faster typing" is the only benefit that AI assistance provides.

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#416
post #43

Earlier quoted context omitted.

The million-dollar question is not whether you can review at the speed the model is coding. It is whether you can trust review alone to catch everything. If a robot assembles cars at lightning speed... but occasionally misaligns a bolt, and your only safeguard is a visual inspection afterward, some defects will roll off the assembly line. Human coders prevent many bugs by thinking during assembly.

> Human coders prevent many bugs by thinking during assembly. I'm far from an AI true believer but come on -- human coders write bugs, tons and tons of bugs. According to Peopleware, software has "an average defect density of one to three defects per hundred lines of code"!

My point is that the bugs generated by LLM or human coders are different.

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#417
post #393

Earlier quoted context omitted.

That is how LLM:s should be used today. An expert prompts it and checks the code. Still saves a lot of time vs typing everything from scratch. Just the other day I was working on a prototype and let claude write code for a auth flow. Everything was good until the last step where it was just sending the user id as a string with the valid token. So if you got a valid token you could just pass in any user id and become…

At least for me, I'm fairly sure that I'm better at not adding security flaws to my code (which I'm already not perfect at!) than I am at spotting them in code that I didn't write, unfortunately.

They're different mindsets. Some folks are better editors, inspectors, auditors, etc, whereas some are better builders, creators, and drafters.

So what you're saying makes sense. And I'm definitely on the other side of that fence.

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#418

The commits are revealing. Look at this one: > Ask Claude to remove the "backup" encryption key. Clearly it is still important to security-review Claude's code! > prompt: I noticed you are storing a "backup" of the encryption key as `encryptionKeyJwk`. Doesn't this backup defeat the end-to-end encryption, because the key is available in the grant record without needing any token to unwrap it? I don’t think a non-expe…

Yeah I was disappointed in that one.

I hate to say, though, but I have reviewed a lot of human code in my time, and I've definitely caught many humans making similar-magnitude mistakes. :/

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#419

The commits are revealing. Look at this one: > Ask Claude to remove the "backup" encryption key. Clearly it is still important to security-review Claude's code! > prompt: I noticed you are storing a "backup" of the encryption key as `encryptionKeyJwk`. Doesn't this backup defeat the end-to-end encryption, because the key is available in the grant record without needing any token to unwrap it? I don’t think a non-expe…

That is how LLM:s should be used today. An expert prompts it and checks the code. Still saves a lot of time vs typing everything from scratch. Just the other day I was working on a prototype and let claude write code for a auth flow. Everything was good until the last step where it was just sending the user id as a string with the valid token. So if you got a valid token you could just pass in any user id and become…

I tend to disagree, but I don't know what my disagreement means for the future of being able to use AI when writing software. This workers-oauth-provider project is 1200 lines of code. An expert should be able to write that on the scale of an hour.

The main value I've gotten out of AI writing software comes from the two extremes; not from the middle-ground you present. Vibe coding can be great and seriously productive; but if I have to check it or manually maintain it in nearly any capacity more complicated than changing one string, productivity plummets. Conversely; delegating highly complex, isolated function writing to an AI can also be super productive, because it can (sometimes) showcase intelligence beyond mine and arrive at solutions which would take me 10x longer; but definitionally I am not the right person to check its code output; outside of maybe writing some unit tests for it (a third thing AI tends to be quite good at)

Re: Cloudlflare builds OAuth with Claude and publishes all the prompts

#420
post #381

Earlier quoted context omitted.

> Still saves a lot of time vs typing everything from scratch No it doesn't. Typing speed is never the bottleneck for an expert. As an offline database of Google-tier knowledge, LLM's are useful. Though current LLM tech is half-baked, we need: a) Cheap commodity hardware for running your own models locally. (And by "locally" I mean separate dedicated devices, not something that fights over your desktop's or laptop's…

I realize I procrastinate less when using LLM to write code which I know I could write.

I've noticed this too.

I remember hearing somewhere that humans have a limited capacity in terms of number of decisions made in a day, and it seems to fit here: If I'm writing the code myself, I have to make several decisions on every line of code, and that's mentally tiring, so I tend to stop and procrastinate frequently.

If an LLM is handling a lot of the details, then I'm just making higher-level decisions, allowing me to make more progress.

Of course this is totally speculation and theories like this tend to be wrong, but it is at least consistent with how I feel.

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