zlacker

>>tablet+(OP)
I’d love to see the authors of effusive praise of generative AI like this provide the proof of the unlimited powers of their tools in code. If GAI (or agents, or whatever comes next …) is so effective it should be quite simple to prove that by creating an AI only company and in short order producing huge amounts of serviceable code to do useful things. So far I’ve seen no sign of this, and the best use case seems to be generating text or artwork which fools humans into thinking it has coherent meaning as our minds love to fill gaps and spot patterns even where there are none. It’s also pretty good at reproducing things it has seen with variations - that can be useful.

So far in my experience watching small to medium sized companies try to use it for real work, it has been occasionally useful for exploring apis, odd bits of knowledge etc, but overall wasted more time than it has saved. I see very few signs of progress.

The time has come for llm users to put up or shut up - if it’s so great, stop telling us and show and use the code it generated on its own.

>>grey-a+ba
Approximately speaking, what do you want to see put up?

I ask this because it reads like you have a specific challenge in mind when it comes to generative AI and it sounds like anything short of "proof of the unlimited powers" will fall short of being deemed "useful".

Here's the deal: Reasonable people aren't claiming this stuff is a silver bullet or a panacea. They're not even suggesting it should be used without supervision. It's useful when used by people who understand its limitations and leverage its strengths.

If you want to see how it's been used by someone who was happy with the results, and is willing to share their results, you can scroll down a few stories on the front-page and check the commit history of this project:

https://github.com/cloudflare/workers-oauth-provider/commits...

Now here's the deal: These people aren't trying to prove anything to you. They're just sharing the results of an experiment where a very talented developer used these tools to build something useful.

So let me ask you this: Can we at least agree that these tools can be of some use to talented developers?

>>steego+ee
I think that experiment was very cool, but I will say that the OAuth2.0/OIDC protocol is very well documented and there are tons of tools already built around it in multiple languages.

I implemented the OAuth2.0 protocol in 3 different languages without a 3rd party library - entire spec implemented by hand. This was like ~2015 when many of the libraries that exist today didn't back then. I did this as a junior developer for multiple enterprise applications. At the end of the day it's not really that impressive.

>>jcon32+Ai
Three weeks ago I did basically the same thing as the author of the Cloudflare story, but I did it with my own open source tool. I went into the experiment treating Claude Code as a junior engineer and guiding it on a feature I wanted implemented.

In a single Saturday the LLM delivered the feature to my spec, passing my initial test cases, adding more tests, etc…

I went to bed that night feeling viscerally in my bones I was pairing with and guiding a senior engineer not a junior. The feature was delivered in one day and would have taken me a week to do myself.

I think stories like the Cloudflare story are happening all over right now. Staff level engineers are testing hypotheses and being surprised at the results.

Oauth 2.0 doesn’t really matter. If you can guide the model and clearly express requirements, boundaries, and context, then it’s likely to be very useful and valuable in its current form.