Where? How do I know you're not pulling from some shady repository?

I don't know any student that really uses it now.

If you want actual good advice: go to a doctor.

Don't go to a chiropractor, don't go to hackernews. Go to a doctor. You can either start with a physical therapist in your area or start with your primary care doctor to get a referral.

I'm assuming you're in the US, so I know it's expensive but this will genuinely shorten your life span if you let it get significantly worse.

Just cause you're using an LLM doesn't mean you're "vibe coding".

I regularly use LLMs at work, but I don't "vibe-code", which is where you're just saying garbage to the model and blindly clicking accept on whatever is spit out from it.

I design, think about architecture, write out all of my thoughts, expected example inputs, expected example outputs, etc. I write out pretty extensive prompts that capture all of that, and then request for an improved prompt. I review that improved prompt to make sure it aligns with the requirements I've gathered.

I read the output like I'm doing a deep code review, and if I don't understand some code I make sure to figure it out before moving forward. I make sure that the change set is within the scope of the problem I'm trying to solve.

Excluding the pieces that augment the workflow, this is all the same stuff you would normally do. You're an engineer solving problems and that domain you do it in happens to involve software and computers.

Writing out code has always been a means to an end. The productivity gains if you actually give LLMs a shot and learn to use the tools are real. So yes, pretty soon it's going to become expected from most places that you use the tools. The same way you've been expected to use a specific language, framework, or any other tool that greatly improves productivity.

When I write my prompts, I literally write an essay. I lay constraints, design choices, examples, etc. If I already have a ticket that lays out the introduction, design considerations, acceptance criteria and other important information, then I'll include that as well. I then take the prompt I've written and I request for the model to improve the prompt. I'll also try to include the most important bits at the end since right now models seem to focus more on things referenced at the end of a prompt rather than at the beginning.

Once I do get output, I then review each piece of generated code as if I'm doing an in-depth code review.

I just tried on Chrome and Firefox on desktop, and the iOS YouTube app. Both show me a message saying "Recommendations are off. Your watch history is off, and we rely on watch history to tailor your Shorts feed. You can change your setting at any time, or try searching for Shorts instead."

I'll also clarify, sometimes if you click on a shorts video that you searched for manually, a few related videos will be queued, but then the feed will try up and the watch history message will display again.

Do you have left over watch history from years ago you've never cleared, and maybe shorts is enabled since it uses that...?

If you actually wanted to test this, you'd need to run Claude Opus 4.6 locally, which is not really possible.

The metal slug games are also on the app store. It's a bit hard to play but you can set infinite lives and it's a fun way to kill some time while waiting around somewhere.

I know many companies using Copilot have no contract work with the government, but this is the Trump admin we're talking about. They want to send a message.

Also, maybe I'm misunderstanding what this library is for, but is this really a good application of AI? I'm getting reminded of gherkin + cypress but without the test actually being embedded in the code. I feel like I'd rather use AI to write the BDD test using gherkin rather than prompt the AI to figure out what test behavior I actually want.

I realize I'm coming off a bit pessimistic here, but I'm just trying to explain where my thoughts are so you can hopefully clarify things a bit for me here because I feel like I'm missing something about what you're trying to accomplish with this project.

My company uses Github Copilot. We have a very specific enterprise agreement that states that data does go to Microsoft's servers where it gets processed in an ephemeral environment and wiped after 3 months.

I'm guessing Anthropic has something similar in their agreements. Now, if you have some proof that Anthropic is stealing highly confidential and/or trade secrets, that'd be good to see, but also whomever is throwing that kind of information into an off-premises and non airgapped model is just asking for a data leak.

Jumping to an invite only network isn't the most ridiculous idea imo.