steve_adams_86

> They suck ass at troubleshooting systems

Given the right tools and instructions I find them to be consistently superhuman. It's unreal.

I have an automated system responding to issues occurring on oceanconnect.ca, and every single diagnosis has been correct for months. Of course I still verify, I tune solutions, I review everything. But it's right. It's not a trivial system. It has a fairly large frontend, a large-scale model processing pipeline on the backend, a fairly complex database, and a queue for getting new data into the system. Claude does a stellar job of navigating and understanding problems, even when they're not 'real' or as they initially appear to be; things like quirks in old versions of Safari, or the model pipeline fails due to data integrity issues from the providers.

I've rarely encountered cases where I need to steer a frontier LLM much when troubleshooting. They're exceptional.

Is anyone else finding that it doesn't pick up Claude Code agents? My Agents pane stays empty no matter how many instances I start and work in. Appears to continue to work fine in herdr, though.

I don't know, strange things happen. The other day I had to rotate a bunch of credentials because a coop cloned a private repo, made it public, and checked in a .env file with production database credentials... 5 years ago. And they still worked. No idea how that wasn't exploited, honestly.

(I wasn't around for this, I just found it)

A little sad in a way, but this seems like the right call. I haven't used Pico in a very long time, and I don't think I'd choose it today.

My comment wasn't meant to imply anything of the sort. I think you can adopt AI aggressively without being a total dickhead, more or less. Doing it at direct expense to others' well-being is clearly a problem. I'll read the nested article to see how wrong I am, but the initial post that's linked didn't seem to indicate Proton have gone to the dark side. I'd need more evidence to judge them like that.

I wasn't aware of cruelty; just that they are opting to use AI. The tracking of AI produced code is tough; I have that at my org too, but it's more so to get a sense for who's using it, so we can find out why, help them use it better, etc.

I also only read the initial post and not the entire 404 article. I suppose if I could edit my comment and have it maintain some posterity, I'd say something like "going all-in on AI doesn't make you evil", but I concede that these guys could certainly be assholes if there's more to it (I'll read the nested article).

This doesn't make them bad guys, though.

edit: stating this based off of the linked post, but will read the article linked in the post as well.

edit edit: Okay, yeah. This seems like an awful place to work.

Where I work, we take on way more exciting and ambitious projects than we would have when I was hired. It's exhilarating at times. Genuinely, AI in general (not just LLMs) has radically transformed the types of work we can conceivably pursue and deliver on. We're an NGO so we have different staff than a regular tech company, but we're highly tech-driven. I don't doubt that this is the case at many orgs like ours.

And it's measurable. We don't just feel more productive; we get grants, we build systems, and we make plans we simply couldn't have before.

In trying to understand how this was possible, I read a bit about how the underlying system and safety protocols work. It's remarkable how much the operators got wrong here. My instinct was to think that this was bad engineering, but no, the system's only flaw here is that it allows operator discretion in degraded security modes. In this case, wow, they made some really poor choices. Unreal.

Likewise, I was left feeling like this is just more fodder for the circus. Tesla's stock is attention-driven more than anything at this point. By that measure, this car makes sense. By any other, it's more grift and gimmick.

That's okay, though. Agents are an abstraction no one will really need to understand. They will still benefit from it when they press a button to 'do the thing' which previously required a human.

> Maybe this time is different

It is in the sense that you performed tasks for people, and knew which tasks needed to be performed. The advent of agentic programs now means those same tasks can be deduced by the agent and also performed by it. There's a very thin moat between you and that, now.

Rather than attempt to be random, knowing that I'm not, I wanted to see how well it can predict Math.random:

    setInterval(() => {
      const num = Math.round(Math.random() * 10);
      const ball = document.querySelector(`.typed-pad .ball-${num}`);
      if (ball) {
        ball.click();
      }
    }, 1000);

This isn't very interesting, but it scratched an itch I had to see what would happen.

    The house's record

    The house called 18 of your 190 scored numbers: 9%.

    Blind guessing would average about 21.1 of them (11%).

    Only 1 of the 206 people in a psychology study was more random than you. The house found you extremely hard to read.

I really want to know who was more random than a RNG

I understood what it was after a moment of looking at it, but had to sit and wonder why they thought it was a good idea. What am I missing here? This looks weird.

They did push it for gaming at one time, but it fizzled out since then. At one point Arcade was pushed pretty hard, and they presented Apple TV as the premier place to play it.

I've used it for a total of a few hours in many years, almost exclusively for mini motorways. It never made sense to play over the Switch or PS5. I'm not sure who's using it.