sobchak

Newer vehicles typically have ceramic stock (well at least my newest car did), but I think "organic" were standard until relatively recently. There's pros and cons to each.

Yeah, Apple's stock went up 5% yesterday because of Tim Cook's meeting with Trump (where he promised $600 billion investment in US manufacturing), and Apple's saying they won't be affected by the new 50% tariffs on India. There are also ghost factories that were built during Trump's first term.

You guys have pensions?

Private property (as opposed to personal property) is property owned by individuals or entities that generate profits from others' labor, and is abolished under communism. So, no, you can't take someone's personal PC (or any personal property). I'm not that deep into communist theory or thought, so not sure if "free markets" can exist under communism (I know money and states don't exist), but I know there are theoretical socialist societies where free markets exist (market socialism, anarcho-syndicalism, etc).

I never understood the popularity of AWS. It's much cheaper using VPSs and even dedicated servers sometimes. I've worked on very cost-sensitive projects where I rolled our own highly-available k8s and postgres clusters on dedicated servers and VPSs and saved the company a shit load of money. Only used the "cloud" to store backups (Backblaze). There's tons of other options other than major "cloud" providers, and they're often much cheaper.

I'm trying to get a job (and failing) after a layoff at the end of last year, and maybe 1/4 of the job postings I see mention you need to be familiar with "AI." So, yeah, in interviews, when AI is brought up, I try to be pro-AI, but cautious. I even messed around with stuff like LangChain/LangGraph because I see so many job postings that require stuff like that, but the results are underwhelming. Now I'm seeing a lot of job postings that require experience in Azure's cloud AI stuff, but I'm not paying to learn that. I have "real" ML experience, and it frustrates me that many of the responses I get back from applications just want me to glue shitty LLM tools together.

Hmm, a lot of my career was done doing embedded programming, where mistakes in production are very costly, and software/hardware has to be released with basically zero bugs, so that may be where the disconnect is. I still think bugs and technical debt are costly elsewhere too if the product is going to have a long lifecycle, but executives are just dumb.

For open source stuff, Codeberg is good. For private stuff, just git + ssh is good. Gitlab and Bitbucket are fine for corporate stuff, I guess. An organization could just self-host a Forgejo (or Gitlab) instance as well.

I keep hearing stuff like this, but I haven't found a good use or workflow for AI (other than occasional chatbot sessions). Regular autocomplete is more accurate (no hallucinations) and faster than AI suggestions (especially accounting for needing to constantly review the suggestions for correctness). I guess stuff like Cursor is OK at making one-off tools on very small code-bases, but hits a brick-wall when the code base gets too big. Then you're left with a bunch of unmaintainable code you're not very familiar with and you would to spend a lot of time trying to fix yourself. Dunno if I'm doing something wrong or what.

I guess what I'm saying is that using AI can speed you up to a point while the project accumulates massive amounts of technical debt, and when you take into account all the refactoring and debugging time, it results in taking longer to produce a buggier project. At least, in my experience.

I think part of it is because they think they can train models off developers, then replace them with models. The other is that the company is heavily invested in coding LLMs and the tooling for them, so they are trying to hype them up.

Chamoy on fruit or candy is awesome.

I've tried Copilot for a while and played around with Cursor for a bit. I was better and faster without Copilot due to sometimes not paying enough attention of the lines it would generate. This would cause subtle bugs that took a long time to debug. Cursor just produced unmaintainable code-bases that I had no knowledge of, and to make major changes, would be faster for me to just rewrite it from scratch. The act of typing gives me time to think more about what I'm doing or am going to do, while Copilot generations are distracting and break my thought processes. I work best with good LSP tooling and sometimes AI chatbots (mostly just for customized example snippets for libraries or frameworks I'm unfamiliar with; though that has its own problems because the LLMs knowledge is out of date a lot) that don't directly modify my code.