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InitialsDiceBearhttps://github.com/dicebear/dicebearhttps://creativecommons.org/publicdomain/zero/1.0/„Initials” (https://github.com/dicebear/dicebear) by „DiceBear”, licensed under „CC0 1.0” (https://creativecommons.org/publicdomain/zero/1.0/)S
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Joined
3 yr. ago

  • The reaction to sports pseudo-stats is what really separates casual viewers from real fans. It's the only way to raise stakes on otherwise forgettable games.

    "This team is on a 5 game win streak": 🥱

    "This player has never lost an away game in June": 😯🍿

  • Retrofuturism as others have said, but probably more specifically cassette-futurism

  • The post misses a few things:

    1. The ai bubble is currently being subsidized to an unimaginable degree. If you were to actually pay true cost for your token usage, you wouldn't be saving that much over an engineer's salary. Probably even worse once AI companies start to extract a real profit. 95% of companies diving into agentic labor will be in for a rude awakening when they balance next year's budget.
    2. The cost to keep ai useful in its current form has a high floor. Unless you keep up with expensive training, your models will drift. You can only scale your model intelligence with more hardware (roughly). In two years, Claude opus 4.8 will still be bloating context to learn about the latest cloud platforms and libraries. A human engineer will get those passively at no cost to the company.
    3. As the complexity of the task grows the complexity of the ai babysitter must match it. Even if Ai stays cost effective, companies can now save money by spinning up bespoke in-house software to cut out vendors (think observability platforms, task tracking, product design, marketing systems, etc...). No matter how many adversarial reviews and sub agents you spin up, an Ai can't grasp the full context of your company and it's shifting priorities. The software engineer role transitions to a pseudo-sysadmin + product architect.

    C-suites don't want know about software and don't care about non functional requirements (security, availability, audit ability, etc...). They just want to wave a magic wand and have a product appear, which is what Ai provides the illusion of. That's why all current Ai software is garbage, but the smarter companies will catch on

  • I don't doubt it's possible to get better consistency but the juice is really not worth the squeeze for me. You end up churning through huge expensive models, orchestrating sub agents, writing out boilerplate hand-holding instructions ("please don't break this, stop trying to commit to main, please lint ffs...").

    I don't use it for Java but that would make sense with rigid enterprise patterns and VeryVerboseNamesThatAreEasierForAModelThanAHumanFactoryClazz {...

    I don't think our career is boned, moreso that all juniors trying to get in are boned. Everyone who knows what going on transition to a more hands-off architect role.

    But like I said, our tokens are heavily subsidized right now. When they pull the rug, code monkey jobs will start to get listed again (with lower salaries of course).

  • Things I've realized while working with AI (Claude code):

    • It's fantastic for very small macros and medium length scripts. Think dev ops stuff, pre-commit hooks, transforming data. Keep it small enough to manually review and something you can run without destroying anything important. This can massively boost your codebase QoL. [Double bonus for not wasting tokens to solve the same problem over and over]
    • It's decent-to-good at debugging but not consistent with fixes. It can find some utf encoding edge case that might have taken you 1hr+ but suggest the dumbest bandaid fix you've ever seen. Also very good at spinning up unit test suites for basic edge cases.
    • Due to obvious training bias, it's pretty good with common libraries and cloud platform infrastructure. It could probably help with writing a complex cron call, debugging regex or fixing an IaC config. On the flip side it won't bother to use the latest package version or know your niche/new library.
    • It does better with greenfield because exploring your codebase introduces a ton of bias. It might try to fit in an ugly hack when a refactor to simplify everything is way easier.
    • It's absolutely garbage with UI, just throws the most disorganized HTML together that isn't reactive or reusable. OK enough for ugly internal stuff but God help anyone relying on it for that.
    • This is setting up to be the biggest rug pull in history. People that buy into it heavily just to save a couple bucks on engineer payroll are going to be fucked when they start ratcheting up the token price.

    All in all it can be useful when used with care but will never be a magic bullet.

  • Someone remake this but with Good-Bad-Fanservice

  • Chili garlic tofu

    Though to be honest I don't usually use a recipe or cook anything. I cube a block of soft/silken tofu, dump on some chili oil, add some kind of vinegar (and maybe sesame oil if I have it), and eat it raw and cold.

    You could probably do it with any kind of sauce you like and put it on rice if you're feeling fancy

  • Photos are the same as most other data, you can store them pretty easily long-term in a physical medium. Of course, capturing an image is much easier and more convenient with a digital device, but that doesn't mean it has to live digitally indefinitely. It's simple enough to have an instant digital camera with a built in printer and access to a high quality scanner.

    If you held a gun to my head, I could pick out a few dozen personal photos that I own that are worth saving physically. If you allowed me a modern flash drive's worth of storage (64-128GB, ~5000 good quality images), I could pretty easily store every picture worth a second look from my entire lifetime.

    Apple's marketing driven perception that every single person needs a cinema quality camera (and cinema sized storage) in their pocket is ludicrous. Only a tiny fraction of people actually truly need that. Let them borrow that gear from a library if we want to preserve fair access.

  • To be honest I don't have any personal digital information that I give a shit about. It's value is only derived from its ability to identify + track me, either for my convenience or for the highest bidder's. Computational liberty is only an issue because we've made everything digital by default and that mindset has leaked into critical social functions (taxes, law, logistics, healthcare, etc...).

    Software and data bloat is more astronomical than most people realize. Only about 10% of persisted data is ever touched again (don't look up the ecological implications). Amazon could capture 90% of all compute hardware and the entire human race could get by just fine on 10%. We wouldn't have access to niceties like app stores full of niche apps, 24MP phone cameras, 4k movies, 10 sluggish layers of software abstraction, 15 years of photos you never look at, etc...

    But you could run a simple message server on basically any scrap of IoT e-waste. A highly available static website can be hosted with an old phone and a solar panel. Any device (fridge/watch/calculator/pregnancy test) can run Doom. All of Apollo 11's source code is a fraction of the size of most web pages.

    We're continously expanding our hardware usage for infinitesimally small gains. We should demand that our governments legislate digital austerity for dozens of reasons, just pick what resonates best for you. Personal privacy, energy usage, ecological damage, corporate capture, information rot, brittle supply chains, national security, etc...

  • Crazy that companies will do this shady stuff with client side code. At least it was slightly obfuscated at first, but that's just incompetent fraud to leave it so obvious that a self professed non-software engineer (though clearly a smart guy) can read it and deduce what's happening. Throw a tiny bit of random noise to the stepdown logic and it becomes much harder to find and reproduce as proof.

  • My shameful secret is admitting that LLMs are great for things like getting comfortable with a programming language. They're generally trained on the same publicly available samples as these courses and the conversational extrapolation is great for identifying concepts you forgot the technical terms for (ie. "How would I do this in python: [Java code]")

    Vibe coding sucks, but walking through some examples with an LLM and a REPL can save hours of navigating docs or Hello World blog posts.

  • Couple of reasons of varying importance:

    • Security. Even when you limit operations or table access it's very easy to mess something up. Some new employee starts storing sensitive data in the wrong place or a db admin accidentally turns off the wrong permissions, etc...
    • It's secretly more overengineered than a standard api despite looking simpler. If your app needs extremely robust query capabilities then you probably have a use case for an entire analytics stack and could use an open source option. Otherwise your users probably just need basic search, filtering, sorting, etc...
    • Ungodly, Flex Tape tier tight coupling. Part of the purpose of an api is to abstract away implementation details and present a stable contract. Now if you want to migrate/upgrade the database or add a new data source, everyone has to know about it and it's potentially a major breaking change.
    • Familiarity. If someone else steps in to maintain it it's much easier to get up to speed with a more standard stack. You don't need a seven layer salad of enterprise abstraction bullshit, but it's useful to see a familiar separation of auth, queries, security, etc...
    • Having the option to do business logic outside of the database can save countless headaches. Instead of inventing views or kludging sprocs to do some standard transformation, you can pull in a mature library. Some things, such as scrubbing PII, are probably damn near impossible without a higher tier layer to work in.
    • Client support. Your browser/device probably has a few billion options for consuming a REST/HATEOAS/graphql/whatever api. I doubt there's many direct sql options with wide support.

    I probably wouldn't do it outside of a tiny solo project. There are plenty of frameworks which do similar things (such as db driven apis) without compromising on flexibility, security or features.

  • Brackets are infinitely easier because any IDE (and most text editors) have a dead simple linting plugin which auto indents for you and lets you know when you fucked up. Your editor can barely do anything with whitespace only because everything is valid syntax.

    Also lemme take this opportunity to say fuck yaml for exactly this reason.

  • Maths

    Jump
  • My dyscalculic ass trying to remember what 50% of 6 is

  • That's a great question! I'll be happy to help you count the lights. I see five lights.

    Here are a few ways you can improve indoor lighting:

  • Car Trek

    Come on, it was right there...

  • This is such a weird essay. Almost nothing about the function of our modern world is related these ancient empires and small modern dissolutions. Yes, life in an agrarian society probably improved somewhat when your food was no longer being taxed to feed an army.

    In our global economic reality, basically no country is self sufficient. We don't have a 90% rural population ready to adapt to subsistence farming. Even putting aside reductions in QoL and luxuries, nearly 60% of global population lives in densely populated urban centers. Once the logistics supplying these centers break down, the surrounding areas don't have carrying capacity to support them (much less so when you account for dependence on fertilizer and pesticides).

    When things fall apart on a large scale in 2025 we don't get to revert to a humble bucolic life, at least not until a ton of people die

  • Out of curiosity, what is your experience/usage like with this? Spotify is very easy to justify if you heavily use some of their features because there's not a way (that I know of) to replicate them. For example:

    • Shared playlists
    • Universal links directly to songs
    • Playback control from a second device
    • Group listen/jam
    • Zero overhead for search and discovery. From someone mentioning a band you can find, sample, and add to a playlist in 30s or less
    • Public playlist discovery
    • Easy crawling. Eg. browsing from Song -> Featured Artist -> Album -> Record label -> Related Artists etc...

    From my usage, sacrificing a majority of those is a non-starter because my Spotify usage has become more than mp3 hosting and organization.

  • Ask Lemmy @lemmy.world

    What are your favorite RSS feeds?