Bridged7756

I love coffee. It's good for you, it smells and tastes so good. It wakes you up, and prevents sleepiness after meals. Its stimulant nature is a plus, but not necessarily the main thing.

Not everything is dopamine. Maybe nitpicky on my end but it gets tiresome when everyone is just like dopamine this, dopamine that, when no one really understands neurotransmitters.

He's an idol, didn't you know? Much like his software architecture takes, they'll be taken as gospel.

It wouldn't surprise me the US government is behind it. As it wouldn't surprise me the government of China is subsidizing those OS models. A lot of things at play, and all over a huge bubble.

Crazy how this doesn't register in people's heads. Has the real bottleneck ever been code written and not the review of code and everything involved? Understanding the nuance and implications behind design decisions; strategy.

In any REAL, workload, with good processes, code review makes speed of code generated a moot point. You still move as fast as you can review the code, and no, I won't debate that you can rely on LLMs, a deterministic language predictor, to determine the correctness of code; in the context of the business, and technical implications.

Shit processes. I don't know what places most of those people work at that crap is being merged into production at insane pace. You would expect any serious piece of software would be important enough to have the code be reviewed by at least one human.

Kind of.... I don't know. To get placed such requirements from the top down and not fight back, just take it head on, not even maliciously, don't even oppose it on a technical basis, just be like "yeah, you've now gotta ship faster or you're left behind, so therefore LLMs must be the future!", no critical thought attached. Is this shit coming from experienced engineers?

Preposterous we're relying on "it's better because I feel like", "dudes who don't use it are falling behind at work", "they ask for it in job interviews".

It's significantly slower to use LLMs for some things. The only thing it excels at is generic, broad tasks. Getting the 90% done. I find that it's less cumbersome to get it mostly right and touch it up yourself than to prompt over details like syntax.

More like a bright future being someone's fall guy. The ignorance to think that a large tech giant like Facebook would give a crap about any of those concerns makes this person too politically inept to make it anywhere

I call it FOTM engineering. Let's throw everything out of the window so we can use X novel thing!

I think it's a fine line to walk. At my job what we do is discuss any complex implementation or risky change or blockers in the dev eng meeting. For smaller stuff, or more straightforward solutions, we don't bring it up. If you make it a hard rule to first discuss all tickets, it just seems draconian.

Code review is specifically for code quality, more lower level stuff.

Ditto.

It circles back to the question, is this unimportant enough for me to delegate it to a LLM that might get it wrong? If the answer is yes, why even do it to begin with. If the answer is no, you have to do it manually.

I personally though, see value in this type of automation. Stuff like tag categorization, indexing, that otherwise would've been lost seems like a good fit for LLMs. Whether or not they're an ideal solution and something else like a search engine would've been a better fit, is a different question.

It all boils down to the same thing. Work out a system that makes you function. It's as simple as a PKMS of your liking, the problem is that people are allergic to writing their thoughts down.

Not sure what you're doing then, or what kind of jobs you all work in where you can or do just brainlessly prompt LLMs. Don't you review the code? Don't you know what you want to do before you begin? This is such a non issue. Baffling that any engineer is just opening PRs with unreviewed LLM slop.

I'm a hot dog chef with over 20 years of experience. Credited with inventing 274 hot dog styles. International awards. World renowned and industry figure.

My entire team, very competent hot dog experts, was laid off after a hot dog cooking machine could do what took us 3 months, in just one day. I've been out of a job for 12 months. The reason? All hot dog making has been offloaded to Claudog Hotdog. "Sorry. Hot dog manual cooking is a thing of the past", one recruiter told me.

I'm working as a software engineer as we speak. I keep applying to hot dog related positions but I get no interviews. Even positions significantly below my pay grade and skillset. No one is hiring. Hot dog cooking is over. We are entering a new era.

In C we don't have those issues.

Do you have any examples?. I'm not that acquainted with the pains of deploying Next apps, though I've heard that argument being used.

LOL. Attackers will run these agents but the thousands of maintainers will be so dumb to sit idly and get hammered with exploits. I wonder what the ratio of attackers to maintainers must be, 1:1000 is a fair assessment i take it.

Also LLMs will be used to attack only, no one will be smart to integrate it into CI flows, because everyone is that dumb. No security tools will pop up.

I suppose their market is one click deployments. Maybe for non technical people or people not willing to deal with infra.

You're relying on the public's sentiment as a metric. The public's sentiment is, more than often, skewed, influenced by marketing, or flat out wrong. That is not a good metric to rely on.

Did it ever occur to you that the ever changing goalposts might have more to do with the expensive marketing campaigns of the big LLM providers?

We could talk about what's a measurable metric and what's not. Certainly, we have not much more other than "benchmarks" of which, honestly, I don't know the veracity of, or if big LLM cheats somehow, or if the performance is even stable. The core idea is that LLMs remain able to do exactly what they were able to do back at release; text prediction. They got better in some regards, sure.

Your example is worrisome to me. It should be to you too. You didn't write a literature review, you generated a scaffold of a literature review, with the same vices of LLM-based-writing as anything it does and still needing review and revising. I would hope rewriting to avoid your work be associated with LLM-generation. For better or worse, you still need to, normally, revise your work. For, once again, because this point seems to be difficult to grasp, a text predictor is not a reliable source of information. We make tradeoffs, sacrificing reliability for ease of use, but any real work needs human reviewing: which goes back to my first point. In this example it's doing nothing other than it being a fancy search and scaffolding tool.

The ball is likely to be in the same place because, once again, they're text predictors. Not sentient beings, or intelligent. Still generating text, still hallucinating, probably even more so thanks to the ever increasing amount of LLM-written content on the internet and initiatives like poison fountain doing a number on the generated content.

It's wild to me to make such claims about the rate of change of those tools. You're claiming we'll see exponential gains for those tools, I take, while completely ignoring the base set of constraints those models will, never, be able to get rid of. They only know how to produce text. They don't know, and will never really, know if it's right.

Feedback loops require a deterministic metric for success. You are doing the equivalent of using a slot machine to decide whether something is right or wrong.

I wouldn't say the same but it's pretty close. At this point I'm convinced that they'll continue running the marketing machine and people due to FOMO will keep hopping onto whatever model anthropic releases.

FYI if you have an older kindle you possibly can jailbreak it and getting KoReader on in.

Even newer Kindles can be jail broken, provided they're on the right version.

Mirrors my sentiment. Those tools seem mostly useful for a Google alternative, scaffolding tedious things, code reviewing, and acting as a fancy search.

It seems that they got a grip on the "coding LLM" market and now they're starting to seek actual profit. I predict we'll keep seeing 40%+ more expensive models for a marginal performance gain from now on.

Yeah it seems so. Anthropic has entered the enshittification phase. They got people hooked onto their SOTAs so it's now time to keep releasing marginal performance increase models at 40% higher token price. The problem is that both Anthropic and OpenAI have no other income other than AI. Can't Google just drown them out with cheaper prices over the long run? It seems like an attrition battle to me.

True, let's not criticize those saints of ours.

I've been warning people of Anthropic's astroturfing for a while now. The amount of "Insert latest model/Claude Code is scary. I'm worried about my job" posts, followed by a doom ridden writing about how their job was automated and 30 dudes got fired and the person is pivoting into plumbing or something or working at Mcdonalds, is just too suspicious not to note. Sometimes it's more covert. They don't mention any provider/model. Sometimes there's a subtle insert somewhere in the body, Opus, Claude, etc.

No they don't. To be able to "check one's work", implies that they can be held accountable, that they can tell apart right from wrong, when in reality they're merely text predictors.

If you think an LLMs can check their work, then you are doing a terrible job at writing software. Plain and simple.

They even go as far as "cheating", so tests fail, writing incorrect tests, or straight out leaking code (lol) like the latest Claude Code blunder. Is this the tool the original comment "is using wrong, plain and simple"? Or do you have access to some other model that works in a wildly different way than generating text predictions?

Efficiency doesn't make as much money. It's in big LLM's best interest to keep inference computationally expensive.

I personally think the whole "the newest model is crazy! You've gotta use X (insert most expensive model)" Is just FOMO and marketing-prone people just parroting whatever they've seen in the news or online.

No, you're forgetting the never ending world shattering models being released every couple of months. Each one with 2X token costs of course, for a vague performance gain and that will deprecate the previous ones.

Its enshittificating real fast. They'll just keep releasing model after model, more expensive than the last, marginal gains, but touted as "the next thing". Evangelists will say that they're afraid, it's the future, in 6 months it's all over. Anthropic will keep astroturfing on Reddit. CEOs will make even more outlandish claims.

You raised a good point, what's a good metric for LLM performance? There's surely all the benchmarks out there, but aren't they one and done? Usually at release? What keeps checking the performance of those models. At this point it's just by feel. People say models have been dumbed down, and that's it.

I think the actual future is open source models. Problem is, they don't have the huge marketing budget Anthropic or OpenAI does.