I’ll even go one step further - I don’t even like saying “Artificial Intelligence”. I think even that anthropomorphizes the machine too much. I prefer “Simulated Intelligence”, and I feel like that describes what is going on much better.
We are, through this process, simulating intelligence. These models aren’t intelligent, but they can simulate it. Every simulation has a degree of fidelity, and we’re not at 100%, not even with the top models. When you think about it in those terms, I find it becomes a lot easier to keep their limitations in mind. Additionally, it becomes easier to remember that this is an algorithm that you are running, and are responsible for, not another being that you can ascribe blame to.
Every time LLM-defenders get upset that people apparently don't understand how LLMs work, why is it they _immediately_ pivot into examples and statements that demonstrate that they don't understand how _people_ work?
"you would be autocomplete too"
"thoughts are just tokens"
etc
You're not helping your case the way you think you are.
I think people have more passion to argue than they have passion to learn. Probably doesn't help that SV culture tells people to hustle so hard that they don't have time to think. Gotta go fast?
15% more price for 25% more battery is worth it alone. Add in that every time I adjust the volume without needing to dig out my phone, and I’ll feel even better.
$20 is a single meal at a fast food restaurant, which I’ll have forgotten about the very next day. This is a much better long term investment.
>Starting September 14, we're permanently raising standard weekly limits in Claude Code by 25% for Pro, Max, Team, and seat-based Enterprise plans. Until then, the current 50% increase will be in place.
> Compared to today, this works out to a 17% reduction in weekly limits on Claude Code. We’re working on exciting changes that will make it feel like you’re getting more from Claude, while having more visibility and control of your usage. Can’t wait to share them.
They are both raising the limits by 25% and apparently reducing them by 17%. I think they mean to say you can do more, but what a terrible press release.
I'm pretty sure they mean going from 150% to 125%, where 1.25/1.50 = 0.83, so they're calling that a 17% reduction. It's less than today, but also more than a limit they made up and then didn't apply.
Exactly this. You still have to understand the abstraction layer the LLM is working at in order to be able to form an opinion about the quality of the code. (If you DON’T care about the quality of the code, there’s always been ways to get an extra 1000% short-term speed improvement by just not giving a shit.)
AI isn’t “a code abstraction layer” any more than Jira is, or the engineer themselves is.
I think "the engineer themselves" is much closer to the abstraction layer I'm referring to.
Imagine for a moment that, rather than using a compiler to translate c++ into assembly, that it instead has to be done by a person on the team. If that were the case, the resulting assembly code would certainly have to be reviewed and assessed before it was accepted.
Why?
Because people can also be leaky, non-deterministic abstraction layers. The only reason that the output of a compiler isn't regularly reviewed (in 99% of cases) is because it's extraordinarily reliable and consistently correct, or correct enough for most cases.
It's not terribly dissimilar from delegating engineering tasks to other engineers. When I ask someone else to develop one component of a larger application, I'm not telling them exactly what lines to write, I'm giving them some kind of structure and they're filling in the rest. The communication to them is above the implementation layer.
Agents are increasingly letting us work at that same boundary. Just because the current state of LLMs requires engineering knowledge to review the result doesn't mean an abstraction hasn't occurred. It speaks more to the current quality of that abstraction than the absence of one.
I think that if LLMs were able to achieve the same consistency as a compiler, most people wouldn't ever bother to check the underlying code it produced. I also think it would be difficult to not acknowledge that LLMs have gotten better at converting natural language into functioning software. The abstraction is certainly not perfect, but it is clearly improving.
Damn, can you imagine a world where it would be so easy to convince one of these companies to stop poisoning the minds of an entire country like that?
Like, I kinda jest, but also kinda don’t. Would that really be so bad of an outcome? The net positives don’t really seem to bear up under all the negatives just… going away.
Yeah, but social media won’t be the only companies that notice. If Australia’s government will do it to them to prop up their local dying industry, they will do it to you, too. If the EU or US tries that, well, those are huge markets and maybe you bend (maybe you don’t!). But Australia is 27 million people, less than 10% the size of those. If they want to get heavy-handed, well, it’s their country, but as recent US actions have shown, other countries’ companies may pick up their ball and go home rather than play with you.
As an Aussie expat who uses Facebook to keep in contact with my friends and family: yes, it would be bad. Social networking tools have real positive effects on the world, let us not forget that.
It's exactly this - "coding was never the hard part" translates more directly to "coding was never was slowing me down". It's nailing down requirements, it's cross-functional team meetings, it's planning the testing and rollout, it's integrating with all the other parts of the product and systems, etc etc etc. Optimizing coding was just aiming at the fastest part of the job already.
So, people are using AI to answer questions about tribal knowledge? Is that really the assertion which is being made here? Because I find that hard to believe.
So, you have different roles and specialties, but you know for a fact that this person should know the answer to your question. I think we're speaking past each other, because this doesn't make sense to me.
I don't presume that someone will have an answer I'm looking for. I'm pleased when they do, but often I just get breadcrumbs, and I have to solve the puzzle for myself.
I'm not GP, but in research very diverse teams are not uncommon. I'm on a team now in which I'm the embedded software engineer / Android SME and my coworker is the 4G LTE/5G NR SME.
I ask him 4G LTE/5G NR questions all the time. I don't know ahead of time if he'll know the answer, but (1) it'd be a solid bet that he does and (2) it's his responsibility to know it given his role.
We are, through this process, simulating intelligence. These models aren’t intelligent, but they can simulate it. Every simulation has a degree of fidelity, and we’re not at 100%, not even with the top models. When you think about it in those terms, I find it becomes a lot easier to keep their limitations in mind. Additionally, it becomes easier to remember that this is an algorithm that you are running, and are responsible for, not another being that you can ascribe blame to.
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