It was probably the other O'Neil, with one L. He has no sense of humour at all.

I could understand bots and mailing lists. The thing I never understood with LinkedIn was how many real people (usually recruitment agents) had apparently spent the time to read my profile and send me a personalised message, yet still thought I'd be interested in a job paying half the market rate for someone with my skills and experience.

I don't know what you mean. Look at the improvement in hiring when you can advertise an open position on LinkedIn and get maybe 100x as many applicants as before! OK, probably 99% of them will be completely unqualified for the role and barely capable of pushing the instant application button, but how is that a problem, really? Surely hiring managers can easily filter them out and no qualified applicant will ever get lost in the noise?

It's like a video I saw on YouTube the other week. Someone was talking all about "skills" for their AI agents and how they'd automated so much of their workflow using them. They started the video by kicking off four different tasks for separate agents to show how productive it was to have all this stuff happening in parallel and how it was so quick and easy to organise.

One of the tasks involved producing an infographic about a certain topic, and the AI duly produced one based on a one-liner prompt, taking only a few seconds of the presenter's time and with no further input from them about the content. The infographic had exactly the level of quality you'd expect from this: a load of boxes and arrows (with some of those arrows starting or finishing floating in space without connecting anything) and some words (a few of which might have been related to the topic mentioned in the prompt).

That infographic was the only substantial output from the whole exercise. It was the worst kind of AI slop imaginable, generated with literally no thought or oversight from the presenter beyond a couple of words about the topic as part of that one-liner prompt. This was probably about the average level of the LinkedIn posts I used to see before I left as well. As you said, I'm not sure you can be a "thought leader" without doing any thinking.

I stopped using LinkedIn when they seemingly decided my account wasn't about me (despite having obvious and publicly verifiable details right there in the description) and wanted me to verify my ID using one of the US-based services with a questionable reputation to get my access back. That's not going to happen, so I just don't use the site any longer.

As far as I can tell, that has made zero difference to my career, and it's one fewer drain on my time. The only thing I have missed is seeing the occasional good news story where a past colleague has been promoted or the like, but I'm not giving up my government-issued credentials to the US-based data harvesting industry for that.

This is fair, but that really just reinforces the point that the article makes. Solo dev is currently different, team output is limited by other factors than pure code output. I've worked on games with literally hundreds of concurrent programmers, and even when you're using something like Unreal Engine and your team is small ( 20 people), you've effectively got all the engine team at Epic generating code for you on a relatively regular basis.

It may indeed be possible for AI to actually make teams faster at some point (even in the nearish future), but right now, it's just more code, which isn't always the best solution.

We are a bunch of neurons meeting action potentials and firing synapses... Hard to see something conscious in there.

(Not that current AI is conscious, just that it's an eventual outcome.)

One of the big problems with this is that it effectively changes the job description of programmers to managers.

You're not just responsible for your own code, you're responsible for telling someone/something else what to do, and then reviewing their work, and then integrating that work and making sure it's correct, because if it gets checked in and it's wrong, you're on the hook for it. But you didn't even write it, so it's harder to understand. Most programmers I know are better at understanding the code they wrote rather than the code they read.

Management is not a job for everyone. I've been a senior programmer and a lead programmer, and it is easier to be a senior programmer that writes complicated, essential systems than it is to be a lead programmer that REVIEWS those systems. If you don't want to do that kind of management work and you just enjoy writing code, you should stay a senior programmer, or move up to some other non-management job. But if you're forced to babysit an LLM, you get ALL THE WORST PARTS of being a lead programmer. You only get the code reviews and none of the intellectual stimulation and enjoyment of creating that thing on your own.

At least a couple comments have pointed out that solo devs use LLMs to great effect, and I'm sure this is true. But if you're not a solo dev, the task is so much different. You're trying to integrate with a bunch of other people and other systems and you're on the hook for something you didn't even write, so you'd best spend the time learning what the code says. It completely defeats the point. When I get an LLM to write my powershell scripts for me, it's because I have no interest at all in learning that scripting language. It takes 2 minutes, usually does a good job, and I can forget about it forever. The development model of asking an LLM to write code that you're responsible for that has to intermingle with the code of dozens of other people and agents sounds like a straight-up nightmare.

Solo development is a different job. The tasks you give to AI are based on what you need, and your own mental model of they code they need to spit out.

Large-scale development is different, because people are different. I've worked on 5 or 6 different game engines over the years, and Unreal is the current one that I'm on. Unreal has its quirks. The rest of our game engine has historical baggage that I need to account for. The interactions between systems are more organic, because not everything can be planned in advance. I worked on Assassin's Creed for 3 games (about 7-8 years?) and we carry over the mistakes of the previous games to the next one, because that engine shipped a game, so it's a known quantity. Sometimes if you're lucky, you get to fix some of those bugs, but then the next games get YOUR bugs, etc.

Solo devs ARE doing amazing work with AI, but solo devs *by definition* don't need to understand the code of 1 or 4 or 50 other people. You can't just check shit in on a big team.

Perfectly reasonable study, because small-scale development is not the same. I have to understand the code of 10+ programmers on a regular basis. Our game engine is involved. The only way for me to learn the code is to use it and step through it.

If you're writing apps yourself, AI is great. It's a teammate that follows your instructions and implements the things that you want. You've already got a mental model of what you need, and it gives that to you. Of course it works for you.

Big codebases are just different. Systems are interdepedent in weird ways for historical reasons, or vendor reasons or weird coworker reasons or whatever. It's not the same task.

There's quite a lot of nuance here, I guess, which isn't unexpected. It's quite a useful anecdote. At the very least, we can't just wave it away like it's not useful. It may generate sub-standard paintings or completely miss the point of art, but if it makes your proofs better, it seems insane to not have it help.

Well, wait, I don't think that actually disproves the claim. I'm not saying it's not impressive, I just don't think it's as novel as you say.

When I ask an LLM to write me code that does something 'novel', it usually does quite a good job. I'm just using the freely available models, but they quite competently write code that is not truly derivative of any other code. If I give them some code of my own that has a bug in it, they'll find the bug and patch it, and that bug is, for all intents and purposes, unique.

You're still seeing a bunch of old patterns rehashed--I presume that other proofs introduce infinity families, and they can iterate through inside a clear logical structure to test whether or not something works. Again, this is impressive work, but I'm not personally convinced that this is 'novel' in terms of the broader corpus of mathematical knowledge. It didn't invent a new field of mathematics to solve your problem.

Even if you didn't prompt it, take a look sometimes at the contemplations of the models, if that's available to you. Before the model even arrives in your hands, it's got stacks of prompts giving it meta instructions, and it then generates prompts for itself to check your work. I think it would be interesting if you ran your experiment again on a new account that's fresh and see if you can watch the chain of reasoning. You might be right, it MAY be doing something TRULY novel, but as I've said, I've got my doubts.

Obviously, you're a mathematician and I'm not; I can't tell you that you're wrong about it if you insist that it is doing something new.

I'm still impressed that the Teams web client can't edit a message with an emoji in it without messing up the keyboard controls and often corrupting the message and losing data. It's had this bug for years. It's literally a messaging app where you can't reliably send messages.

I saw a video by a photographer and he points out that the quality of photos is not the reason to buy a dedicated camera. After all, you can buy a $2000 Ricoh that only takes black and white photos now; the iPhone will, in most circumstances, take 'better' photos, or at least more true-to-life photos.

But a dedicated camera focuses your attention. If you carry your camera, you're concerned with photography. You're not distracted by texts or whatever. And so your photography is likely to be better--you're paying attention to the task in a way that you rarely will with your phone.

I think you're misunderstanding the point: there's a lot of FUD about BE vehicles in north america, not least of which is that battery fires are common, and they may burst into flames at any point. There have been some high-profile examples of badly designed or built cars killing people or lighting on fire, etc. As one would expect, the number of ICE vehicles that this happens to is greater because they're still a larger proportion of all vehicles. But also, as a proportion of their type, more ICE vehicles spontaneously combust than EVs.

The point is that this is not an issue with BEV technology.

Indeed, the intro to the vehicle even says as much:

Emphasis mine.

Because he is not (currently) a dictator, he can't make his own laws. He's limited in what he can do.

Tariffs are one of the few things in which he is mostly able to do unilaterally. When all you've got is a hammer, everything starts to look like a nail.