I didn’t see Claude 4 Sonnet in the tests and this is the one I use. And it looks like about the same category as o4 mini from my experience.

It is a nice tool to have in my belt. But these LLM based agents are still very far from being able to do advanced and hard tasks. But to me it is probably more important to communicate and learn about the limitations about these tools to not lose tile instead of gaining it.

In fact, I am not even sure they are good enough to be used to really generate production-ready code. But they are nice for pre-reviewing, building simple scripts that don’t need to be highly reliable, analyse a project, ask specific questions etc… The game changer for me was to use Clojure-MCP. Having a REPL at disposal really enhance the quality of most answers.

Search engines are able to help me with 100% of work.

It's a rubber ducky that talks back. If you don't take it seriously, it can reach the level of usefulness just above a wheezing piece of yellow rubber.

It's literally the most common answer on stackexchange.

Sadly, the lack of junior devs means my job is probably safe until I am ready to retire. I have mixed feelings about that. On the one hand, yeah for me. On the other sad for the new grads. And sad for software as a whole. But software truely sucks, and has only been enshitifying worse and worse. Could a shake up like this somehow help that? I don't see how, but who knows.

Sucks for today's juniors, but that gap will bring them back into the fold with higher salaries eventually.

In the worst case scenario where you ask it a coding problem for which there is no solution—it's just not possible to do what you're asking—it may nevertheless engage you indefinitely until you eventually realize it's running you around in circles.

Exactly this, and it's frustrating as a Jr dev to be fed this bs when you're learning. I've had multiple scenarios where it blatantly told me wrong things. Like using string interpolation in a terraform file to try and set a dynamic source - what it was giving me looked totally viable. It wasn't until I dug around some more that I found out that terraform init can't use variables in the source field.

On the positive side it helps give me some direction when I don't know where to start. I use it with a highly pessimistic and cautious approach. I understand that today is the worst it's going to be, and that I will be required to use it as a tool in my job going forward, so I'm making an effort to get to grips when working with it.

Well, this kind of AI won't ever be useful as a programmer. It doesn't think. It doesn't reason. It cannot make decisions besides using a ton of computational power and enormous deep neural networks to shit out a series of words that seem like they should follow your prompt. An LLM is just a really, really good next-word guesser.

So when you ask it to solve the Tower of Hanoi problem, great it can do that. Because it saw someone else's answer. But if you ask it to solve it for a tower than is 20 disks high it will fail because no one ever talks about going that far and it flounders. It's not actually reasoning to solve the problem - it's regurgitating answers it has ingested from stolen internet conversations. It's not even attempting to solve the general case because it's not trying to solve the problem, it's responding to your prompt.

That said - an LLM is also great as an interface to allow natural language and code as prompts for other tools. This is where the actually productive advancements will be made. Those tools are garbage today but they'll certainly improve.

My productivity has at least tripled since I started using Cursor. People are actually underestimating the effects that AI will have in the industry

Ok, but there's no "AI" involved in this process.

The hard problems are the only reason I like programming. If 90% of my job was repetitive boilerplate, I'd probably be looking elsewhere.

I really dislike how LLMs are flooding the internet with a seemingly infinite amount of half-broken TODO-app style programs with no care at all for improving things or doing something actually unique.

i would guess a lot of the pro ai stuff is from corpos given the fact good press is money to them.

Probably because nobody really wants to read absolute nonsense.

there aren't that many, if you're talking specifically LLMs, but ML+AI is more than LLMs.

Not a defence or indictment of either side, just people tend to confuse the terms "LLM" and "AI"

I think there could be worth in AI for identification (what insect in this, find the photo I took of the receipt for my train ticket last month, order these chemicals from lowest to highest pH...) - but LLMs are only part of that stack - the input and output - which isn't going to make many massive breakthroughs week to week.

Well, I recently did kind of an experiment, writing a kid game in Kotlin without ever using it. And it was surprisingly easy to do. I guess it helps that I'm fluent in ~5 other programming languages because I could tell what looked obviously wrong.

My conclusion kinda is that it's a really great help if you know programming in general.