I've been at ESUG a few years ago. I can definitely recommend it if you want access to all kinds of Smalltalk and Pharo experts, and listen to all kinds of topics that contain a high amount of expertise.
I remember that I wanted a visual step by step debugger for a visualization library [1]. I was lucky enough to find the library maintainer himself. He liked the idea, and within just 30 to 60 minutes we programmed a prototype in (this was around ChatGPT 3.5, so pure hand coding).
Isn't the author of The Culture series an interesting answer to this? I only read The Player of Games. To me it was fun to read that you could just play games your whole life.
I have a bit of both. Most of my thoughts aren't really originally because I'm not playing around and go wild. This is what LLMs seem to be lacking a bit.
Most of my thoughts are things that other people have come up with as well. Aka it feels like I'm just predicting the next token based on the data that I already have.
It's only when I go to places such as "what if life at the speed of light is possible, what would that look like?" that I get to places I personally find somewhat novel. It's almost a different dimension for these guys of course since a million years can feel like 10 years to them. Yet, they're moving so fast, but time-wise they move so slow, maybe even too slow for us to understand that anything can be alive at that speed (I'm not claiming there's life at light speed by the way, I just think it's fun to imagine that there is).
My message to the world is that LLMs should be able to point anything they see in the application they're in or even the whole computer (if you give it that kind of access).
For web apps, WebMCP is a way where you can make a frontend way more discoverable to an LLM rather than that it is going to read all your code. I sometimes create this in my apps at home and sometimes in my apps at work and it makes LLM assistants way more usable. It also helps if they can highlight certain things of a visual.
We humans can do this too on paper. We can point at something, we can highlight something with a marker. Why not give an LLM these capabilities as well?
> I don't even see salary or what your debt is as "personal information" (am Swede not in Sweden), personal information is stuff that no one else would need to know. What people earn affects not just people around you and others in the workplace but also society at large, makes a ton of sense for that stuff to be public.
In a high trust culture I get this. But what about if you're in a low trust culture with quite some "not so orderly behavior" (if you will).
I think it's the opposite, the mismatch of information availability between employer and employee makes that a low trust culture, which is addressed by making that information public instead. If it was a high trust culture, employees would trust their employer pay them fairly, but they don't, hence this information deserves to be public.
Yep, and this applies to several other types of crimes too. Countries with the very lowest rate of reported rape, domestic violence and so on tend to be horrible for women, because the reason for low rate is that they are too afraid to report the crimes.
That it says something about the human brain seems to be about right. If you have 8 planets and 8 children it means you've classified certain things you've seen to be part of the same concept and you group them together.
> Clipboard history, but also just "oh you have these windows open while working on this task".
I feel this. When I first got to learn what a workspace was (in Eclipse, of all things), and I really drilled down into the English meaning of it (I'm Dutch), I thought about exactly what you're describing right now.
There's also a thing of wanting "http referer"-style things but at the desktop. I want things that tell me _from where_ I clicked into a page in the browser (like "oh you got here from Slack (at this spot)"
Desktop history, clipboard history... all associated to certain contexts. Would be quite nice IMO
Yea I get the bearishness from my own personal experience.
Personally, I use LLMs for a lot of things. Oftentimes, I'm a think out loud type of person so even having something that feels like a rubber duck, but more competent, is already amazing for me. And LLMs are a lot more competent than a rubber duck.
But especially sometimes I've noticed that LLMs can be unbelievably stupid. It recently happened a few times with Fable 5.1 as well. Ultimately, I think it comes down to that LLMs can't think broadly. In software development one can usually see this too. For example, a whole app might be built by an LLM and it didn't spend a single token thinking about security because the prompter is at the level of "build a dating app for dogs, make no mistakes". Now you have a dating app for dogs that is insecure.
Since I prompt for almost everything in my life to have an LLM as a sounding board, I'm usually not an expert either. I've noticed LLMs are amazing at "bulk search engine information aggregation" (or whatever you want to call it). So if I need something from the Dutch government, I can find it way more quickly. But oftentimes I've noticed that going for a walk and thinking about a particular thing I'm facing is a more effective way of finding a good solution.
Other times times they are not incredibly stupid, but can't form a strong opinion. This usually happens when I'm tackling a wicked problem [1]. When that's the case, prepare for LLMs to sway with you for every small change in your opinion that you ever will experience.
So I agree: drop in replacement for knowledge workers? No. Rigorous specification is usually needed yes. Though, the small win here is that it doesn't always need to be as rigorous as programming is and it can happen in natural language. It depends on the topic/problem being tackled.
I really like them as UX tools though. Amazing for interactive prototyping and requirements elicitation. And that also corresponds with what the author is saying. Though I find it a bit of a disservice saying "just 3". You know how hard requirements elicitation is? It became a whole lot easier thanks to LLMs (I might change this opinion in a year, haha, but this is the opinion I hold now).
Don't see how you can trust the output on matters you don't understand, especially if they're more serious, if you already note instances where they're plainly stupid. You're literally falling for the grift.
I remember that I wanted a visual step by step debugger for a visualization library [1]. I was lucky enough to find the library maintainer himself. He liked the idea, and within just 30 to 60 minutes we programmed a prototype in (this was around ChatGPT 3.5, so pure hand coding).
[1] https://github.com/pharo-graphics/Roassal
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