Interesting. Because I have a much harder time typing on my Pixel. In fact, I hate it. I wish I had a blackberry.
When I use iOS devices, it feels better but I don't use them enough to have used them in anger. Ok, well, yes they have made me angry but for other reasons than the keyboard hence why I'm on Android lol.
I used a Clicks keyboard with a folded Moto Razr for a while and it was Blackberry-esque. The keyboard is a little narrow compared to the Blackberries of yore, though. I'm somewhat hopeful about the Clicks Communicator which is wider, but sadly still only a four row keyboard.
To be clear, I only kind of recommend the keyboard. I stopped using mine after a while because of how awkward it was with the Razr unfolded and never actually found it faster or more accurate than the on screen keyboard.
I've been running Hermes inside a remote docker container connected to Slack bound to a Codex account. It's actually pretty great, I prefer this approach for a lot of things. Because it's in a Docker container I have 100% control over the configuration. It may do some crazy stuff, but I know it's not going to start exfiltrating my AWS SSO tokens or SSH keys from my laptop.
I'm frequently listening to music or a video in the background. Join a zoom call early because I don't want to be late, instant AM radio. You can argue I shouldn't do this, I'll argue that it shouldn't matter and should just work. It's 2026, not 1926.
That's not true at all of the corporate world. If your team is mass producing slop and you don't have processes in place to get it under control, you've got a big problem on your hand.
If any engineer sent me a 20,000 line refactor I'd immediately reject it and tell them to go back and start making changes incrementally at minimum. More likely I'd force them to have a whole design discussion with the team to make sure that what they are doing even makes sense.
What happens if they push out slop that significantly increases your infrastructure costs?
What happens if they push out slop that significantly increases the number of bugs or outages?
What happens if they push out slop that has no observational metrics, dashboards, or tooling?
In every case you push back on the team and make them fix their shit. I don't care if they are using LLMs or not. They are responsible for their work being sufficient quality. If they aren't meeting those standards, then they need to step it up.
I don't disagree with you on this, I worked my whole life in corporate and haven't worked as a OSS maintainer before, though I will _and already did_ reject PRs way less than that, I speak for myself and my team here and it's unrealistic to ship a single PR as complex as this, we usually plan features as tech designs with PRs of no more than 500 LOC, but that doesn't mean we could never have a 20k PR at all. in my experience, those huge PRs are usually the simple ones where most of it is just noise. I did one recently and moved the UI library in one of our old codebases three major versions up to the very latest, although it was 20k lines of changes, all of it is just mechanical chanes, renames, codemod stuff, test fixes, snapshot updates, ...etc. and it's not realistc to split this into multiple smaller PRs as this can bring other complications like having multiple versions of the same UI library in the codebase, which could cause more problems than it fixes, AI helps with that kinda work a lot and I would've never been able to do this migration is such a short time without it.
despite that, reviewing it was a UI challenge, not code, with UI libraries, the breaking changes are usually in the UI so you can't see it from the code, and we did have a special process to review it, although on the code side, Github was a nightmare to deal with reviewing this PR, we noticed that github was the bottleneck here since it lays out the code changes without much context and is already hard to navigate and stuggles with huge PRs, the review surface and the developer experince on github was horrible, and that's why I suggested you look for better alternatives, there are a lot out there and all of them are free for OSS so why not try them?
How do you handle them? I'm not facing this problem as the team I work with is very senior and have good taste and discipline. But I can imagine it will be a problem at some point, and I frequently have to personally tell Claude to rewrite it's vomit in English. That's probably step one for people submitting poorly written PRs, reject them until they are written clearly and concisely. And if they are too big, also rejecting them and telling them to go back to the drawing board and submit smaller more focused change. But I'm not int his position so I'm taking an educated guess.
Maybe. I don't have enough context, but maybe that's what he wanted to do? Whatever you may think about it, I'm pretty convinced Ozzy wanted to go out with a big concert. Nobody had to push him to do it.
Even if he did... he was in bad shape and it must have been physically taxing.
The thought of him feeling obligated to be on stage in front of a room of wide-eyed adult children is particularly sad. This is more a commentary on his fans than Tim himself.
Big "depends". Ali has "ships from China" and "ships from US" stuff. In a lot of cases, though, Amazon also tends to have cheap Chinese knockoffs for a comparable price (although sometimes their product ranking buries them and/or promotes the more expensive knockoffs)
Edit: Yeah I see an ONTi QSFP56 on Amazon for $45, 10Gtek QSFP112 for $62
I'm not sure I want another layer of indirection personally, and I'm guessing an updated Claude model will reign this in at some point. I have however created a skill I call "deslop" and I invoke it to clean up Claude output when it goes off the rails. Here's the skill if anybody is curious:
*Meta commentary.* Sentences about the document, the diagram, the reader, or the
writing itself ("the split across this diagram is the whole point", "a reader who
assumes X will be wrong", "as we'll see below"). Delete the frame and keep the fact
it was wrapped around. If there is no fact underneath, delete the sentence.
LLM doesn't need soft skills, but just knowing how to write a prompt to get the correct percentage values in a RAG and get the result close to your expectations out. Well it might be different based on the training data, which ai company, and how much you're paying.
People are different, they will be sometime affected by their emotional situation, surrounding, no matter how much they're being paid, You need to understand their mental situation, did he got scolded by the upper management today? He might not be on his best of his capacity right now. Or they might've pulled an all nighter and really not in their best position.
If someone going to treat people like an LLM, definitely is not going to have good time
Ironically, the same applies to AI. We seem to get demonstrably better results when speaking to models encouragingly [1]. It's a lot easier to re-establish goodwill when you can clear the memory and context of a program vs. a human though.
We don't know if it's all marketing stunts, or real, do we now?
> It's a lot easier to re-establish goodwill when you can clear the memory and context of a program vs. a human though.
That's the point. You can't erase human memories, experiences, (unless you bonk their head hard enough according to movies in my subcontinent, another bonk might reverse too) which will definitely affect their decisions and results.
But if you are managing AI agents you dont' need "soft skills" do you? You don't need to be especially nice to the AI, or symphatize with it, or have fun with it to build trust,
I would imagine that managing a team of AI-agents is totally different from managing a team of people.
> But if you are managing AI agents you dont' need "soft skills" do you?
“Soft skills” in management just means figuring out how to get what you want from the people you have available to you. In that respect those skills translate to using an LLM.
Figuring out how to get what you want from people would seem to me to be a very different skill than figuring out how to get what you want from AI agents.
For instance, how do you motivate people to work long hours, put in extra effort, feel proud of their work? How would you do that with AI?
They may be softer, but they're really not an identical set of soft-skills.
To illustrate the difference, imagine: "Hey, you've got all those soft-skills from tweaking the AI stuff, right? I need you to motivate Bob to get his head back in the game, but without causing him to resign."
Talking to an LLM is not a skill, just like using Google is not a skill.
Why? One, the companies like Google or Anthropic or OpenAI are working hard for it not to be a skill. That's the whole point. Second, these system are opaque, so there is no understanding to happen, only superstition, which might be wrong or change tomorrow.
I beg to differ. It is a simple skill that a great many have, but that doesn't make it “not a skill” - there are certainly many that don't have it, or don't want to practise it. Though I wouldn't name it specifically for Google, it is the more general “finding information online” skill which feels more specific because for many people these days it doesn't extend much beyond using Google or whatever their browser's default search service is.
People without the skill are quite evident: many of the closed duplicates on SO and similar sites are due to people lacking the skill to find information in old answers and effectively just asking others to look things up for them, the same for this week's 20th+ “my first layer has these bumps and gaps, what is going on?” question on any 3D printing forum (facebook groups etc.) that could be answered by scrolling down a few posts, and I'm sure the equivalent happens in groups serving any other plaything/hobby/skill/whatever.
Neither are skills that a large portion of users of those services pursue to any meaningful extent, I'll grant you that. They also certainly are not synonymous with the term "soft skills" as I know it. So I think I am on your side of the fence on that part any way.
I feel like if they were skills under a reasonable definition, you should be able to name an expert in these skills, and how do we know they are an expert.
But I think you can't. It seems to me, instead, one is better at googling/prompting the better they are in a particular domain, but it only applies in that domain. Like knowing a jargon is not a skill, knowing the domain is.
> you should be able to name an expert in these skills
There are certainly local “finding information online” experts in many families and social groups.
> and how do we know they are an expert
They are the ones who get mentioned a lot in conversations in the manner “I'll have to ask [name]” with the implication that [name] will look up the information or know it from previous occasions people (possibly this specific person and [name] is getting sick of them asking and not remembering simple answers!) have asked.
Soft skills include: handling change under ambiguity, critical thinking under pressure, self-awareness, prioritizing, motivating and guiding others without relying on authority, navigating disagreement constructively.
And of course if you point any of this out people go “Well many people are good at it, people getting bad results are just bad at it.” The constant refrain of “you’re just using it wrong” has become very tiresome.
If you can always say “just use it right” every time a critique comes up, then we aren’t having an honest conversation about the limitations of these tools.
It is impossible to duplicate results with an LLM. This strikes me as a serious barrier to calling it a proper skill. If you can’t even somewhat replicate the results you can’t really improve the input consistently. You can’t become “skilled” at it if you can’t even reproduce what you did.
If you enter the same prompt 3 times the results are of pretty significantly different quality. ChatGPT literally has you A/B test for them sometimes. They’re right to call it superstition - it feels like we’re making incantations and hoping for the best a lot of the time.
Prompting LLM’s still feels like a constant game of guess and check. At best you can argue it’s an educated guess. I don’t know about you but I didn’t learn math by guessing and checking, I frequently had to work backwards and review where I went wrong and/or I had the answer given to me with the work shown so I can learn. I can’t do that with a prompt. When I get bad results (which we all frequently do) I just guess what it didn’t like, try again, and pray for a better result.
Me typing into emacs is also not replicable, until I git push. Me with emacs and a good coding LLM can generate systems that I see as good, in my extensive professional judgement. For coding, for production grade code, the LLM will mostly be a tool in the hands of the professional. There is a new category of disposable code, which I think will be useful for many adhoc investigations; in neither case is replicability a serious requirement.
I do a lot of guessing and validating in learning maths. It is pretty efficient way to build that conceptual understanding. I even try to predict the next big theorem as I am listening to a lecture or reading a text book. It's engaging.
And honestly, I am enjoying learning this new way to make code I am pleased with. Using the LLM effectively and for quality deliverables is different from typing in many surface ways, but modularity of thought, iterative design and implementation, simplicity and generality, documentation, all still pay off.
These conversations always veer into “well I find it useful so I disagree.” I’m not saying anything about utility, I just think that system prompting is still very much hopes and prayers. We’re having a discussion about whether or not it’s a hard skill one can learn, I think that’s incredibly debatable
> It is impossible to duplicate results with an LLM
But that's the fundamental property of it - it is stochastic by nature. The skill is to learn how to sandwich deterministic logic between layers of randomness. Determinism doesn't live in the model. It lives in the harness you build around it. You can't make the model deterministic (it simply cannot be), so you make the system deterministic instead. Validation before, validation after, the randomness stays contained in the middle.
Talking to an LLM is not a skill, having a meaningful conversation leading to practical outcomes is.
If you ask me to write an email, all 3 variations will be more or less the same, except it will almost always improve with each iteration. 3 cracks at a prompt is 3 separate, unrelated attempts. None of them informs the other. In fact, you run the risk of making it worse if you include previous versions.
> 3 cracks at a prompt is 3 separate, unrelated attempts. None of them informs the other.
Thats where the "skill" part comes in. Like your 3 attempts at email that `almost always improve`. This is where you input the "previous versions", not directly back into the model. It's the "soft skill" of being flexible and adjusting based on how an entity responds to the input. Not learning how to adjust the input (by using previous attempts to inform the next) to more optimally direct the output given the state of the llm (chat? agent? model, effort lvl etc) it will seem chaotic.
The skills wont make an llm* deterministic, same as applying these soft skills to people. Give the same input to a person in `3 times separate, unrelated attempts` you are likely to get 3 different seemly chaotic outcomes. The "skill" is in being able to take what you received as output the first time, and make adjustments based on previous attempts while accounting for the state of the entity for the next attempt.
* In no way am I saying they are conscious beings or whatever nonsense by using people in the analogy. There are, however, parallels in how a set of soft skills (and this is why they are "soft" skills) can be used to get more optimal results from an entity that should never be expected to act as a pure function.
I don't think soft skills describes it in the traditional sense. The skillset largely needed with LLMs is more akin to being an editor or qa tester.
I suppose you could describe having the modesty to admit to yourself when you don't understand and research something deeper could be described as a soft skill, but I'd say it's a stretch. You are dealing with yourself in that scenario, not others.
When I use iOS devices, it feels better but I don't use them enough to have used them in anger. Ok, well, yes they have made me angry but for other reasons than the keyboard hence why I'm on Android lol.
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