YHK - yet another hacker news clone

edit: Not exactly as I remembered, but it's a PG tweet: Prediction: In the AI age, taste will become even more important. When anyone can make anything, the big differentiator is what you choose to make.

https://x.com/paulg/status/2022604692178522562

following this advice would have made most of my professional life impossible, what a luxury it would have been to be able to.

This takes about 30 seconds to fix permanently. You can prompt them to use any tone , be as concise or verbose as you like.

> They confidently bullshit me - often giving me useful, helpful answers. But also just making stuff up with the same assurance - and with only a veneer of fake remorse when I call them out on it.

Only people with flimsy epistemological underpinnings feel threatened in this way. Everyone makes mistakes, and gets fooled by AI (as we’ve been fooled by historians and scientists), but to write off AI because you feel it’s constantly misleading you means you lack proper foundations. Most of my fun conversations with AI are bending it back into proper grounded truth.

it is a tool after all.

*This sadly also describes me as a 31 year old man.

For my own sanity ive wrapped my pi setup in some strict bubble wrap and it is basically exclusively an LOC generator. I have no need nor desire to "converse" with the LLM, it is there to do exactly what i need when i need it.

I'm sure I can sort of prompt it to try to give the answer I want but some people talk about "I don't want an LLM with a political perspective, just provide all the perspectives equally and without bias."

And to a certain extent they have to be constrained. Anything more than a 500 word response I'm probably not going to read, particularly if I want to go deeper on something I want to navigate the conversation. But it means that tuning things like sycophancy just create sort of extremely simple mitigations. Even when I say "May" or "slight chance of" I'm often corrected "Be careful to make too blanket of a statement." I wonder if part of this has been the move towards optimizing towards the agent experience.

Likewise a bias towards "Say things equally without bias" is an exceptionally poor way to actually explore the nuances of an idea, with this sort of regression to the mean.

I don't know if they'll be able to solve this problem broadly. I mean, LLMs probably shouldn't be therapists/coaches/philosophical gurus. But I could anticipate a growth in sort of groupthink and regression to the mean in terms of perspectives broadly speaking as a society.

I find them useful. Maybe it's better I find them distasteful to talk to as well.

Is he actively coding...anything? Any projects? And engagements? Or is he a coding influencer now, giving hot takes and opinions, and riding on the XP inertia as a relevant authority?

Because if it's the latter, and I strongly suspect it is, his opinions on LLMs and coding are close to worthless. There are loads of "I'm now an influencer" giving these sorts of hot takes now, and they all seem...detached and irrational with the real world.

It's amazing how effectively tech leaders have indoctrinated people to give up their power and give the tech people free reign. The same thing has happened in the socio-political realm. Assertions of powerlessness are seen as wisdom.

I def want to finetune my llm responses and yes sure Claude has some type of memory but its too early to just bet on one horse and while i use claude at home through claude.ai i also use claude through an api at my company.

It might start feeling better when they solve the issue of forgetting things they already got right before.

He is of course entitled to his opinion on the topic, but I’m personally not going to put too much weight on it considering he hasn’t written software for a living in probably decades.

- When we think of AI agents, we shouldn’t anthropomorphize

- ...my visceral dislike of interacting with an LLM that’s not just making a pretense of being human, but also posing as the kind of human I walk away from.

So he's anthropomorphised the LLM as being like a human himself (rather than forcing it to act as a machine via its prompt for example).

Maybe he should have had an AI check his post :D

I dislike that an LLM can produce tens of thousands of lines in 30 minutes, but if I had done it, it would have taken a month.

I know that using LLMs degrades my skills and also degrades my ability to verify LLMs. But in the freelance market, these days contracts are made on the premise that you use LLMs.

I hate AI slop, but here I am actually trying to make a small indie game using AI.

I hate LLMs, and I also like them. I have complicated feelings about it.

I find that what makes people hate LLM-voice isn’t the voice itself. It’s that the voice pings their brain with a reminder of their AI anxiety. That ping makes people instantly upset.

> They confidently bullshit me - often giving me useful, helpful answers. But also just making stuff up with the same assurance … When we think of AI agents, we shouldn’t anthropomorphize... They are (software) machines

I believe these ideas contradictory. I find that people get angry at LLMs bullshitting precisely because they are not anthropomorphizing. People bullshit all the time. But, these are machines! Machines are not supposed to bullshit! And, when they do, there’s supposed to be a bug filed and fixed.

By holding LLMs up to the expectations of machines instead of expectations of (simulated) people, users are frustrating themselves.

If you take the same “trust but verify (everything)” approach with LLMs as you do with people, you’ll be a lot less frustrated.

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I have a lot of mixed feelings about AI and LLM technology. I’m fascinated by its effect on our profession, excited by the potential gains in productivity - and thus the products we could rapidly build. On the other hand, I’m fearful of the damage AI might cause: agent swarms taking over our virtual and physical infrastructure, designing bio weapons. But, back on my first hand, LLMs might also design miracle cures, and come up with clever ways to raise our prosperity. Fundamentally I don’t think we have a choice about riding on the AI technology train. It’s a wild ride and I just hope we’ll get through it OK.

But as I mull on this more, I realize that among this mix of contrasting feelings, there is one emotion that dominates - one that comes from my direct interactions with LLMs. I don’t like them. They talk to me in this grating LLM-voice, an uncanny valley of talking to a real human. They confidently bullshit me - often giving me useful, helpful answers. But also just making stuff up with the same assurance - and with only a veneer of fake remorse when I call them out on it. That’s not enough to make me feel we should avoid them. As Jessica Kerr put it “not only are they useful, it is irresponsible not to use them…. They’re more thorough, as well as faster.” This contradictory reaction comes through in polling, where people say they find these models are useful, but also that they think they will be bad for society. Much of this may be because LLMs are young - we haven’t trained them to grow up yet. Maybe I’ll like them once they mature. (I hope we get to find out.) But I’m not encouraged when I think of the kinds of environments that cultivate them. I’m wary of the Silicon Valley brogrammer subculture, and these LLMs are their products, so naturally lean toward their world-view. When we think of AI agents, we shouldn’t anthropomorphize, treating them as conscious beings with their own will. They are (software) machines, developed by people working in corporations. While the agents’ behavior aren’t explicitly programmed, they are nurtured with the values of their creators.

One of my most successful life-hacks is to avoid people I don’t like or don’t trust. I decline to interact with them socially, and make a deliberate effort to avoid working with them too, even if they are doing much that is beneficial. I feel that hanging out with pleasant, capable people, the people with integrity, has made my life a far better one. Hence my visceral dislike of interacting with an LLM that’s not just making a pretense of being human, but also posing as the kind of human I walk away from.

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I like LLMs for stuff I don't care about. Programming is not one of them.

The attitude that AI is doing things all on its own is so pervasive. These are all set off by human operators, giving them instructions and tools to do whatever it is that are doing. The "AI has a mind of its own" attitude is just wrong.

The fear of bad people using AI to do bad things is very different then AI agent swarms attacking and taking over.

It's a computer giving me information, so as long as the communication is clear and efficient, who cares about particular word choices?

I have been feeling this feeling but never put into words. Thanks martin.

If you want to work with untrustworthy people, you not only have to double check everything, which may be tolerable but you may also need to do some social gymnastics, as people usually don't like be told they are full of shit.

LLMs don't mind, you can correct them, kill the conversation and open a new one with a clean context, even insult them if it makes you feel better with no negative consequences.

In fact LLMs love to be corrected, and it is a common trap, as they will happily use your correction as fact and build around it, without pushing back even if you are wrong. So if there is a negative consequence to tell them they are wrong, that's it, LLMs won't hold a grudge against you like people do, but it may trigger more hallucinations.

Agreed, so why frame it as avoiding unpleasant people? My experience with Anthropic's latest models is that no amount of instruction can overcome their latent verbosity (nor can AGENTS.md overcome OpenAI models' reticence). I tried A/B testing several models and Opus was the clear winner, so I'm not likely to retire it just because it generates unpleasant prose. I do curate model-specific notes to mitigate some of the worst offenses.

If you think the model is "bullshitting you" and is in need of being "called out", odds are that that tone is coming through in your prompts and the model's fake remorse is analogous to the fake remorse that you get after "calling out" a customer-support rep. In both cases, the entity at the other end of the connection is doing exactly what they are trained to do: placate you and deescalate.

It's not bullshitting you, it's just wrong (or you're just wrong), and it usually can fix the problem if it's not too busy tending to your emotional state.

“Press X to doubt”

Why is this a bad thing? The capability to identify bs, ideally with as little latency as possible, is one way that expertise shows up.

Due to this reason, I built a tool called MiseGuard.

MiSeGuard replaces slow, unpredictable "AI judges" with a deterministic, zero-AI circuit breaker. It is pure code, not an LLM. If a command attempts something catastrophic—like wiping a directory, deleting a database, or touching private secrets—it slams the door shut instantly with a hard stop before any damage can happen.

Check it out here : https://github.com/midhunweb/miseguard