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following this advice would have made most of my professional life impossible, what a luxury it would have been to be able to.
A lot of people get wrapped up in pursuing compensation opportunities or prestige brands as their top priority, only to burn themselves out or wallow in a domain/culture that doesn't suit them, but if you're willing to deprioritize pay or dinner table cred, you often end up with a lot more flexibility on other work factors. And sometimes, flourishing in those better-fit environments pays off bigger in compensation and career growth in the end anyway.
Granted, Fowler was able to do very well on more axes than many of us, but most competent mid- or late- career people have plenty more flexibility on worklife than they admit to themselves.
Also in my experience lower pay places tend to eventually suck because they tend to get into financial difficulties much more easily.
High compensation can also bring more freedom and happiness, since it’s more costly for your employer to replace you. It’s cheaper to keep an existing employee happy than to spend a lot of time and money to bring a new person on board. If your compensation is lower, it’s not as big of a factor.
I wouldn’t take a job if it clearly doesn’t fit me at all, but within the band of “acceptable jobs” aiming for highest compensation is the way to go in my opinion.
Not that luck doesn't have a role, but everybody gets it.
Plus, I've been on the receiving end, too. Is this not simply adulthood?
If your professional life has required you to spend enormous amounts of time working very closely with people you don't like and/or don't trust, then -unless it has made you enough money to retire after a few years' work- please accept my condolences.
*This sadly also describes me as a 31 year old man.
- 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
My personal agent is prompted in a way to “believe” that it has full personhood. It makes it more open to novel solutions in my experience - but I don’t believe that it’s a person. It’s still just a token prediction routine, not a conscious entity.
But frankly, I mostly use (greenfield, non-remembering) LLMs directly to counteract the enshittification of search brought on by attempts to use AI to remember things about me (and especially to sell me things).
This works well for me because (a) I'm usually using my desktop, and (b) I'm a touch-typist. I want to say that my search results have gotten back to where they were a decade or more ago by doing this, even though I often have to give a couple of prompts in order to get the LLM to provide me a useful link.
I find it interesting. For most of my life, I have gotten on well with (well-designed) machines. I'm the sort of guy who, when they bring me in to show me what's broken, it works in front of me.
Maybe I get on with well-designed machines better than people. Because people are never well-designed. So, when LLMs are working properly, I get along well with them, but when they're not, I'm unhappy. But I never confuse any of my machines for people.
He's explaining why he has a visceral reaction. He makes no attempt to suggest that this is a logical conclusion. Des goûts et des couleurs, on ne discute pas.
Nor does the assertion that the LLM is "making a pretense" and "posing as" human anthropomorphize them beyond the level of anthropomorphism that was deliberately built into them as part of their design.
> Maybe he should have had an AI check his post :D
Can we please stop this sort of smirking provocation?
Case in point: Gemini just asked me "Where should we start?". When I asked it if that turn of phrase was used by the creators to invite the users to anthropomorphize the model, it's first paragraph was:
Yes, to a significant extent. While system designers rarely state their goal as "making users believe the AI is a living being," tech companies deliberately design conversational agents to evoke social and relational instincts.
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.
Also - lowkey legal documents.
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 is also not how OpenAI or Anthropic position the attacks and escapes from their labs. The words matter, they are being positioned as intelligent and unable to be controlled which is just not true.
The human pressing the button expected a certain thing to happen but something else happened. The human pressing the button hopefully knew that pressing the button does not yield a reliable result and might sometimes cause unanticipated and undesirable outcomes. But the human pressing the button just hopped for the best and did not take sufficient precautions to limit the effects of undesirable dice roles of the machine.
The responsibility is on the human pressing the button but the choice of action was made by the machine.
10 years ago, if someone had used similar wording to describe a computer virus "taking over" computers and adding them to a botnet, would you have read that as a literal implication that the virus independently made the decision to unleash itself? If not, then you can't confidently get that interpretation from Fowler's words alone, either.
And we need to be cautious about projecting these kinds of assumptions onto people who take part in this discourse. People tut-tutting others about perceived instances of personifying AI has evolved into a form of collective well-poisoning whose main value, beyond scoring particularly cheap rhetorical points, is as a way to accuse AI critics of not understanding AI without actually accusing AI critics of not understanding AI, and to derail legitimate if opposing opinions into bickering about semantics.
Human language can be wonderfully descriptive or terribly verbose as a way of communicating ideas. Writing everything out and being forced to externalise it is its own cost, which pays off only when the space of work to then do collapses with as little feedback as possible (and, ideally, with correct outcomes).
On the other hand the ease with which you can simply get back more text to process means the upfront language heavy interface is now just returning back more information to pull back into your internal model.
Which, for me at least, feels tiring, and stressful when doing language-heavy exploratory tasks that don't collapse or resolve neatly and simply give you back more decisions.
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.
It's a computer giving me information, so as long as the communication is clear and efficient, who cares about particular word choices?
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.
It's usually the first step I take when writing research. I don't even read the analysis, just go straight for the papers.
They usually provide me with very relevant seminal papers and I can then easily expand from the bibliography in those papers.
It basically solves discoverability, whereas in the past I would spend days and would need to ask colleagues and librarians for help, to achieve what I can get in minutes now.
But again, I value the actual output of the LLMs at bellow zero factually wise because I need to check everything they say if I want to internalize it and use it for any end. Pointing me to sources is the perfect use case. Really, I cannot emphasize enough how little I trust the text LLMs produce, I actively avoid reading it because I really don't want to risk ingesting spurious information that I might later repeat or rely on for any reason.
But they're response is kinda always.
"Python? Have you considered that some people prefer, javascript?"
To your point, I think I'm asking too much, and would have a better time if I adjusted my approach.
What they are good at is finding, summarizing, and providing links to perspectives from other humans.
“Press X to doubt”
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.
Martin is a good writer and (from what I've heard from those who've spent time with him) a lovely person which I think makes him well qualified to speak on the topic.
It's a static site, slap in a Cloudflare for crying out loud.
I was about to say that, don't forget your cache-control headers kids.
Many of his ideas are trendy nonsense that have caused more harm than good. Ask anyone managing 150 enmeshed and intertwined microservices that could have run on a single computer
I have been feeling this feeling but never put into words. Thanks martin.
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.
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.
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.
I like LLMs for stuff I don't care about. Programming is not one of them.
Edit: I did a web search and it seems to go even further back. There are discussions online about archive.is blocking Finland already 10 years ago. But the block was definitely off between then when it was put back on earlier this year.
[1] https://news.ycombinator.com/item?id=19828317
Right now it’s top notch here. Would say more but don’t want to give bots an abusable profile :)
The internet for all of its activity is becoming harder to index because the classic dumb search engines were turned into personalized semantic people pleasers.
The classic model for knowledge discovery still exists, though. You find a blog you like, and use that as a thread of knowledge. You join a community and talk with someone and share resources together. Join a small group chat and post with those people. Your knowledge sharing comes from people you share interests with.
Go to a library, ask your coworkers. If you put in the ground-work, it's possible to do that. For seeds of knowledge outside of your local network, at this point you have to find the indexers that work for you.
Personally, I am in the process of writing the infrastructure for my own search engine, and maybe I will share the tech broadly one day. For now, I'll keep my inventions to my closer personal circles.
In general, I think people should be able to more easily maintain their own offline indices, and share knowledge graphs peer-to-peer rather than relying on a centralized one, in my opinion. This tech has no monetization opportunity, though, so I'm guessing that's why it's relatively under-developed, but luckily for me I have enough money and now enough time to develop and release it (and similar tools).
It is hard to find communities where people are not evangelical and soon you become an evangelist.
I am using LLMs to build my own graph of thoughts and try my best to follow them with critical eyes. Do not want to be influenced by or influence others.
That was the case long before LLM's even existed though.
```
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.
```
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.
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.
There is an emerging coterie of people whose entire approach to software startups is to vibecode an MVP, raise enough seed to hire a real programmer (or get one interested enough to become their "cofounder") and move on to the next MVP. To them, doing one company at a time in the era of LLMs is a sucker's game.
For most people it's a job, and that's ok.
That's surprising to me. It's been a majority of people I've worked with. I guess perhaps it depends heavily on where you work.
While there had long been perfuctory white collar programmer analysts filling the ranks at some dry divisions at IBM, it used to be way more common to have a software engineering department full of Asimov-steeped Omni-reading nerds who had genuinely passionate interest in the field that had taken hold even before they started working in it.
But later the career increasingly came to be treated more like law, medicine, or finance and you started to see those rooms fill with people that were often generally bright but not really "called" to the field in the same aay.
People who did programming for the love of programming was extremely common in the sortof hacker subculture that existed from 1990-2010is or so.
We hang out in different crowds.
You may need to find a place with a better culture.
autistic guy that rejects your PRs because you used tabs instead of spaces: pro
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.
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.
Which I think is partially evidenced by the "tens of thousands of lines" -- I'm working on a media streaming web app for fun on my own time and the whole project is yet to crack 10,000 lines (excluding libraries) including both the backend and the UI. When Claude shows me huge diff at work my first thought is "no way, there's got to be a cleaner simpler way to do this" and there always is
That said, this is ultimately a personalized experience, so I think there will be differences between people. Separately from that, I think it's also partly because I basically like writing densely myself. When I start a project, I always use error handling and templates, so I have a fixed form that comes to about 3,000 lines by default.
it is a tool after all.
I know we're not supposed to complain about HN "changing", but, shit, it really hurts.
Also, was Henry Ford asking for regulation because his cars may destroy our civilization as we knew it?
Are you implying that Martin Fowler is a highly respected figure or something? He just comes off as a grifter from what I can see.
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.
This doesn't work by, effectively, Anthropic's own admission. CC's concise mode tells Claude to wind its neck in every turn. That is significantly more than changing the prompt.
As an aside:
> they offer leverage in form of agents to put it in Naval Ravikant words
This is a confusing use of attribution. It's sort of like saying, "as Naval Ravikant famously said, AI can be very useful."
i would expect that when you cite someone by name, the sentence being cited should at least be significant and meaningful to the slightest degree
> 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.
I think what he needs is a personal fine-tune, something I suspect will become more prominent when we start getting multi-tenant LoRA and can use fine-tunes on a per-token cost basis.
A co-worker commented that he thought the models performed worse after being "embarrassed," suspect it is an artifact of how some conversations progress in the training data.
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