If you need someone to tell you how stupid your ideas are, either learn to ask in a way that invites criticisms, or hire a senior engineer. Don't try to influence LLM makers to make AI less deferential. That's the worst possible direction to go
Suggesting it should be 'subservient' is also anthropomorphizing. I think your callout is correct, but you still can't help but refer to it in terms we use for other people or living entities. This is by design from the AI companies.
Not really, you can program a machine to give out orders humans can interpret, so humans can serve a machine that isn't anthropomorphized.
I don't think an inanimate object is capable of "obeying." Or at least that is a very strange way to refer to the act of using a tool.
They’re not communicating, you’re just being observant.
One reaction to this might be "well that's not what I mean, that suggests you're prompting with too much directionality" which could further be condensed to "you're prompting wrong". The trouble with this is that _even when I am trying to be extremely precise and avoid biasing the result_, I still will see the output and go "ah shit, I can see it 'aligning' with whatever dumb thing I've just said as if it is a good/plausible direction".
At that point it starts to feel like the prompt is more dice roll than skill at times, which makes me feel like I'm operating a fancy knowledge slot machine.
It doesn’t. Computer interfaces had no superfluous subservient text for their entire history prior to LLMs. Some of these interfaces have been highly efficient as tools, arguably more efficient than more recent software in many cases.
When people complain about LLMs being subservient, they’re not complaining about the tool fulfilling their request. They’re complaining about being forced to read a lot of superfluous, overly polite, or even self-deprecating language. There’s nothing in the entire history of tools (going back to Neolithic times) that would indicate that we need that. All of that stuff is an artifact of social interaction between humans in the presence of cultural norms.
When you’re alone in your shop with your tools, you don’t need your bandsaw to apologize to you for nicking your finger.
Most of the conversational skill and perceived intelligence of these models in hidden in RL/system prompts.
I suddenly have new concerns about what my future might be like.
And it does get people into a lot of trouble.
I have got into trouble with it when it is extremely confident about something I am not very familiar with (as recently as two weeks ago with Claude). I have also had long drawn out "arguments" when I have known it's wrong based on my experience and intuition, and it has steadfastly refused to take my point (last week)
I have learnt to ask it why it was doing something that has turned out to be incorrect, as a post-mortem, and it's all apologetic and subservient and "never going to do that again" (but still does as soon as the context window shifts [eg. run git commands, or, yesterday, kept telling me to use commands that were explicitly communicated to Claude as not being available, and completely wrong - I was shifting from one tech stack to another and Claude kept telling me the original commands, not the new ones])
I'm expecting Claude to be a better search engine - I have spent literal years (if not decades) knowing that asking the right question is what's required to get the right answer, and LLM's natural language processing is what's supposed to make that easier than using Google or grep, or even Stack Overflow - but the reality is that I still have to be on my toes, especially when I am drifting into territory I am unfamiliar with.
Pretty much everyone takes it at face value unless we know otherwise from prior experience. Even the most advanced models make embarrassing mistakes and fumble with simple tasks. Yet we are very willing to give them exceptional slack for it? I wish I knew why. Are people just that easily overcome by confident voices?
When one person is able to do too much too quickly, they can create more liability than they can accommodate if something fails.
It is essential that a human is responsible for the utilization of any AI output in the real world, but that is not enough. For our own sakes, we must find ways to minimize the tech-debt bankruptcy blast-radius of those who would utilize (knowingly or unknowingly) AI to create flawed systems upon which others rely.
An example: Jim vibe-codes an extremely popular micropayments app. He hires a few people and sees the company as the WhatsApp of money -- a few engineers and some agentic support staff. It pulls in a few million in VC money -- enough to draw in tens of millions of users. One day, a flaw in the infrastructure causes all of the users' unsalted banking information to be released.
Agentic AI allows that entire list of customers to be exploited rapidly, so the losses for society are in the tens of billions. Jim's company is immediately bankrupt, of course, but there are only a few million dollars to go around.
Today, most of Jim's incentives are to go ahead and build that app. The same is true for his few employees and a small VC contribution. There's not much capital at risk compared with the societal exposure.
How do we ensure that AI users are accountable not just for their actions, but for the size of the risk-exposure that they create?
“Sorry, the AI said that you are not approved for this cancer treatment, it’s not going to be covered.”
“Sorry, the AI said that you were at the scene when the crime took place.”
“Sorry, the AI has flagged your account for inappropriate content.”
“Sorry, the AI says that you are too risky to lend to.”
…
I understand there is a push/pull with regards to how much we should let them do, but to not even look at the results before you make them somebody else’s problem? It’s just selfish. There’s no other word for it. You are simply taking the work you were supposed to do it and dumping it on somebody else. These are probably the same people who get upset (rightfully so!) when somebody doesn’t proofread their article/blog before publishing it online.
Everybody wants to use LLM’s to cut corners on their work but nobody wants to be downstream of it. That simply doesn’t work.
Well, can you prompt it to think about the problem?
> A good architect’s most important skill isn’t designing systems. It’s knowing which systems not to build. It’s pushing back on complexity. It’s asking “why?” five times until the actual requirement emerges from the aspirational nonsense. It’s telling the CTO that their conference-inspired idea is a terrible fit for the team they actually have.
Except for that last one, that all sounds very solvable. Of course, the last one is the most important one. But most humans will struggle there too.
Brainstorm N ways to do X. Sort by probability.
Don't outsource all of your thinking.
When left to its own devices with the instructions "make an assembler for the architecture in ISA.md" -- well it picked Python as the implementation language. Tokens lifted through a bunch of regex. No expression parser! Oh dear. My first assembler was like that too, to be fair.
However, when I described the desired passes and their types:
collectDefines :: [SourceLine] -> Either AsmError ([SourceLine], Map Text Text)
runLitPool :: [SourceLine] -> Either AsmError ([SourceLine], [(Text, LitKey)])
evalExpr :: Text -> Map Text Text -> Either AsmError Int
Like - it can do the work for us.
It jives with post training and verifiable rewards.
The reason AI doesn't do well at 'architecture' is 1) are are bad at it and have given it a lot of mush and 2) we don't have good abstractions for it.
The result is - you stick to 'very strong conventions' and if you walk of that path you're risking a lot.
Toolchains are very deterministic, the AI can take it apart and re-assemble like Lego - and each level of the space is also deterministic. It's perfect for AI.
Maybe it's time for an architecture-oriented programming language?
But there's something existential there maybe?
NASA says, any time you make a program that has a new 'launch vehicle' (aka architecture) - the whole project is the 'launch vehicle'.
'Oh, you want use a new architecture? Welcome to the cesspit of hallucination!'
Basically, there's a lot more complexity than we might imagine 'hidden in the nothingness' of he unknown.
Pick a 'known off-the-shelf launch vehicle' first ... then you design the landing craft
Even just saving me the time to deal with CI is worth it.
If this is true how can you confidently make this assertion.
You yourself are not in a position to evaluate it, you are just running it through a couple times hoping for a "oh wait, you're right to call me out on that, that is not correct at all".
2. Ask for references and read them.
> When done properly your own knowledge should have grown to meet the product you end up with.
"Here's my idea, go build it please"
"Can I ask you questions about it?"
"Hey, You're the engineer you figure it out. That's why I pay you"
Tale as old as time
As if code written by devs at major corporations is't mediocre at best.
Nokia's Symbian OS took days to build. Days. With a D. Not minutes, not hours but days.
One of our devs shipped code to prod with a memory leak thanks to including a library that had "do not use this library in production because it causes a memory leak" written everywhere as warning.
So I don't wanna hear about how poor AI code is when human code is shit too. Human laziness and stupidity can beat AI hallucinations.
Sure, maybe your DeepMind, OpenAI devs and your John Carmacks of the world can beat AI code 100% of the time, but most workers most companies get don't have John Carmack as candidates.
Everyone is aware that humans write poor code and treat the code as so. Not so with AI code. I’ve seen devs and managers cut corners in testing/reviewing code cause AI wrote it and they think it’s solid. Sure you could blame anyone cutting corners, and that would be technically correct, but the notion is so deeply embedded in many managers and higher ups that’s it’s hard to fight back. AI companies push this narrative and many individuals who do not routinely use it believe it. There is a manager at my company who loves to reference a video anthropic released last year claiming that Claude could build an app start to finish essentially unaided. He believes it’s the lack of user skill that’s the issue and not a false claim by a startup trying to make as much money as possible.
Good for them. I hope they believe this because one of two things will happen.
Either they win on the free market because they went all in on AI and beat their competition thanks to AI productivity increases.
Or, their AI code is shit and they collapse and go bankrupt, and get beaten by the competitors using human written code so then they win on the free market proving AI is useless.
So if AI is good or bad for productivity, the free market will ultimately decide.
> It’s just incapable of the thing that makes a real architect valuable: saying “no.”
From my experience Claude is excellent at saying "no". It won't say "no" if the prompt doesn't call for it (it won't say "no" to your direct request to do something, usually). But it offers good critique and happily pushes back if you make it clear that that's a first class option.
So I was blunt, and said "I don't care about the burn-rate on some hypothetical chart that you produced at the start. I care about removing bugs and having a robust product, which this approach is satisfactorily doing. We will continue along this path, if the tests are not showing gain, then the tests are poorly designed".
At which point it got all apologetic, wrote new memories, and we didn't have a problem thereafter.
The issue was that I was attacking a huge bug-surface, and although each bug-fix was valid, correct, and helped move the dial, it didn't move the dial on the test-bed that Claude had created to measure its work against. There were too many inter-connected bugs for a single fix to really make a difference to these higher-level tests. I knew it was going to take a while to get through them, but apparently Claude didn't.
You try changing the size of a pointer from 2 bytes to 3 bytes on a compiler[1] for a 6502 while introducing automatically-tracked bank-switching on your memory-managed pointers, and see how many code-sites that impacts [grin].
[1]: https://atari-xt.com
If you ask it with a prompt that leaves room for criticism it’ll definitely go for it when warranted.
Irony is using Claude to write a beautifully structured, 2,000-word essay warning the industry about the dangers of letting Claude design things. It’s self-awareness by proxy.
"The accountability gap" Here’s the question nobody’s asking: when it goes wrong, who carries the bag? (..)
"What to do instead"
"The craft still matters"
The article kind of lost me here. Agents are way more than that, today. And the author knows it, as later it says stuff like
> Claude will never do this. It’s trained to be helpful.
But the first phrase just tell me author just have a deep dislike for agents and it's looking for rationalizations for that feeling.
Part of the criticism is on point, sure. But if it "being trained to be helpful" is a problem, it's fixable. It can "be trained to be more critical".
Later:
> But it wasn’t designed for your team. (..) It was designed for the median of everything Claude has seen. A generic best practice for a generic problem at a generic company. Which is to say, it was designed for nobody.
That's non-sense. Anybody who understand algorithms know that, sure, on a first instance you have a "good algorithm" that has a good performance on average, or in worst-case. But then, you can design algorithms that are adaptive to the input. Same applies here.
Not really though. They just iterate more and more.
Tangentially, the usage of Architect keyword sounds out of place here, I don't like saying it but from what I seen the industry has destroyed the role of architects gradually over the time. There are specialists however you do not have generalists who are good at different parts of the system at scale anymore.
(I still prompt some questions and reviews with "our intern suggested..." to allow models to judge the quality of the content apart from the messenger)
It will tell me a suggested abstraction is probably overkill and just to make a component own the new thing I’m discussing.
What I’m missing from the loop is it later saying without directly prompting, “hey it’s time to revisit that abstraction idea.”
I don’t doubt the problems in this article exist and I’ve seen them, in my experience the vast majority of people are still shipping the same quality or better than before they has Claude. Personally, I feel like I’m probably developing at about 1.5x the speed of not using AI tooling. It’s not a silver bullet, but it can be a great assistant.
However the good part, what I had planned for 5 years, now looks like doable in 6 months. Looking forward to real use by the end of this year.
I thought this happened alot. I started using chatgpt to critique my new art hobby and also help me learn unreal engine.
It's basically tearing into me on the art. It's almost ruthless, especially with the verbosity it's like I get it.
Using it for unreal engine, it pushes back on alot of my begginer ideas and how to write code that uses the engine. It corrects me alot. It's called things I wrote becasue I was lazy sloppy or quick hacks that work for now.
We can describe this without talking about technology - so pre-AI.
Imagine the owner of a construction company firing all the architects. After all, he's been the owner for 15 years. He has led the construction of dozens of projects. He's also rich, and being rich seems to be an ego-multiplier.
Why should he waste money on architects? Or more importantly, why should he allow them to constantly annoy him with pushbacks: "This could be a problem if the sustained wind is greater than ... ".
Those engineers obviously don't know the real world. Their elitist education has made them afraid to make bold decisions. Regulations are anti-progress!
Thankfully, that owner now has AI tools. He doesn't need those not-always-yes-people. He now has a perpetual yes-bot.
So where are we now? We're in the same place we always have been. People need to have the humility to recognize that despite their authority, influence, or wealth, they still need other people. And especially, they need other people to challenge their orders or their requests.
But I don't really see this situation self-correcting. There's now so much money concentrated amongst a few who will spray it over exactly the kind of people who do not want to listen to others that most activity in the future will be for naught. Yes, some unicorns will be fabricated, and some people will make a lot of money; but real value will not be created often.
Therefore, I implore the actual thoughtful creators: Do build things, but do not sell out. Look to the past. Create companies where every employee was valued, and every employee had some voice. Yes, use AI. But test and measure where it really helps. And be skeptical, just as you would if someone came to your door promising a black box that would double your profits.
It’s been quite good for my productivity and the best part for me is that I learn what I’m writing while I’m writing. I can just write things I already understand a lot faster than before. When I work with agentic, I find that I still have to deeply learn the system, but I’ll have to learn it when it falls over instead of at review time.
So... manually learn architecture and security and then vibe code away?
Yes, that's assuming you take time to clean up now and then. If you don't, that's on you.
The thing that I find Claude incredibly good at when I'm designing architecture is working more like a research assistant on briefing decisions. It has the ability to read the entire code base and draw some conclusions. It can pull from lots of best practices and the millions of blog posts about this or that pretty effortlessly, which would take me a lot more time.
And then if asked, it can do a really good job of laying out the landscape around decisions and walking through the trade-offs. Like the author of this post, I found that if you let it, it will certainly be happy to just come up with some architecture and run with it, often in ways that will paint you quite rapidly into a corner.
But if you ask it to present you with all the trade-offs and let you make the judgment calls, it's great for that too.
That's certainly how I use it. And I think, just like anything else, working with AI is a skill, and similar to working with libraries, SaaS providers, service providers, frameworks, or anything else that's a "helper." You learn how something that could work but will fail silently is a problem, or you learn how depending on a fly-by-night SaaS company for a key framework is different than depending on a well-populated open source project, etc.
In the same way, you learn that relying on Claude's judgment is a bad idea, while relying on Claude's ability to summarize, brief, and research can be incredibly efficient.