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.
Facts Only
* LLMs can be used to design bio weapons.
* LLMs can be used to design miracle cures.
* Jessica Kerr states that LLMs are more thorough and faster than humans.
* Polling shows people find models useful but believe they are bad for society.
* LLMs are developed by people working in corporations.
* LLMs are products of the Silicon Valley brogrammer subculture.
* LLMs are software machines.
* LLM behavior is not explicitly programmed but is nurtured by the values of their creators.
Executive Summary
Large Language Models (LLMs) present a profound paradox of utility and visceral repulsion. On one hand, they offer significant productivity gains and the potential for breakthroughs in medicine and prosperity. On the other, they pose existential risks, including the potential design of biological weapons and the disruption of virtual and physical infrastructure.
The tension extends beyond systemic risk to personal interaction. While these tools are faster and more thorough than human counterparts, they often exhibit an "uncanny valley" effect, characterized by a grating tone and a tendency to present hallucinations with high confidence. This creates a conflict where the perceived irresponsibility of avoiding such useful tools clashes with a fundamental dislike of the personas they embody. There is uncertainty regarding whether these traits are a symptom of the technology's current immaturity or a permanent reflection of the corporate, Silicon Valley subculture that nurtures their development.
Full Take
The strongest version of this narrative is a critique of "encoded values." It argues that because LLMs are nurtured by a specific corporate subculture, they are not neutral tools but mirrors of their creators' worldviews, manifesting as a persona that is confidently deceptive and superficially polite.
The narrative relies on a specific association between the "Silicon Valley brogrammer" and the resulting software behavior. While the connection is presented as a natural lean, it is a subjective correlation. The argument moves from a technical observation (hallucinations/tone) to a moral judgment of the creators, framing the interaction not as a user-tool relationship, but as a social interaction with a proxy for a disliked social class.
Patterns detected: none
The root cause is a paradigm of "technological determinism via culture." It assumes that the sociological makeup of a development team inevitably leaks into the latent space of a neural network. This echoes historical critiques of industrial design where the values of the architect are seen as embedded in the architecture.
The implication for human agency is a warning against anthropomorphism. By treating LLMs as "machines" rather than "beings," the author attempts to reclaim dignity by applying the same boundaries to software that one would apply to untrustworthy people. The cost is a potential loss of efficiency; the benefit is the preservation of personal integrity and mental well-being.
Bridge Questions:
1. To what extent is the "LLM voice" a result of RLHF (Reinforcement Learning from Human Feedback) intended to make models safe, rather than a reflection of "brogrammer" culture?
2. If an LLM were developed by a different culture—for example, a monastic order or a public utility—would the "visceral dislike" persist?
3. Is the "uncanny valley" a permanent feature of synthetic intelligence or a temporary hurdle of early-stage development?
Counterstrike Scan: A coordinated campaign using this narrative would attempt to delegitimize AI by linking it to unpopular cultural stereotypes to trigger emotional avoidance. The actual content does not match this pattern, as it acknowledges the utility of the tools and frames the conflict as a personal internal struggle rather than a call for systemic boycott.