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Don't fall into the anti-AI hype

antirez.com

381–390 of 1001 posts

Re: Don't fall into the anti-AI hype

#381

Earlier quoted context omitted.

> I think there is a section of programmer who actually do like the actual typing of letters, numbers and special characters into a computer... This sounds like an alien trying and failing to describe why people like creating things. No, the typing of characters in a keyboard has no special meaning, neither does dragging a brush across a canvas or pulling thread through fabric. It's the primitive desire to create som…

My entire point is that people are different. For some people (read through the other comments), it's quite literally about typing of characters, or dragging a brush across the canvas. Sure, that might not be the point for you, but my entire point of my comment is that just because it's "obviously because of X" for you, that doesn't mean it's like that for others. Sometimes I like to make music because I have an idea…

No, they're right. Your description is what you get from outsiders who don't understand what they're seeing.

In a creative process, when you really know your tools, you start being able to go from thought to result without really having to think about the tools. The most common example when it comes to computers would be touch-typing - when your muscle memory gets so good you don't think about the keyboard at all anymore, your hands "know" what to do to get your thoughts down. But for those of us with enough experience in the programming languages and editor/IDE we use, the same thing can happen - going from thought to code is nearly effortless, as is reading code, because we don't need to think about the layers in between anymore.

But this only works when those tools are reliable, when we know they'll do exactly what we expect. AI tooling isn't reliable: It introduces two lossy translation layers (thought -> English and English -> code) and a bunch of waiting in the middle that breaks any flow. With faster computers maybe we can eliminate the waiting, but the reliability just isn't there.

This applies to music, painting, all sorts of creative things. Sure there's prep time beforehand with physical creation like painting, but when someone really gets into the flow it's the same: they're not having to think about the tools so much as getting their thoughts into the end result. The tools "disappear".

> Other times, I make music because I like the feeling of turning a knob, and striking keys at just the right moment, and it gives me a feeling of satisfaction.

But I'll bet you're not thinking about "I like turning this knob" at the moment you're doing it, I'll bet you're thinking "Increase the foo" (and if you're like me it's probably more liking knowing that fact without forming the words) and the knob's immediate visceral feedback is where the satisfaction comes from because you're increasing the foo without having to think about how to do it - in part because of how reliable it is.

Re: Don't fall into the anti-AI hype

#383

> But what was the fire inside you, when you coded till night to see your project working? It was building. I feel like this is not the same for everyone. For some people, the "fire" is literally about "I control a computer", for others "I'm solving a problem for others", and yet for others "I made something that made others smile/cry/feel emotions" and so on. I think there is a section of programmer who actually do…

In my feed 'AI hype' outnumbers 'anti-AI hype' 5-1. And anti-hype moderates like antirez and simonw are rare. To be a radical in ai is to believe that ai tools offer a modest but growing net positive utility to a modest but growing subset of hackers and professionals

Well put.

AI obviously brings big benefits into the profession. We just have not seen exactly what they are just yet. How it will unfold.

But personally I feel that a future of not having to churn out yet another crud app is attractive.

Re: Don't fall into the anti-AI hype

#384
post #2

> As a programmer, I want to write more open source than ever, now. I want to write less, just knowing that LLM models are going to be trained on my code is making me feel more strongly than ever that my open source contributions will simply be stolen. Am I wrong to feel this? Is anyone else concerned about this? We've already seen some pretty strong evidence of this with Tailwind.

This is why I never got into open source in the first place. I was worried that new programmers might read my code, learn how to program, and then start independently contributing the the projects I know and love - significantly devaluing my contributions.

Re: Don't fall into the anti-AI hype

#385

Earlier quoted context omitted.

> I think there is a section of programmer who actually do like the actual typing of letters, numbers and special characters into a computer, and for them, I understand LLMs remove the fun part. Exactly me.

That's because physical programming ing is a ritual. I'm not entirely sure what that means myself, so please speak up if my statement resonates with you.

It resonates. But as I see it, that kind of ritual I rather devote myself to at home. At work, the more efficient and rapidly we can get stuff dobe, the better.

Drawing and painting is a ritual to me as well. No one pays me for it and I am happy about that.

Re: Don't fall into the anti-AI hype

#387
The reason I am "anti-AI" is not because I think LLMs being bad at what they do, nor because I'm afraid they'll take my job. I use CC to accelerate my own work (it's improved by leaps and bounds though I still find I have to keep it on a short leash because it doesn't always think things through enough). It's also a great research tool (search on steroids). It's excellent at summarizing long documents, editing and proofreading, etc. I use it for all those things. It's useful.

The reason I am anti-AI is because I believe it poses a net-negative to society overall. Not because it is inherently bad, but because of the way it is being infused into society by large corps (and eventually governments). Yes, it makes me, and other developers, more productive. And it can more quickly solve certain problems that were time consuming or laborious to solve. And it might lead to new and greater scientific and technological advances.

But those gains do not outweigh all of the negatives: concentration of power and capital into an increasingly small group, the eventual loss of untold millions of jobs (with, as of yet, not even a shred of indication of what might be replace them), the loss of skills in the next generations who are delegating much of their critical thinking (or thinking period), to ChatGPT; the loss of trust in society now that any believable video can be easily generated; the concentration of power in the the control of information if everyone is getting their info from LLMs instead of the open internet (and ultimately, potentially the death of the open internet); the explosion in energy consumption by data centers which exacerbates rather than mitigates global warming; and plenty more.

AI might allow us to find better technological solutions to world hunger, poverty, mental health, water shortages, climate change, and war. But none of those problems are technological problems; technology only plays a small part. And the really important part is being negatively exacerbated by the "AI arms race". That's why I, who was my whole life a technological optimist, am no longer hopeful for the future. I wish I was.

Re: Don't fall into the anti-AI hype

#388
> However, this technology is far too important to be in the hands of a few companies.

I worry less about the model access and more about the hardwire required to run those models (i.e. do inference).

If a) the only way to compete in software development in the future is to outsource the entire implementation process to one of a few frontier models (Chinese, US or otherwise)

and b) only a few companies worldwide have the GPU power to run inference with those models in a reasonable time

then don't we already have a massive amount of centralization?

That is also something I keep wondering with agentic coding - being able to realize your epic fantasy hobby project you've on and off been thinking about for the last years in a couple of afternoons is absolutely amazing. But if you do the same with work projects, how do you solve the data protection issues? Will we all now just hand our entire production codebases to OpenAI or Anthropic etc and hope their pinky promises hold?

Or will there be a race for medium-sized companies to have their own GPU datacentets, not for production but solely for internal development and code generation?

Re: Don't fall into the anti-AI hype

#389

Earlier quoted context omitted.

If you can't see this by working with Claude Code for a few weeks, I don't want to go into bigger efforts than writing a blog post to convince you. It's not a mission, mine. I just want to communicate with the part of people that are open enough to challenge their ideas and are willing to touch with their hands what is happening. Also, if you tried and failed, it means that either for your domain AI is not good enoug…

I am waiting people to commits their prompt/agents setup instead of the code to call this a changing paradigm. So far it is "just" machine generating code and generating code doesn't solve all the software problem (but yeah they get pretty good at generating code)

If you want an example, I just open-sourced a project which includes the prompts and CLAUDE.md: https://github.com/minimaxir/miditui/tree/main/agent_notes

Re: Don't fall into the anti-AI hype

#390

Don't fall into the "Look ma, no hands" hype. Antirez + LLM + CFO = Billion Dollar Redis company, quite plausibly. /However/ ... As for the delta provided by an LLM to Antirez, outside of Redis (and outside of any problem space he is already intimately familiar with), an Apples to Apples comparison would be he trying this on an equally complex codebase he has no idea about. I'll bet... what Antirez can do with Redis…

What "domain expert" means is also changing however.

As I've mentioned often, I'm solving problems in a domain I had minimal background in before. However, that domain is computer vision. So I can literally "see" if the code works or not!

To expand, I've set up tests, benchmarks and tools that generate results as images. I chat with the LLM about a specific problem at hand, it presents various solutions, I pick a promising approach, it writes the code, I run the tests which almost always pass, but if they don't, I can hone in on the problem quickly with a visual check of the relevant images.

This has allowed me to make progress despite my lack of background. Interestingly, I've now built up some domain knowledge through learning by doing and experimenting (and soon, shipping)!

These days I think an agent could execute this whole loop by itself by "looking" at the test and result images itself. I've uploaded test images to the LLM and we had technical conversations about them as if it "saw" them like a human. However, there are ton of images and I don't want to burn the tokens at this point.

The upshot is, if you can set up a way of reliably testing and validating the LLM's output, you could still achieve things in an unfamiliar domain without prior expertise.

Taking your Postgres example, it's a heavily tested and benchmarked project. I would bet someone like Antirez would be able to jump in and do original, valid work using AI very quickly, because even if hasn't futzed with Postgres code, he HAS futzed with a LOT of other code and hence has a deep intuition about software architecture in general.

So this is what I meant by the meaning of "domain expert" changing. The required skills have become a lot more fundamental. Maybe the only required skills are intuition about software engineering, critical thinking, and basic knowledge of statistics and the scientific method.

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