jmfldn

I see this sort of thing as a mind gym, and staying sharp will help your critical faculties as a programmer. Of course, the specific problems are nothing like the problems most of us solve day to day, but it still has many benefits.

Let's take a hypothetical where we really do all stop reading or writing code, because the models and tooling get good enough. In that scenario I would still argue for this of thing. Studying algorithms gives you a lot of insight and a powerful way of thinking. This class of problems is ultimately about how aspects of software work, so having some familiarity with famous algorithms is part of computer literacy. I'm not saying that you need to be an expert, but struggling to solve a few hard algorithm problems teaches a lot.

My approach is to write a bit of totally AI-free code every day. So after a day of Claude, I'll spend at least 30 mins wrestling with something. The gnarlier the better, e.g.leet code or Project Euler-type stuff. I think of it as like lifting weights for the mind. The more I struggle at the edge of my knowledge and skill the better.

The other thing is to give your agent a skill not to solve certain key problems unless explicitly prompted. Write the scaffolding sure, but leave the juicy parts alone. And if I get stuck, I have it enter into a dialogue with me, nudging me towards understanding.

Buddha addressed this idea directly. Your instinct that "getting comfortable with nothing" is still doing something turns out to be exactly right, and Buddhism doesn't deny it. Its answer is basically: yes, you use one kind of wanting (the motivation to practice) to loosen a deeper kind of wanting (craving a specific outcome), like using fire to burn down a house, then the fire has nothing left to burn.

Meditation, in the Therevada tradition at least, never claimed to be nothing, it uses doing to undermine it.

As the Buddhist joke goes 'don't just do something, stand there'.

I'm somewhere in between. I'm excited about building more things faster and extending my capabilities. But I also love thinking about the underlying language, runtime, algorithms, the wider system. I want LLMs to enhance this for me, I want my understanding to go up as I write less code. It's also key to my job as a lead that I maintain understanding of the system for debugging, security etc.

So if I can do both with these tools, then great. I want to cognitively offload in a way that allows me to focus on the important bits. And I'm writing instructions to the LLM to help me do that eg 'help teach me this bit'. A builder and tutor at once.

I understand he’s making a technical point about efficiency, but language isn't neutral and I think it betrays something deeper. It's such a glib and shallow point too that I think it should be called out since he has a track record of saying some incredibly shallow things about AI, people, politics, and everything really.

This is a profound category error. What Altman reduces to a 20-year 'training' cycle fueled by 'energy' is what we, in the actual world, call life. It is a stunningly hollow perspective that uses the language of industrial output to describe the human experience. While he is likely being provocative to keep his product at the center of the cultural conversation, it probably exposes something about him.

Well exactly ;)

"In 2025 finally almost everybody stopped saying so."

I haven't.

If it moves and connects with you then it's real music.

It's fine to have a preference for live musicianship, but the 'real music' argument has been leveled against every new musical technology (remember the furore around Dylan going electric?). It dismisses contemporary creativity based on a traditionalist bias that elevates one form of execution above all others. There's also a huge amount of skill in producing good electronic music. It's always hard to make good music no matter the means.

Seeing all the experienced engineers on this thread who feel discouraged is really depressing.

Not because I disagree with you, I don't! It's because I fear a gradual brain drain of people who actually love their craft and know how to build things properly. I fear we'll end up with worse software thats simply 'good enough', built a atop a pile of AI slop.

If it's cheaper but with acceptably worse results, I fear this is good enough for a lot of companies.

Sure maybe you're right. I'm just so underwhelmed by what I see in my day job that it's hard to map error prone and limited deep learning tools to what is being described here.

I don't see a strong argument here, more just a hope that something will spark this sci fi trajectory you describe. I'm sure big enough changes are afoot, but I think that the AI we have now will turn out to be much more of a 'normal' technology than most people expect.

A fun read, but wildly implausible. Perhaps there are other frontier technologies out there that get us even a fraction of this. But if we're talking this time horizon, I assume we mean LLMs or some other related thing? Are you joking?