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Comment by sixtyj | Hacker News Reader

Remove LLM and 80 pct of people will have to jump to start. LLM assistance is a huge dependence on something owned by few. And although I use it daily since Nov 22, I don’t see any big progress in productivity. Yes, I have done a lot of projects (that I can’t remember), I see a lot of sites made without human touch, I have heard fairy tales about llm’s breakthroughs to internet from a cage.

What I see that everybody is somehow a blacksmith now without knowing how to forge iron. And we call it progress.

I am optimistic, and I am not against LLM. I like a quote from OP’s article:

> One of my colleagues used to say, "AI is a mirror." I find that insightful: it reflects who you are, including the curiosity, judgment, and habits you bring to it. The questions you ask and the standards you apply to its answers matter.

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My first project with it was in Jan 22, back when it was just sentence completion. Really hard to implement practically.

But in the past year the production boost is just insane. LLM assistance took away so many of the barriers that prevented me from executing on ideas.

I've also learned more than ever before, although it is admittedly getting harder to stay involved when the models are becoming more and more reliable.

What I have not figured out yet is why most developers around me do not share this effect. It's like it mostly works for a very specific subset of people, that do understand code, but it's not their main focus.

Just take a look at what is happening with the M-Wave FM1. Stating those devs would be lost without Ai won't stop the tide. It's not going to go away.

> Remove LLM and 80 pct of people will have to jump to start.

Isn't the same true for every service and technology we start to rely on?

Remove GPS and people will have to figure out how to read maps again.

Remove search engines and people will have to figure out how domains work.

Remove Wikipedia and we have to go back to the library to check encyclopedias.

And much like society has rebuilt itself around, for example, the cellular phone and even the car, it’s rebuilding itself around LLMs. Yes, now you have to buy a thing you didn’t in the past. A bunch of capitalists have found a new way to build capital. I guess we get some value out of it too, but once it becomes built-in it can be hard to see it.

Yes, you’re right. How many times a day do you really use GPS? Dependence on LLM is much bigger stake.

> Remove GPS and people will have to figure out how to read maps again.

It's not GPS, but turn-by-turn navigation. Remove that and people's spatial understanding of their environment improves significantly, and this improvement persists even long after the experiment, and they'll even be able to use turn-by-turn navigation better.

Which aligns with Anthropic's reports that people are able to use Claude better if they understand their own codebase better, and that increased Claude usage leads to reduced understanding of the codebase.

When society replaced walking as the primary mode of transportation with driving, people started going to the gym to keep their body in shape.

We should probably be training spatial perception (replaced by GPS), understanding of algorithms and data structures (replaced by coding agents), too.

Counterpoint, lots of people learn to navigate the areas where they spend their time by following GPS directions repeatedly, and can drive regular routes without them (though they're still useful for routing around unknown traffic issues).

I understand that it feels that way, but this has been widely studied and it's just not the same.

When you repeatedly follow directions, you'll learn how to take that path.

But when you repeatedly read a map, or walk an area on foot, you'll also learn the roads and areas you're not taking nearby, and learning the spatial relationships between these places.

A lot of learning happens through the mistakes we make, because they teach us a lot more about our environment. Whether that's a physical landscape or a codebase.

When you search for a bug, you'll look at maybe one or two files that are related to that bug, but also 10-20 files that aren't. You won't consciously remember the content of those 20 files, but your mind is building a map of their spatial and logical relations, which helps you the next time.

There is a giant difference in retention and learning between following even a printed turn by turn guide and using a modern gps.

This is anecdotally obviously as well as proven by studies. You don't learn the route or the neighborhood when you just "mindlessly" respond to "turn left" directions.

"LLM assistance is a huge dependence on something owned by few."

Open models are capable and owned by everyone who wants to.

And the overwhelming majority of LLM users will never use them or even understand what they are or how to set them up. Those people will remain dependent, and we shouldn’t ignore that.

Fair point. How many people know OpenCode, Pi? How many pct of ppl code? How many pct of companies buy their own hardware with GPUs? It is similar situation e.g. as Salesforce vs Odoo. Imho 99 pct of companies choose SF, not Odoo.

People don't know about those because the options owned by few are cheap (subsidized by VC) and easily available.

My worry is that if we need to pivot to those open options, we'd be so far behind in infrastructure, and no one has the hardware to run the open models at their home/office.

You can't remove LLMs. Once models are released as open weights, they cannot be removed. As long as the compute to run them exists, so will LLMs.

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