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Ask HN: Go deep into AI/LLMs or just use them as tools?

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Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#41

Post by mindcrime »

3) go back to school and study something that isn't done entirely on a computer and requires human physical presence (for now). Learning plumbing, electrical wiring, welding, etc. are options. Even if you don't make that your primary path, it never hurts to have a fallback plan JUST IN CASE some of the buzz around AI-fueled job displacement turns out to be valid.

Or, if you believe there may be some merit to "AI is coming for your job" meme, but really don't want to do blue collar / skilled trades work, at least go in with the mindset of "the people who build, operate, and maintain the AI systems will probably stay employed at least a little bit longer than the people don't". And then figure out how to apply that to deciding between one or both of your (1) and (2) options. There may also be some white collar jobs that will be safe longer due to regulatory reasons or whatever. Maybe get your physician's assistant license or something?

And yes, I'm maybe playing "Devil's Advocate" here a little bit. But I will say that I don't consider the idea of a future where AI has meaningful impact on employment for tech professionals to be entirely out of the question, especially as we extend the timeline. Whatever you think of today's AI, consider that it's as bad right now as it will ever be. And ask what it will be like in 1 year. Or 3 years. Or 7 years. Or 10 years. And then try to work out what position you want to be in at those points in the timeline.

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#42

Post by jll29 »

LLMs are part of soft-computing, i.e. contrary to traditional (algortihm-based) computing sometimes things won't get the right result (or, just as bad, the right result in the wrong format). Engineering solutions with LLM is a lot of fiddling, which is experimental rather than analytical/logical.

It is worth getting use to that mind-set, and then use LLMs as a tool (they are likely here to stay, because big tech have started to integrate features based on them everywhere, for better or worse). So this is your option (2.). Personally, I prefer software I use NOT to be smart, but to be 100% deterministic.

But already my favorite LaTeX authoring environment (Overleaf) has a button pop up called "fix this" that auto-resolves syntax errors, many of which overwhelm my doctoral students that no longer read books end-to-end (here, to learn LaTeX).

Gradually, you may dive deeper into the "how", driven by either need or curiosity, so eventually you will probably have done both (2.) and (1.). - in the same way that you will have first learned SQL before learning how replication, transactions, data buffers and caches, or query optimizers are implemented.

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#43

Post by xg15 »

drdunce wrote: post #36
sMarsIntruder wrote: post #17

Earlier quoted context omitted.

Looks like OP’s curiosity isn’t just about deep diving LLMs —he’s probably itching to dig into adjacent topics like RAG, AI pipelines, and all the other adjacent LLM rabbit holes. So in that case I don’t see why not?

I just wanted to second the previous comment, and this is even for adjacent fields. Also a PhD AI/ML grad, and so many of us are out of work at the moment that we'll happily settle for prompt engineering roles, let alone RAG etc., just to maintain appearances on CVs/eligibilty for possible future roles.

Kinda surprised of that, actually. Sure, I get that research interest in any if the "traditional" ML methods (SVMs, markov models, decision trees, that kind of stuff) is probably essentially dead right now, but I had thought interest in neural networks and "understanding" what LLMs do internally to be ballooning.

I could imagine that even those "ancient" techniques might some day make a comeback. They're far inferior to LLMs in terms of expressive power, but they also require literally orders of magnitude less memory and computation power. So when the hype dies down, interest in solutions that don't require millions in hardware cost or making your entire business dependent on what Sam Altman and Donald Trump had for breakfast might have a resurgence. Also, interestingly enough, LLMs could even help in this area: Most of those old techniques require an abundance of labeled training data, which was always hard to achieve in practice. However, LLMs are great at either labeling existing data or generating new synthetic data that those systems could train on.

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#44

Post by manmal »

antirez wrote: post #21

My 2 centes: 1. Learn basic NNs at a simple level, build from scratch (no frameworks) a feed forward neural network with back propagation to train against MNIST or something as simple. Understand every part of it. Just use your favorite programming language. 2. Learn (without having to implement with the code, or to understand the finer parts of the implementations) how the NN architectures work and why they work. Wh…

My problem with 5. is that there are many unknowns, especially when it comes to agents. They have wildly different system prompts that are optimized on a daily basis. I’ve noticed that Gemini 2.5 Pro seems way dumber when used in the Copilot agent, vs me just running all the required context through OpenRouter in Continue.dev. The former doesn’t produce usable iOS tests, while the latter was almost perfect. On the surface, it looks like those should be doing the same thing; but internally, it seems that they are not. And I guess that means I should just use Continue, but they broke something and my workflow doesn’t work anymore.

And people keep saying you need to make a plan first, and then let the agent implement it. Well I did, and had a few markdown files that described the task well. But Copilot‘s Agent didn’t manage to write this Swift code in a way that actually works - everything was subtly off and wrong, and untangling would have taken longer than rewriting it.

Is Copilot just bad, and I need to use Claude Code and/or Cursor?

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#45

Post by tmsh »

Hot take: based on how fast models are accelerating and replacing large parts of the development process (my two cents in https://x.com/TomHarada1/status/1926193211678023953), I think more and more you want to work backwards from a world where AI does 90% of things. Script kiddies : prompt engineering :: current engineering :: future of engineering. Either path makes sense - going deep in research or development. One is a kernel and one is the rest of the egg.

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#46

Post by antirez »

manmal wrote: post #44
antirez wrote: post #21

My 2 centes: 1. Learn basic NNs at a simple level, build from scratch (no frameworks) a feed forward neural network with back propagation to train against MNIST or something as simple. Understand every part of it. Just use your favorite programming language. 2. Learn (without having to implement with the code, or to understand the finer parts of the implementations) how the NN architectures work and why they work. Wh…

My problem with 5. is that there are many unknowns, especially when it comes to agents. They have wildly different system prompts that are optimized on a daily basis. I’ve noticed that Gemini 2.5 Pro seems way dumber when used in the Copilot agent, vs me just running all the required context through OpenRouter in Continue.dev. The former doesn’t produce usable iOS tests, while the latter was almost perfect. On the su…

I never ever use agents for coding. Just the web interface of Gemini, Claude, ..., you are perfectly right that agentic coding just creates a layer of indetermination and chaos.

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#48

Post by yapyap »

You could definitely do 1. if you have the mental patience to surround yourself with the grifters in the AI world and the moral ambiguity to do your work.

It’s up to you where your morals lay and how important money is compared to those morals but it seems like AI is here to stay.

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#49

Post by risyachka »

mindcrime wrote: post #41

3) go back to school and study something that isn't done entirely on a computer and requires human physical presence (for now). Learning plumbing, electrical wiring, welding, etc. are options. Even if you don't make that your primary path, it never hurts to have a fallback plan JUST IN CASE some of the buzz around AI-fueled job displacement turns out to be valid. Or, if you believe there may be some merit to "AI is c…

Going into trades sounds nice on paper but the salaries there were mostly always low because you need only a handful of those to saturate market needs.

Its not IT where you can create value from thin air and thus grow the market and increase need for even more professionals.

As soon as a tiny percent goes into trades (bet tons of new people already doing this) the market will be oversaturated in a few years when they finish apprenticeships.

After that it will be harder to find a job than in IT with AI around the corner.

Re: Ask HN: Go deep into AI/LLMs or just use them as tools?

#50

Post by amelius »

jillesvangurp wrote: post #34

Depends on what you want to do. But my 2 cents are that like all new technology, LLMs will become a commodity. Which means that everybody uses them but few people are able to develop them from scratch. It's not different from other things like databases, GPU drivers, 3D engines for games, etc. That all involves a lot of hardcore computer science and math. But lots of people use these things without being hindered by…

But the question is what mindset will allow you to put yourself ahead of the rest. Because I suppose the OP doesn't want to end up as just another mediocre programmer.
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