I'll say invest totally in domain knowledge now. The value of knowing how to invert a binary tree from memory has dropped to approximately zero. Web development as we knew it for the past 20 years is completely dead as an entry level trade. The power is shifting to people with useful knowledge and expertise that isn't about twiddling bits.

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mekoka 5 hours ago | parent | next [-]

Are people still under the impression that testing candidates with coding challenges is in preparation of a job where real world problems are described like "invert the binary tree"?

There was never any value in simply the ability to invert a binary tree from memory. First, contrary to popular belief, this particular challenge is quite trivial, even easier imo than fizzbuzz. The value of testing candidates with easy problems is their usefulness in quickly filtering out potentially problematic coders, not necessarily to identify strong ones.

Second, another common take on coding challenges is that they're about memorization. Somewhat, but only to a point. Data structures and algorithms are a vocabulary. A big part of the challenge of using them "creatively" in real life is your ability to recognize that a particular subset of that vocabulary best matches a particular situation. In many novel contexts an LLM might be able to help you with implementation once the right algorithm has been identified, but only after you yourself have made that insightful connection.

Having said this I generally agree with the philosophy [0] that keeping things simple is enough 95+% of the time.

[0] https://news.ycombinator.com/item?id=47423647

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Ifkaluva 7 hours ago | parent | prev | next [-]

What do you mean by “domain knowledge”? And how is it a competitive advantage?

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crop_rotation 7 hours ago | parent | next [-]

Domain knowledge as in non public aspects of the work you/ your workplace does. The AI tools are very good at whatever is public but very clueless about proprietary domains .Let's say you make CRUD apps about some confidential domain. Now the CRUD skills might be commodity but the confidential domain is even more important.

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magic_hamster 6 hours ago | parent | next [-]

As long as there's internal documentation, which virtually every serious shop has, it can be processed and combined with AI. There are startups selling this product already. I've seen first hand some very narrowly focused domain knowledge becoming more accessible when you can ask the chatbot and the thing is right. It works.

Come to think of it, domain knowledge should be an LLMs strong suit as long as you can provide the right documentation, which is working pretty well already.

Right now the main issue I see with AI is that it doesn't do well with scaling. It's great for building demos and examples but you have to fix its code for real production work. But for how long?

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generic92034 6 hours ago | parent | next [-]

In ERP software there are MLOCs without any technical documentation. And nobody would spend a dime to create one. So, the deep expert knowledge on how business processes are supposed to work (in full detail) and how they are implemented is mostly in the heads of a couple of people.

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mycall 6 hours ago | parent [-]

AI is most excellent at reading and understanding large codebases and, with some guidance docs, can easily reproduce accurate technical documentation. Divide and conquer.

	▲	yladiz 5 hours ago \| parent [-]
		Accuracy/faithfulness to the code as written isn't necessarily what you care about though, it's an understanding of the underlying problem. Just translating code doesn't actually help you do that.

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jasondigitized 2 hours ago | parent | prev [-]

Documentation rarely reflects how anything is actually done, referred to by good business analysts as 'shadow functions'.

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kokanee 7 hours ago | parent | prev | next [-]

But everyone at the company has that private domain knowledge. The only thing you're bringing to the table that anyone in any other role doesn't offer is the commoditized skill set.

	▲	follie 6 hours ago \| parent [-]
		Right, and you'll not keep everything out of materials like AI generated meeting notes for every repeat of every process so the company doesn't really need many experts in its existing operations.

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skybrian 6 hours ago | parent | prev [-]

Internal domain knowledge can become pretty useless when you switch companies and have to start over, though.

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7 hours ago | parent | prev | next [-]

[deleted]

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kurthr 6 hours ago | parent | prev | next [-]

Can't speak to the OP, but lots of technical work (and frankly many trades are also technical) doesn't lend itself to text based documentation and teaching. Software, translation, non/fiction writing (like marketing and sales) all do. I think LLMs will take a significant part of those businesses, because I don't believe there is a Devon's Paradox for code -Tractors- Agents.

At the same time medicine, hardware design, good industrial, and specific domain knowledge (problems you solve in assembly or control loops) that are fundamentally proprietary and aren't well documented will continue to have value even when LLMs make solving the problems around them easier. Those might have increased leverage, at least for this round of LLMs. Now, maybe they succeed in World Models, but that is not today.

Really, I don't know what "kids these days" are going to do. I couldn't have predicted the influencer boom 15 years ago, but I also think there are geopolitical risks that are probably bigger than that shift, and "synergized" with the push to AI Everything, it doesn't look like a good time to be a learning/working human.

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bossyTeacher 7 hours ago | parent | prev [-]

Pre-LLMs, algorithmic knowledge was used as a proxy for skill difference at interview stage. In the workplace, you could google the implementation details and common gotchas. This was valuable knowledge.

Post-LLMs, the value of this (as differentiator) has dropped to zero. Domain knowledge (also known as business knowledge) is the obvious area to skill up on. It simply means knowledge about the area your organisation is working in. Whether it is yogurt delivery logistics, clothing manufacturing supply chain systems, etc. That's the real differentiator now. Anyone can invert a binary try in 5 minutes using an LLM. But designing a software system knowing well the domain your organisation is in is invaluable.

	▲	forgetfulness 7 hours ago \| parent [-]
		Right, bridging the gap of knowledge by getting closer to that of the clerical workers of the company, because pure software knowledge is no longer as valuable. That will probably make your salary closer to theirs, and that'll be a pretty big adjustment.

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travisdrake 5 hours ago | parent | prev | next [-]

I think this is true today, especially with complex domains, but I foresee a future where more and more walls fall. If you are in college now, go deep on a domain. If you are entering in 10 years, I have no idea.

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alephnerd 5 hours ago | parent | prev [-]

The fact you are getting downvoted to oblivion shows how fucked HN has become.

Ain't nobody gonna hire a code monkey - you are being hired based on whether or not you can reason and enable workflows via tech.

If you're only name to grace is you can write pretty Python but cannot architect at scale or care to actually understand the bigger picture of what is being built and why, you will get offshored to someone who is also using Claude Code.

If I'm working on a fullstack for a cloud security product like Wiz, I'd rather hire an average developer who deeply understands the cloud security industry versus a NodeJS doc wiz who has zero empathy or interest in learning about cloud security. There are too many of the latter and not enough of the former in the American scene now, and especially on HN.

If HNers cry about how cut-throat the American market has become, they haven't seen it in China, India, or the CEE.