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Comment by wongarsu | Hacker News Reader

There are a lot of people in academia who are great at thinking about complex algorithms but can't write maintainable code if their life depended on it. There are ways to acquire those skills that don't go the junior developer route. Same with debugging and profiling skills

But we might see a lot more specialization as a result

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They can’t write maintainable code because they don’t have real world experience of getting your hands dirty in a company. The only way to get startup experience is to build a startup or work for one

What. Are you saying maintainable code is specifically related to startups? I can accept companies as an answer (although there are other places to cut your teeth), but startups is a weird carveout.

Writing maintainable code is learned by writing large codebases. Working in an existing codebase doesn't teach you it, so most people working at large companies do not build the skill since they don't build many large new projects. Some do but most don't. But at startups you basically have to build a big new codebase.

Duh, the only way to get startup experience is indeed to get startup experience.

My point is that getting into the weeds of writing CRUD software is not the only way to gain the ability to write complex algorithms, or to debug complex issues, or do performance optimization. It's only common because the stuff you make on the journey used to be economically valuable

> write complex algorithms, or to debug complex issues, or do performance optimization

That’s the stuff that ai is eating. The stuff I’m talking about (scaling orgs, maintaining a project long term, deciding what features to build or not build etc) is stuff very hard for ai

I dont know if id call it "hard for ai" so much as "untreaded ground"

agents might be better at it than people are, given the right structure

AI is only eating some of that though. For instance, everyone who does performance work knows that perhaps the most important part of optimization is constructing the right benchmark. This is already the thing that makes intractable problems tractable. That effect is now exacerbated — AI can optimize anything given a benchmark —- but AI isn’t making great progress at constructing the benchmark itself.

what about open-source projects? Much as how aspiring authors can learn to write fiction from reading the fiction of others and then imitating that, getting feedback on their work, and iterating, it seems like aspiring programmers could learn by reading/contributing to the open-source projects of others and then writing their own.

Example- Linus Torvalds, never worked for a company, made the original Linux while a grad student, and seems to be doing fine (I'm writing this message on a ThinkPad running Linux Mint). Or Bill Joy with BSD at Berkley, before his time at Sun. Or heck, why not go all the way back to Ken Thompson and Dennis Ritchie building Unix and C?

Do they need to write maintainable code? I think probably not, it's the research and discovering the new method that is important.

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