It definitely is at the youth level. I don’t think any football or basketball pros could be soccer stars, but absolutely there are kids who are star point guards on their youth basketball team but top out at 5’8”, or football players who never make it past high school but could have been great at soccer.
Well no, an existing professional American football player has no chance of switching to being a professional soccer player. Nobody can simply switch at that level. You have to have cultivated the skills over a long period of time to ever have a chance at competing at the highest levels.
On the other hand, I can’t imagine the guys that ended up being cornerbacks, wide receivers, safeties, or even halfbacks couldn’t have become soccer professionals given the right culture, training, and desire growing up. Sure, linemen, tight ends, and fullbacks aren’t built for soccer.
When we are talking about the really TOP elite of football those kids get into it at age 5. From that age on every day consists of hours of football. There are scouts looking at prepubescent kids all over the world ready to sign them.
That's the point. Since so many sports are competing for "player attention", people may commit to the "wrong" sport early on, be decent, and then top out at an age where it's too late (in terms of going pro) to switch to a sport they may have been great at.
In a hypothetical world where every kid plays only soccer, every potentially great soccer player has been practicing the sport from an early age. In a world with 10 competing sports, some potentially great soccer players might have be playing baseball or basketball from a young age up into their late teens.
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.
I agree with this — there is at least some bifurcation by skillset and capabilities. Lots of engineers are overfitted to working on consumer web apps or SaaS products, but those are no longer an area of focus. You need to be adaptable enough to work on other kinds of systems too. Doing so either requires that you’re really good commercially (can lead development of a product over time, drive revenue, etc) or very good technically at a wide breadth of technologies and problems.
What makes this more extreme is that we’re in a paradigm shift, technically. Systems of the future look different than what’s been built before. Building agentic stuff is very different than web apps. The infrastructure side is also different. Moreover, both are uncertain so there’s no plug-and-play set of skills that would fit into any company in the way you could probably get hired reliably in the 2010s if you can operate Kubernetes, design a database schema, write Node.js APIs, etc.
Context windows are a natural improvement, but new architectures are completely speculative and it’s unclear we can make any sort of predictable progress with new, better architectures. Most progress has been made on essentially the same architecture paradigms, although we did move from dense models to MoE at some point.
You said above that our country “needs the best engineers and doctors.” Are the tests you mention really objective, direct measures of which student is likely to be the best engineer or doctor in the future? What does it even mean to be the best engineer, and how do you test that?
Depends on the team — managing can be quite a bit more scope than being a senior IC, depending on expectations for that role. You have broader ownership of technical outcomes over time, even aside from the extra responsibility for growing a team. Managers have all the responsibility of a senior engineer plus more. In that way manager feels to me like a clear promotion to me. Manager vs staff eng, maybe not though.
Management not being a promotion doesn’t mean that managers aren’t (usually—I’ve both been at equal and higher levels than my managers at times) higher levels than their reports. It means that switching to a management role from IC is never a promotion itself (ie always L6 -> M1 in Google/Meta levels) and it never comes with any difference in compensation.
I haven't been a manager, but my understanding is that the higher IC roles assume you're competent enough to do some management-like things if needed ("responsibility without control"), and I also assume that being a manager helps with compensation because they actually teach you how the review process works and let you into the calibration meetings.
I don’t agree with that though, plenty of places practice agile well. Maybe big corporations don’t practice it well, but startups often do agile correctly and understand the philosophy.
I think the primary benefit of LLMs for me is as an entrypoint into an area I know nothing about. For instance, if I’m building a new kind of system which I haven’t built before, then I’m missing lots of information about it — like what are the most common ways to approach this problem, is there academic research I should read, what are the common terms/paradigms/etc. For this kind of thing LLMs are good because they just need to be approximately correct to be useful, and they can also provide links to enough primary sources that you can verify what they say. It’s similar if I’m using a new library I haven’t used before, or something like that. I use LLMs much less for things that I am already an expert in.
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