Is the point of math really to prove the statement? Arguably interesting, unproven statements are interesting often specifically because they are hard to prove with existing techniques.
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.
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.
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.
Big companies hired a lot, but I don’t think this specifically is true? In theory a high-value engineer would be productive, or else they aren’t worth stealing.
The simpler explanation seems more correct here — there was a lot of product fluff and a lot of headcount allocated to build that fluff.