I have sat through job talks given by postdocs from Nobel laureate labs and have never seen a more impeccable presentation of ideas in such a concise manner. Once my professor spent three full days working on 6 slides she was going to talk about for five minutes. The majority of the time my professors spend is on the politics of grants and spending and hiring more than actual science and that was actually the biggest issue. None of these sound naive or meandering to me!
If this author’s experience is the opposite this suggests my suspicion about biotech entrepreneurs - they’re often people who got out of academia a little too early and with a view of it that’s far too amateur. Not defending academia at all but I can only wonder if that selects for the type of person that might be more or less suited for entrepreneurship.
But you just spent 2 and a half paragraphs doing just that. Don’t try then to distance yourself from the opinion you’ve just given.
Conciseness is a good thing; it’s a minimum requirement in academia while you can get by elsewhere without it. The lack of naïveté is actually not a good thing necessarily. People in academia learn to play the game and not actually do proper science. A quick perusal of my comment history would reveal I am no friend of academia, I too ran away from it with just a PhD!
It does seem the author's description fits recent phd's better than experienced academics for the two points you refer to.
I don't know that "amateur" is the right word for someone who just graduated. They should have been trained to be a legitimate world-class researcher, despite their possible inexperience in the others sides of tenure-track jobs specifically. Unless you're suggesting they leave but still dabble in academic research on the side or something.
Believe me if you are at a lower-tier R1 university with revolving door faculty you are not insulated from these things as a grad student.
In Academia (at-least in CS where I did a PhD), you have to be working on a novel idea. It doesn't matter how many people actually care about the problem you are working on and/or will be impacted - as long as the idea is new and you are the first one.
Completely opposite in the startup. The problem has to be relevant. It doesn't matter if 5 other startups before you have worked on a similar problem - as long as you can out execute them.
This switch requires some serious "unlearning"
In academia, instead, there can be gaps of years between starting an experiment and seeing the first results, so "moving slowly" and "de-risking each step" is really the only way to achieve anything.
From my (extremely limited) experience, I feel that as a startup you want to be working with tech/tools of 50-75% of the complexity that you are able to handle and work with. You (probably) don't want to be working right up against cutting edge unless you are very confident about it or your unequivocally an expert. Otherwise all the variance and errors that come with running a startup is just going to render your product/service/whatever unusable