This comment sounds like itās partly implying āRP seems to have recently overcome these bottlenecks. How? Does that imply the bottlenecks are in general smaller now than they were then?ā I think the situation is more like āThe bottlenecks were there back then and still are now. RP was doing unusually well at overcoming the bottlenecks then and still is now.ā
The rest of this comment says a bit more on that front, but doesnāt really directly answer your question. I do have some thoughts that are more like direct answers, but other people at RP are better placed to comment so Iāll wait till they do so and then maybe add a couple things.
(Note that I focus mostly on longtermism and EA meta; maybe Iād say different things if I focused more on other cause areas.)
In late 2020, I was given three quite exciting job offers, and ultimately chose to go with a combo of the offer from RP and the offer from FHI, with Plan A being to then leave FHI after ~1 year to be a full-time RP employee. (I was upfront with everyone about this plan. I can explain the reasoning more if people are interested.)
The single biggest reason I prioritised RP was that I believe the following three things:
āEA indeed seems most constrained by things like āmanagement capacityā and āorg capacityā (see e.g. the various things linked to from scalably using labor).
I seem well-suited to eventually helping address that via things like doing research management.
RP seems unusually good at bypassing these bottlenecks and scaling fairly rapidly while maintaining high quality standards, and I could help it continue to do so.ā
I continue to think that those things were true then and still are now (and so still have the same Plan A & turn down other exciting opportunities).
That said, the picture regarding the bottlenecks is a bit complicated. In brief, I think that:
The EA community overall has made more progress than I expected at increasing things like management capacity, org capacity, available mentorship, ability to scalably use labor, etc. E.g., various research training programs have sprung up, RP has grown substantially, and some other orgs/āteams have been created or grown.
But the community also gained a lot more āseriously interestedā people and a lot more funding.
So overall the bottlenecks are still strong in that it still seems quite high-leverage to find better ways of scalably using labor (especially ājuniorā labor) and money. But it also feels worth recognising that substantial progress has been made and so a bunch more good stuff is being done; there being a given bottleneck is not in itself exactly a bad thing (since itāll basically always be true that something is the main bottleneck), but more a clue about what kind of activities will tend to be most impactful on the current margin.
This comment sounds like itās partly implying āRP seems to have recently overcome these bottlenecks. How? Does that imply the bottlenecks are in general smaller now than they were then?ā I think the situation is more like āThe bottlenecks were there back then and still are now. RP was doing unusually well at overcoming the bottlenecks then and still is now.ā
The rest of this comment says a bit more on that front, but doesnāt really directly answer your question. I do have some thoughts that are more like direct answers, but other people at RP are better placed to comment so Iāll wait till they do so and then maybe add a couple things.
(Note that I focus mostly on longtermism and EA meta; maybe Iād say different things if I focused more on other cause areas.)
In late 2020, I was given three quite exciting job offers, and ultimately chose to go with a combo of the offer from RP and the offer from FHI, with Plan A being to then leave FHI after ~1 year to be a full-time RP employee. (I was upfront with everyone about this plan. I can explain the reasoning more if people are interested.)
The single biggest reason I prioritised RP was that I believe the following three things:
āEA indeed seems most constrained by things like āmanagement capacityā and āorg capacityā (see e.g. the various things linked to from scalably using labor).
I seem well-suited to eventually helping address that via things like doing research management.
RP seems unusually good at bypassing these bottlenecks and scaling fairly rapidly while maintaining high quality standards, and I could help it continue to do so.ā
I continue to think that those things were true then and still are now (and so still have the same Plan A & turn down other exciting opportunities).
That said, the picture regarding the bottlenecks is a bit complicated. In brief, I think that:
The EA community overall has made more progress than I expected at increasing things like management capacity, org capacity, available mentorship, ability to scalably use labor, etc. E.g., various research training programs have sprung up, RP has grown substantially, and some other orgs/āteams have been created or grown.
But the community also gained a lot more āseriously interestedā people and a lot more funding.
So overall the bottlenecks are still strong in that it still seems quite high-leverage to find better ways of scalably using labor (especially ājuniorā labor) and money. But it also feels worth recognising that substantial progress has been made and so a bunch more good stuff is being done; there being a given bottleneck is not in itself exactly a bad thing (since itāll basically always be true that something is the main bottleneck), but more a clue about what kind of activities will tend to be most impactful on the current margin.