Sayash Kapoor

@sayashk · Princeton · joined 15 Mar 2015

Incoming prof @UCBerkeley AI agents, policy, evals, AI for science Essay/newsletter (AI as Normal Technology): https://t.co/5amOkqLb4A Book (AI Snake Oil): https://t.co/DabpkhNZ2k

14 827Followers

2 437Following

1 637Posts total

237.1KViews on collected posts

Against accounts of the same size

7 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views6 724this account2 751median for 10K–100K

Reach, %45.35%this account9.00%median for 10K–100K

Engagement, %0.73%this account1.65%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	6 724	2 751	2.44×
Reach (views ÷ followers)	45.35%	9.00%	5.04×
Engagement rate	0.73%	1.65%	0.44×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

6.7K27 Jul

173.6K30 Jul

6.6K

9.5K

5.5K

31.3K27 Aug

Last 7 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.96%27 Jul

0.55%30 Jul

0.81%

0.26%

0.73%

0.22%27 Aug

0.97%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.65%.

What the audience does

Likes49.3%995 in total

Reposts9.0%181 in total

Replies4.6%92 in total

Quotes2.3%47 in total

Bookmarks34.8%703 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Latest posts

I’ll be joining the @MTSlive stream in an hour or so to talk about our work on evaluating open-ended AI research (https://t.co/BCnIMkxbok) and to share some thoughts on the OpenAI HuggingFace incident. 4K views · 33 likes · 3 reposts · 3 replies 27 Aug 2026 METR REPORT | NVIDIA RIPS | ROBOT ATHLETICS https://t.co/yebsV9CZdz 31.3K views · 49 likes · 5 reposts · 9 replies 27 Aug 2026 One of the best parts of working on CRUX has been the diversity of priors/opinions in the coauthor group. I'm glad we had Seth's feedback (and pushback) on our results and interpretations. The paper is stronger as a result. On that note, we are open to adversarial collaboration: 5.5K views · 31 likes · 5 reposts · 4 replies 30 Jul 2026 I am really enjoying these *CRUXes*. I was definitely more bullish on agents' prospects for writing a neurips-worthy paper than most, but that was largely because of, ahem, a certain scepticism about that as a bar. Still, this was definitely an update for me, as of now—but like 9.5K views · 20 likes · 4 reposts · 0 replies 30 Jul 2026 ICYMI: We plan to continue these evals and are looking to collaborate with AI researchers who have unpublished, open-ended research. If you would like to test frontier agents on your research questions, we'd love to hear from you: https://t.co/6pBgCyGmdI 6.6K views · 46 likes · 3 reposts · 3 replies 30 Jul 2026 Can AI agents conduct open-ended AI research? Most evaluations of agents conducting AI research focus on narrow, verifiable tasks. But AI research is often open ended. Researchers pick hypotheses, decide what evidence is appropriate, and recognize a failing approach. We gave h 173.6K views · 705 likes · 145 reposts · 68 replies 30 Jul 2026 How can academics impact AI policy? I had the pleasure of talking to @r_zwetsloot about my PhD experience in AI policy. While the interview is about policy impact, most of the points apply to AI research broadly. https://t.co/o4uWDfkZOY 6.7K views · 111 likes · 16 reposts · 5 replies 27 Jul 2026