rajan agarwal ✓

@_rajanagarwal · sf · joined 06 Mar 2018

coding models @openai

12 360Followers

1 600Following

2 220Posts total

6.8MViews on collected posts

Against accounts of the same size

7 posts from the last 90 days, next to the 10K–100K follower range. shown to more people than peers of the same size.

Median views28 902this account1 756median for 10K–100K

Reach, %233.83%this account5.38%median for 10K–100K

Engagement, %1.43%this account1.75%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	28 902	1 756	16.5×
Reach (views ÷ followers)	2.3× audience	5.38%	43.5×
Engagement rate	1.43%	1.75%	0.82×

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

202.9K25 Nov

3.4M19 Aug

6.6K20 Aug

1.7M23 Aug

28.9K24 Aug

1.5M3 Sep

3.8K

5.8K

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.49%25 Nov

0.44%19 Aug

1.43%20 Aug

0.59%23 Aug

2.14%24 Aug

0.64%3 Sep

1.66%

4.28%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.75%.

What the audience does

Likes69.4%30 231 in total

Reposts6.2%2 716 in total

Replies5.1%2 206 in total

Quotes2.9%1 268 in total

Bookmarks16.4%7 121 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

meet GPT-6 Astra! it takes a village to make a model and experience that is this capable, safe, aligned and tasteful. i can feel the agi, and i hope you do too https://t.co/yT8fiqLLdP 5.8K views · 223 likes · 4 reposts · 21 replies 03 Sep 2026 it’s incredible how much everyone is able to contribute towards models and products, the attention to detail, and the speed at which we do it it’s a hard feeling to communicate but inside, everyone feels it 3.8K views · 61 likes · 2 reposts · 0 replies 03 Sep 2026 I think the best way to describe OpenAI's culture is as a mega startup. It's hard to believe unless you see it from the inside. Extreme ownership, care and pace. 1.5M views · 7.8K likes · 168 reposts · 1.6K replies 03 Sep 2026 it is a very hard problem to make models tasteful - it seems like all you need is a group of friends who want to learn something new 28.9K views · 599 likes · 12 reposts · 8 replies 24 Aug 2026 You can just RL a coding model to paint with javascript btw https://t.co/4x5B81kjUh 1.7M views · 8.4K likes · 779 reposts · 245 replies 23 Aug 2026 im so excited for this!! past few years, we’ve learned a lot about scaling general-purpose language models and using post-training/RL to make them more useful as physical pretraining starts producing similarly general capabilities, robotics gets a head start on what to try next 6.6K views · 89 likes · 2 reposts · 3 replies 20 Aug 2026 Introducing GEN-1.5, a one-shot learner. It can learn new tasks in a few seconds. Show it what to do, and it generalizes. This capability emerged from pretraining on physical data at scale, as a step towards our mission of building general intelligence for the physical world. h 3.4M views · 12.1K likes · 1.7K reposts · 316 replies 19 Aug 2026 in order to have research agents that can run for days, we need context compaction i used RL to have LLMs naturally learn their own 10x compression! Qwen learned to pack more info per token (ie use Mandarin tokens, prune text) read the technical blog: https://t.co/3pzRvt4zvr 202.9K views · 891 likes · 58 reposts · 27 replies 25 Nov 2025