Anand Kannappan ✓

@anandnk24

co-founder and ceo @PatronusAI (series B). prev AI @Meta evals, RL, data ⚡️

1 583Followers

569Following

285Posts total

135.1KViews on collected posts

Against accounts of the same size

6 posts from the last 90 days, next to the under 10K follower range. reaches fewer people than peers, but engages them much harder.

Median views309this account3 020median for under 10K

Reach, %19.52%this account191.81%median for under 10K

Engagement, %2.96%this account1.52%median for under 10K

Metric	This account	Median for under 10K	Ratio
Median views per post	309	3 020	0.10×
Reach (views ÷ followers)	19.52%	191.81%	0.10×
Engagement rate	2.96%	1.52%	1.94×

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

133.6K3 Sep

350

555

209

268

664 Sep

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.10%3 Sep

2.86%

2.88%

3.83%

4.48%

3.03%4 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.52%.

What the audience does

Likes63.7%142 in total

Reposts6.7%15 in total

Replies5.4%12 in total

Quotes7.2%16 in total

Bookmarks17.0%38 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

@anandnk24 Aside from the fact that my kids are already hard at work trying to beat the agents on this, there have always been deep insights on agent advancement we can glean from how they play games. Great job as always by @anandnk24 and team @PatronusAI. 66 views · 2 likes · 0 reposts · 0 replies 04 Sep 2026 We find that agents often inherit a slower route than the best human players, and route freely when not. Additionally, giving a model a seed makes the task tractable for weaker agents, since several models failed to reach the goal from scratch at all and many models cannot http 268 views · 11 likes · 0 reposts · 1 replies 03 Sep 2026 Website: https://t.co/CFZ3zpgM3n Paper: https://t.co/wGJti51WYN Blog: https://t.co/Z9MxZLCFQD Benchmark: https://t.co/BSEzZRuJUW 209 views · 8 likes · 0 reposts · 0 replies 03 Sep 2026 We set up a demo at https://t.co/KmpLixqu2O, where you can pick any model and any game and play them in the browser. https://t.co/DWO9XjBlV0 555 views · 15 likes · 0 reposts · 1 replies 03 Sep 2026 Most game benchmarks measure “can the agent complete the game”? That metric basically saturates the moment frontier models complete the game. Human speedrunning communities have spent decades pushing the same games well past completion by discovering new routes and techniques, ht 350 views · 9 likes · 0 reposts · 1 replies 03 Sep 2026 Today, we’re releasing SpeedrunBench: the first benchmark that measures how fast agents can beat video games. We asked frontier models not to simply complete video games, but to speedrun them - across 10 titles like Mario Kart and Pokemon. On simpler games, agents get close to 133.6K views · 97 likes · 15 reposts · 9 replies 03 Sep 2026