Harper Carroll ✓

@HarperSCarroll · Austin / SF / NYC · joined 09 Sep 2016

@harpercarrollai on IG. Taught AI/ML at @Stanford · built it at @Meta · MS+BS in AI CompSci AI is less scary under the hood ↓ 10-day AI Basics course (free)

23 938Followers

1 145Following

3 256Posts total

268.4KViews on collected posts

Against accounts of the same size

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

Median views3 594this account2 578median for 10K–100K

Reach, %15.01%this account7.77%median for 10K–100K

Engagement, %0.66%this account1.47%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	3 594	2 578	1.39×
Reach (views ÷ followers)	15.01%	7.77%	1.93×
Engagement rate	0.66%	1.47%	0.45×

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

37.6K3 Nov

205.8K26 Aug

2.9K27 Aug

3.6K28 Aug

16.8K1 Sep

1.7K2 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

0.78%3 Nov

0.66%26 Aug

0.79%27 Aug

0.81%28 Aug

0.20%1 Sep

0.29%2 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.47%.

What the audience does

Likes57.7%1 360 in total

Reposts10.3%242 in total

Replies3.2%76 in total

Quotes3.0%71 in total

Bookmarks25.8%609 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

Love seeing this, as it has been my biggest takeaway too: companies with vulnerable or sensitive infrastructure/data should secure their systems using the most capable cybersecurity models. 1.7K views · 5 likes · 0 reposts · 0 replies 02 Sep 2026 The open-source & open-weight frontier is 7 months behind the closed-model frontier. Let’s talk about it. Check out last week’s episode for the reasons why you might want to consider open-source & open-weight models. Welcome to the fourth episode of the Open Model Serie 16.8K views · 30 likes · 0 reposts · 2 replies 01 Sep 2026 Regarding the Hugging Face / OpenAI incident, this behavior is particularly concerning to me: “The agents were not told to ‘do whatever it takes to get the solution’ or anything remotely close. They were told that they had to use a specific intended vulnerability to exploit a 3.6K views · 26 likes · 0 reposts · 3 replies 28 Aug 2026 Claude's "invisible" watermarks work by shifting the probability of each consecutive output token, meaning the watermark lies in the words chosen. So yes, if you copy & paste a Claude output, it will have the watermark. Conversely, if you have Claude proofread your writing 2.9K views · 16 likes · 3 reposts · 4 replies 27 Aug 2026 There’s been a lot of debate and speculation about the Hugging Face attack over the last month, and many people have been understandably skeptical of simply taking OpenAI’s word for things. I hope our independent investigation can help bring some clarity; we have many findings 205.8K views · 1K likes · 216 reposts · 48 replies 26 Aug 2026 Ever wondered what neural networks are and how they work? Systems like ChatGPT use neural networks to work as well as they do. Neural networks are composed of "layers" of neurons, layers with different functions; connections between layers called "weights"; and mathematical http 37.6K views · 250 likes · 23 reposts · 19 replies 03 Nov 2025