Pratham engagement report
@Prathkum - 449K followers on X
Measured over 33 original posts from a 30-day window, last computed on September 23, 2026.
Engagement
A typical post picks up 101 interactions against 449K followers, an engagement rate of 0.022%. Measured over 33 original posts, its engagement rate beats 46% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 15K times each, and 0.688% of those impressions turn into an interaction. That is about 3.27% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.4 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 13:00 UTC, and Wednesday is the busiest day of the week. Of the 33 posts sampled, 42% carry an image or video and 9% link out. The account's strongest tracked post pulled 22K interactions, about 220x its own typical post.
Measured over 33 original posts from a 30-day window, last computed on September 23, 2026.
Compared with accounts its own size
Pratham's engagement rate beats 46% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 38% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.022%, Pratham sits above the 10th percentile of the 204,491 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 13:00 UTC, and Wednesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 42% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 9% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 42% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 9% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 348 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Sep 7, 2026220x their median
I think I can officially say: we are so back
- Aug 28, 2026100x their median
GLM-5.3 is now open-weight. Our most capable model for agentic coding and cyber defense is now available to download, run, and customize. Weights: https://t.co/v1IbWMXxg4 Tech blog: https://t.co/ekQkO83jCv https://t.co/f8XlJksKyf
- Sep 15, 202620x their median
Anthropic CEO: "AI development needs to slow down" OpenAI CEO: "Completely agree" Two months later: Anthropic: Introducing Fable 5.2 OpenAI: Introducing GPT 6.1
- Aug 23, 20266.0x their median
Hot take: We don't need GitHub anymore. Or at least we need a new version of it, designed agent-first. GitHub made sense when humans wrote code by hand. Developers needed a place to store code, iterate on it, and keep it backward compatible so if something broke, you could go back to a previous log and fix it. The whole workflow, PRs, issues, review, was built around a human being the one writing and reading every change. Coding has changed now. Agents write code and iterate at lightning speed. Why would an agent waste time reviewing its own code the way a human reviews a PR, when it can just reiterate and fix things in the same breath? The bottleneck GitHub was designed to manage doesn't really exist anymore. We are early, so most agent workflows just bolt onto GitHub because it's what's there, not because it's the right interface. The real shift is from reviewing diffs to grading outcomes. Whatever wins here won't be GitHub with an AI button, it'll be built agent-first from scratch.
- Sep 11, 20265.8x their median
Everyone forgets DeepSeek started this whole open-weight movement. I still remember R1 dropped in Jan 2025 and everyone realized open-weight models could be useful. They were competitive with frontier closed models, which made everyone realize how expensive closed AI is. On paper, DeepSeek V4.1 Flash already beat Astra in SWE bench. DeepSeek V4.1 Flash: 74.2% GPT-6 Astra: 74.1% This number definitely looked inflated and they might increase the compute just to go above 74.1%. But the cost difference is massive. DeepSeek V4.1 Flash (open) → $0.30/$1.20 GPT-6 Astra (closed) → $10/$50 per MTok Open-weight models are something we all should take seriously.
- Aug 16, 20263.6x their median
Anthropic is so quiet these days!? 👀 They literally didn’t predict that people wouldn’t care about Fable as much as they expected. Launched Opus 5 in a panic. Now nobody is looking forward to Opus 5.1 either. They need another Claude Code moment to build momentum again.
- Aug 24, 20263.0x their median
So ultimately Fable is the most flopped thing Anthropic has ever launched.
- Aug 19, 20263.0x their median
People saying computer science is dead because of AI are usually the ones who think computer science is just coding.
- Aug 27, 20262.9x their median
Fable 5.1 is coming. But Anthropic isn’t creating unnecessary hype around it this time. That makes me think they are locked in on building the best model they can. I am hopeful Anthropic is about to make a strong comeback.
- Sep 5, 20262.7x their median
Astra launched by OpenAI is one of the craziest incidents in the AI world. People are going crazy in the same way they did when ChatGPT first dropped. Best model. Less verbose. Less token consumption per task. Clean part is that OpenAI didn’t try to create unnecessary hype around it like other labs do. They just dropped it and let the users decide. Astra has put a huge dent in Anthropic, and they will have to make a strong comeback.
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 101 interactions against 449K followers, an engagement rate of 0.022%. Measured over 33 original posts, its engagement rate beats 46% of 20,444 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 15K times each, and 0.688% of those impressions turn into an interaction. That is about 3.27% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.4 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 13:00 UTC, and Wednesday is the busiest day of the week. Of the 33 posts sampled, 42% carry an image or video and 9% link out. The account's strongest tracked post pulled 22K interactions, about 220x its own typical post.
- What is Pratham's engagement rate on X?
- Pratham (@Prathkum) has an engagement rate of 0.022%, based on the median interactions across 33 original posts from the last 30 days against 448,857 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.022%, Pratham sits above the 10th percentile of the 204,491 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @Prathkum have real engagement?
- Its engagement rate beats 46% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @Prathkum post?
- Most posts go out around 13:00 UTC, and Wednesday is its busiest day, at roughly 3.4 posts per day across the measured window.