Pau Labarta Bajo engagement report
@paulabartabajo_ - 80K followers on X
Measured over 4 original posts from a 30-day window, last computed on September 16, 2026.
Engagement
Early reading. We have captured 4 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.
A typical post picks up 20 interactions against 80K followers, an engagement rate of 0.028%. Posts are seen about 2.6K times each, and 0.78% of those impressions turn into an interaction. That is about 3.22% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.2 posts a day over the last 30 days, though only 17% of days saw any activity at all. Most posts go out around 07:00 UTC, and Tuesday is the busiest day of the week. Of the 4 posts sampled, 50% carry an image or video and 25% link out. The account's strongest tracked post pulled 4.6K interactions, about 228x its own typical post. Only 4 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
Measured over 4 original posts from a 30-day window, last computed on September 16, 2026.
Where this sits in the catalog
At 0.028%, Pau Labarta Bajo sits above the 25th percentile of the 151,176 accounts in this comparison. That places it in the below the median band, which runs 0.021% to 0.126%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.003% |
| 25th percentile | 0.021% |
| 50th percentile | 0.126% |
| 75th percentile | 0.6% |
| 90th percentile | 2.29% |
| 99th percentile | 84.3% |
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 07:00 UTC, and Tuesday 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 | 50% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 25% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 50% 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.
- 25% 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 233 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.
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
- May 13, 2026228x their median
If AI was trained on the internet, where the hell did all the em-dashes come from? They weren't there before.
- Jul 7, 2026120x their median
Here's a step-by-step process to kill all the bloat from your Claude Code system prompt: 1. Run a proxy so you can see exactly what gets sent to Claude Code (included in the article) 2. "Fuck, there is so much cruft in there" 3. Use my settings.json to kill all the bloat Down to a clean 13K tokens to start each session with. Nice. Full process here: https://t.co/Kie84HMe2A
- Jul 24, 202689x their median
How to graph-max with Codex and 5.6 Sol: 1. Draw a graph (literally in any tool, even on paper) 2. Send it to Codex and say "write a code mode script that implements this workflow, run it with <your inputs>" There's no step 3, it just works. Seriously it's that simple. https://t.co/TBHmsTOFEI
- Jul 28, 202656x their median
Today we release LFM2.5-Encoder-230M and LFM2.5-Encoder-350M: bidirectional encoders that stay fast at long context, even on CPU. > LFM2.5-Encoder-230M: about 3.7x faster than ModernBERT-base on CPU at 8,192 tokens. Under 30s per forward pass, versus over a minute and a half. > LFM2.5-Encoder-350M: 4th of 14 models on GLUE, SuperGLUE, and multilingual classification, behind only three larger models, one of them nearly 10x its size. 🧵
- Jul 2, 202654x their median
What's the most ambitious project you have Fable working on right now?
- Sep 8, 202638x their median
GPT-6 Astra brought data labeling to the farm. >Labels 200+ animals with individual IDs >Flags animals that may need inspection or veterinary care >Creates images for livestock listings with GPT Image 2.5 on Higgsfield This is how AI can help industries like agriculture solve practical problems and make people’s work easier.
- Aug 4, 202621x their median
by popular demand - the new SlopCodeBench results are out for the new frontier: Fable 5, GPT-5.6-Sol, and Kimi K3 Live stream starting now to review the results!!! https://t.co/TwrQq4R8s7
- Jul 29, 202617x their median
Two ways to be a fool in software engineering right now: 1. Never touch AI-assisted workflows, never iterate, never compound the gains. 2. Believe “software factories” are real and that agents can autonomously solve 99% of the work. The truth is boring: build your own workflow, iterate weekly.
- Jul 1, 20265.5x their median
Personal updates: After 9 super intense, challenging and fun months at @liquidai I’ve decided it is time for me to take a break, breath, reconnect with myself, family and friends and get ready for the next adventure. What’s next? I want to help you and your company build AI that works. I will get back to building high quality courses and doing contracting work, which condense everything I ve learned working at a foundational AI company and over the lasr decade. Finally, I am in the process of moving back to my home town Barcelona, and I will spend the whole summer there. I would like to help grow the local AI community here. If you are passionate about building stuff that can change the world for good, send me a DM and we can even go for a beer 😊
- Jul 12, 20263.6x their median
You can run (very slowly) (almost) frontier GLM-5.2 on a 25GB machine. Sexy. A bit hacky, but nonetheless a beautiful open source contrbution showing that memory is not a hard wall. Now, be a good sould and give them a well deserved star on github ⬇️ https://t.co/mGOYfEyur7
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 20 interactions against 80K followers, an engagement rate of 0.028%. Posts are seen about 2.6K times each, and 0.78% of those impressions turn into an interaction. That is about 3.22% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.2 posts a day over the last 30 days, though only 17% of days saw any activity at all. Most posts go out around 07:00 UTC, and Tuesday is the busiest day of the week. Of the 4 posts sampled, 50% carry an image or video and 25% link out. The account's strongest tracked post pulled 4.6K interactions, about 228x its own typical post. Only 4 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.
- What is Pau Labarta Bajo's engagement rate on X?
- Pau Labarta Bajo (@paulabartabajo_) has an engagement rate of 0.028%, based on the median interactions across 4 original posts from the last 30 days against 79,578 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.028%, Pau Labarta Bajo sits above the 25th percentile of the 151,176 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 @paulabartabajo_ have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @paulabartabajo_ post?
- Most posts go out around 07:00 UTC, and Tuesday is its busiest day, at roughly 0.2 posts per day across the measured window.