Bilgin Ibryam engagement report
@bibryam - 85K followers on X
Measured over 44 original posts from a 30-day window, last computed on September 2, 2026.
Engagement
A typical post picks up 42 interactions against 85K followers, an engagement rate of 0.049%. Measured over 44 original posts, its engagement rate beats 37% of 6,874 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 3.4K times each, and 1.22% of those impressions turn into an interaction. That is about 4.01% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 09:00 UTC, and Sunday is the busiest day of the week. Of the 44 posts sampled, 45% carry an image or video and 91% link out. The account's strongest tracked post pulled 1.2K interactions, about 29x its own typical post. Recurring topics include #devoxx, #kubernetes.
Measured over 44 original posts from a 30-day window, last computed on September 2, 2026. Recurring tags: #devoxx, #kubernetes.
Compared with accounts its own size
Bilgin Ibryam's engagement rate beats 37% of the tracked X accounts closest to it in follower count (6,874 accounts, accounts of similar size (decile 5 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 49% 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 0.049%, Bilgin Ibryam sits above the 25th percentile of the 66,128 accounts in this comparison. That places it in the below the median band, which runs 0.016% to 0.1%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.016% |
| 50th percentile | 0.1% |
| 75th percentile | 0.499% |
| 90th percentile | 2.09% |
| 99th percentile | 119.9% |
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 09:00 UTC, and Sunday 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 | 45% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 91% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 45% 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.
- 91% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
- Its average post runs 235 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
- Jun 24, 202429x their median
Java is dead Kubernetes is dead DevOps is dead And now: Serverless is dead... In this context, 'dead' means: mature, stable, well understood by the industry. It's not the hot topic for marketing, devrel, or conferences anymore.
- Aug 29, 20268.7x their median
https://t.co/C7uN2Vdu03
- Aug 23, 20267.2x their median
🎯 Just Use Postgres! by @denismagda This has to be one of the coolest titles for a book: The practical takeaway: before adding a specialty database, check what Postgres already handles. A real fast guide on: • JSON and full-text search • AI/RAG, time series, geospatial data, and queues https://t.co/nyRi0rslCK via @ManningBooks
- Aug 30, 20264.5x their median
Oracle: Agent memory is a database problem. Turso: Treat agent state like a filesystem, but implement it as a database TroveFiles: Filesystem-as-memory Mem0: Your AI Agent’s Memory Is Just a File? That’s the Problem. Neo4j: Memory should be a context graph Vercel: Agent memory is a state problem, not a memory problem ...
- Aug 30, 20264.5x their median
There's no reason for software to be slow anymore https://t.co/BHNBedtkdc
- Aug 16, 20264.0x their median
https://t.co/hSlBRCjbYE
- Aug 30, 20263.9x their median
GitHub reviewed 2,500+ agents.md files. Five patterns stood out: • Put commands early • Show code, not prose • Name the exact stack • Set clear boundaries • Cover tests, structure, style, and Git An agent needs an operating manual, not a personality. https://t.co/GShsUymmkO 👆 Use it as a review checklist, not another generic prompt template.
- Aug 16, 20263.9x their median
Good system design starts before the architecture diagram. Donne Martin’s System Design Primer: 1. define use cases and constraints 2. sketch the high-level design 3. design core components 4. scale around bottlenecks https://t.co/D6P9JIdS8d https://t.co/61XkCCe9h9
- Aug 23, 20263.5x their median
Git at any scale - @cursor_ai 👏 A write‑ahead‑log first Git storage system on S3 gives fully consistent, horizontally scalable push and clone performance, solving Spokes’ replication and consistency limitations. Enables up to 120 pushes/s on S3 Standard and 300+ pushes/s on S3 Express One Zone . https://t.co/9MxdqybPU4
- Aug 29, 20263.0x their median
Taking AI agents to production takes more than deployment: • governed data and memory • evaluation before release • security and guardrails • observability after launch Google maps the lifecycle from development to production. https://t.co/Hqq3qxbWOt https://t.co/88RoCXndxA
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 42 interactions against 85K followers, an engagement rate of 0.049%. Measured over 44 original posts, its engagement rate beats 37% of 6,874 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 3.4K times each, and 1.22% of those impressions turn into an interaction. That is about 4.01% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.9 posts a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 09:00 UTC, and Sunday is the busiest day of the week. Of the 44 posts sampled, 45% carry an image or video and 91% link out. The account's strongest tracked post pulled 1.2K interactions, about 29x its own typical post. Recurring topics include #devoxx, #kubernetes.
- What is Bilgin Ibryam's engagement rate on X?
- Bilgin Ibryam (@bibryam) has an engagement rate of 0.049%, based on the median interactions across 44 original posts from the last 30 days against 84,590 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.049%, Bilgin Ibryam sits above the 25th percentile of the 66,128 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 @bibryam have real engagement?
- Its engagement rate beats 37% of the tracked X accounts closest to it in follower count (6,874 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 @bibryam post?
- Most posts go out around 09:00 UTC, and Sunday is its busiest day, at roughly 1.87 posts per day across the measured window.