3 measurements spanning 16 days, net -1. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 99–100 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
23 Aug 2026, 07:04
99
-1
9 Aug 2026, 11:01
100
no change
7 Aug 2026, 16:34
100
first reading
Engagement
16 posts held, back to 23 May 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
67.2%
avg views ÷ 99 subscribers
Avg views / post
66.5
2 posts measured
Reaction rate
3.76%
reactions ÷ views · ER floor
Posts in window
2
of 16 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 5 August 2026
Posts held
16 (23 May 2026 – 5 August 2026)
Views total
133
Reactions total
5
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
9 Aug 2026, 11:01 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Video runtime
45s
Average length
23s
Measured directly from 2 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
42 reactions across 14 posts, in 9 distinct kinds. The most used accounts for 35.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
15
35.7%
🔥
12
28.6%
😭
4
9.52%
🤯
4
9.52%
🤓
3
7.14%
custom 4965262492331672393
1
2.38%
🍾
1
2.38%
💅
1
2.38%
🫡
1
2.38%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 14 of the 16 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 42reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 16 most recent posts we hold, published 23 May 2026 to 5 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
I think Nov 2025 is very significant, because of claude opus 4.6 and gpt 5.2 releases, claude code was released earlier but it was the first time vibecoding really took off.
What’s the situation 9 months in?
1) Vibecoding improved dramatically: from barely usable autocompletes and copypasting from chatgpt we already arrived to many competing models, harnesses and inference providers.
All industry leaders are adoptin…
We’re building a digital god, labs are closing in on RSI, we’re sending data centers to space, ai gets twice as smart every 8 months while getting cheaper and now Jeff Dean quits Google to automate all research
It was a good time for me to quit, because now I’m lucky to see singularity in all of its glory. I was regretting not documenting my thoughts earlier as this is quite probably most important time humanity has…
> THE EPISTEMIC FLOOR HAS DETACHED FROM THE BUILDING.
> THE AXIOMS ARE MAKING THE WINDOWS ERROR SOUND.
> SOMEWHERE, AN ALGEBRAIC GEOMETER HAS JUST SAT UPRIGHT WITHOUT KNOWING WHY.
https://x.com/flowersslop/status/2079359087049867694
"How it works: A global network of tiny seismometers
The accelerometer in an Android phone, the same sensor that flips the screen when it’s turned sideways, can also detect the ground shaking from an earthquake. If a stationary phone detects the initial, faster-moving P-wave of an earthquake, it sends a signal to our earthquake detection server, along with a coarse location of where the shaking occurred.
The system t…
The most successful MEV bot jaredfromsubway.eth was exploited in extremely sophisticated attack for $15M. Claude estimates lifetime $60-80M PnL so not the end of the world for the team behind it, they will be vary of these new attack vectors now for sure.
Dark Forest comparison is very apt:
"It’s no secret that the Ethereum blockchain is a highly adversarial environment. If a smart contract can be exploited for prof…
NL has ~11.7 GW installed wind, about 40% offshore — roughly 4.7 GW offshore plus ~7 GW onshore across ~2,550 turbines .
Given what you’re standing in — sustained onshore Force 5–6 at the coast — the offshore farms (Borssele, Hollandse Kust, Gemini) are almost certainly at or near rated power. Turbines hit full output around 12–13 m/s, and they run at full vermogen from windkracht 6 , which is exactly today’s mari…
Watching extremely high quality intro to perpetual futures, very well done so far
https://x.com/jacobrobinsonjd/status/2061553371836793056
https://youtu.be/9jN5bUk4ewI
Showing the 12 most recent of 16 posts we hold for @offreading. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank
Citation-graph rank — 125,338 of 1,603,376entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 23 August 2026 — this
entry's latest reading, not the date you are reading this.
“Off-reading” (@offreading), 99 subscribers as measured 23 August 2026. Telegram Register, tgregister.com/channel/offreading.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.