This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
4 measurements spanning 7 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 4,109–4,125 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 11:17
4,123
+12
10 Aug 2026, 13:08
4,111
-8
7 Aug 2026, 03:07
4,119
-3
6 Aug 2026, 05:49
4,122
first reading
Engagement
11 posts held, back to 2 July 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 5 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
10.6%
avg views ÷ 4,123 subscribers
Avg views / post
439
6 posts measured
Reaction rate
1.48%
reactions ÷ views · ER floor
Posts in window
6
of 11 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 28 July 2026
Posts held
11 (2 July 2026 – 28 July 2026)
Views total
2,632
Reactions total
39
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 12:18 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.
Reaction mix
84 reactions across 11 posts, in 13 distinct kinds. The most used accounts for 31.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
26
31.0%
👍
23
27.4%
❤
11
13.1%
😁
8
9.52%
🤝
5
5.95%
🏆
4
4.76%
🍾
1
1.19%
🎉
1
1.19%
👀
1
1.19%
💯
1
1.19%
😍
1
1.19%
😱
1
1.19%
🤯
1
1.19%
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 11 of the 11 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 84reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 2 July 2026 to 28 July 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.
🤔 ЧЕЛОВЕК С ОСТАТКОМ ЛИМИТА
🤫 Показываю свой скриншот из Codex. Лимиты почти целы. Раньше такая картинка радовала: экономный хозяин, токены не транжирит. Теперь смотрю на неё как на справку о собственной недоработке. Андрей Карпати признался в подкасте No Priors: «Я нервничаю, когда у меня остаётся лимит. Значит, я не максимизировал поток токенов». Во времена аспирантуры его так же тревожили простаивающие GPU. Тепер…
🤔Какие ИИ-стартапы исчезнут, почему фриланс уже теряет рынок и какие компании смогут выжить в эпоху нейросетей?
🟢 В новом выпуске Александр Горный без лишнего оптимизма разбирает, что на самом деле происходит с бизнесом, SaaS, профессиями и рынком труда.
🟢Это разговор не о далёком будущем. Уже сейчас нейросети меняют работу программистов, копирайтеров, переводчиков, врачей, юристов и авторов контента. Вы узнаете, п…
🤔 Недавно был на мероприятии «Человек читающий» - вокруг предприниматели, топ-менеджеры и разговоры про нейросети.
🟢 Но пока большинство только обсуждает AI, рынок уже уходит дальше в Vibe Coding. И скоро платить сотни тысяч за простой сервис, бота, аналитику или автоматизацию будет выглядеть так же странно, как нанимать отдельного человека, чтобы он вручную отправлял письма.
🤔 Раньше для запуска цифрового продукта…
✅ ИИ в помощь семье
Я постоянно использую нейронки в бытовых вопросах. Сегодня покажу на примере трех задач, хотя список можно перечислять безконечно.
✅ Примеры:
• Семейное автопутешествие
• Выбор секции для ребенка
• Семейный календарь распределения дел
Промпты в коментариях, а для удобства их потестировать можете воспользоваться Алиса АИ - https://alice.yandex.ru
🤔 Если вы до сих пор думаете, что Skyeng вырос только благодаря удачной идее, этот разговор быстро разрушит иллюзии.
🟢 В новом выпуске подкаста мы поговорили с Денисом Сметневым, основателем Skyeng, о том, как на самом деле строятся компании стоимостью в миллиарды: какие решения приходится принимать, какие ошибки оказываются самыми дорогими и почему большинство предпринимателей сами ограничивают рост своего бизнеса.…
Тут такое дело 🤔
🤔 Предпринимателям, руководителям и экспертам нужны надёжные источники, которые могут дать другой взгляд на проблемы и помочь найти реальные решения
Вот папка в которой я оказался как раз с такими экспертами.
В папке кстати есть чат “Заяви о себе”, где можно представить свой бизнес и находить потенциальных клиентов. Использовать адекватно и аккуратно)
⏳ Бесплатный доступ будет открыт всего 5 дней
😈 Без хейта!)
🤔 Просто смешно и прямо перед глазами кроется истина. Как сделать что-то в нейронках за 2 минуты - а само объяснение в час)
👀 Да да это обучение я понимаю, но суть тут в том что раньше продавали и до сих пор легкие деньги, а теперь супер скорость. Прокачивать интеллект продается хуже)
🫡 Но важный поинт, тебе чтобы получить качественный результат все равно придется поработать. Просто не 2 часа на зада…
😈 Люда б*я, у нас отмена!
🤡 Меня что-то порядком затрахало что каждый день в ленте появляется очередной «убийца GPT», «новая эра ИИ», «бесплатная нейронка, которая делает всё» и прочий цирк с конями, клоунами и кнопкой “успей, пока не закрыли”. Проблема даже не в том, что новые инструменты появляются. Это нормально. Проблема в том, что вокруг них моментально рождается тонна пиздежа: кто-то где-то увидел пост, кто-то…
🔥4👍2😁2❤1🏆1💯1
Showing the 11 most recent of 11 posts we hold for @r1isaev. 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 — 224,467 of 1,169,250entries 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.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“ISA Roman | ИИ41” (@r1isaev), 4,123 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/r1isaev.
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.