3 measurements spanning 3 days, net -2. 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 1,383–1,385 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
10 Aug 2026, 16:31
1,383
-2
8 Aug 2026, 01:37
1,385
no change
7 Aug 2026, 11:17
1,385
first reading
Engagement
19 posts held, back to 1 April 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
12.2%
avg views ÷ 1,383 subscribers
Avg views / post
169
4 posts measured
Reaction rate
5.93%
reactions ÷ views · ER floor
Posts in window
4
of 19 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 30 July 2026
Posts held
19 (1 April 2026 – 30 July 2026)
Views total
674
Reactions total
40
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 11:17 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
179 reactions across 19 posts, in 13 distinct kinds. The most used accounts for 30.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
54
30.2%
👍
51
28.5%
😁
23
12.8%
💯
17
9.50%
👏
9
5.03%
🤣
9
5.03%
❤
7
3.91%
😱
3
1.68%
❤🔥
2
1.12%
🌚
1
0.559%
🏆
1
0.559%
👌
1
0.559%
🙏
1
0.559%
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 19 of the 19 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 179reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 1 April 2026 to 30 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.
Telegram Stars
Stars received
10
across the posts below
Posts paid on
1
of 19 we hold a reading for · 5%
Most on one post
10
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @KaskovLive. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 19 most recent posts we hold for this entry, published 1 April 2026 to 30 July 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Верификатор. Отношусь к AI-коду как к коду от джуна Ловлю дыры41%
Архитектор потока. Не прошу код - проектирую пайплайн на ИИ: кодинг - тесты - сборка - доставка29%
Системный дирижёр. Задаю принципы по которым конвейеры строятся себя сами. Код генерится и чинится24%
The shares total 148%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
ИИ внедрили все. Денег не прибавилось
Свежее исследование от РУССОФТ:
За три года генеративный ИИ в разработке ПО прошёл путь с 12,7% компаний до 72,4%. К концу 2026-го будет 93%.
А теперь то, ради чего стоит остановиться. Оборот в 2025-м вырос больше у тех ИТ компаний, кто ИИ НЕ внедрял - на 14,1% против 7,5% у внедривших. Выручка на сотрудника — тоже выше у «безИИшных».
🤖Это не значит, что ИИ бесполезен. Это зн…
📆Честно говоря, людей которые отсылают на личные ящики корпоративную информацию надо увольнять быстро и безжалостно.
➡️Что касается кормления облачных нейронок корпоративными необезличенными данными - как по мне тоже, следом за первыми
🔘А у вас в компаниях в должностные инструкции внесены допущения про использование ИИ сотрудниками?
🔘А правила обращения с даннымидля ИИ описаны?
🔘А что с ответственностью?
🔘А как дел…
🔝Что придёт на смену САПР
Вышло моё интервью в «Стимуле».
📰 Короткий тезис: за тысячи лет принцип работы инженера не менялся. В Древнем Египте — папирус и тростниковая палочка, потом перо, бумага, карандаш. Затем в руках оказалась мышка, а вместо ватмана — монитор. Инструмент менялся. Действие — нет: инженер выдумывает в голове и вручную переносит на носитель.
САПР этот принцип не сломал. Он его оцифровал.
🔆 Мы в…
🧠 ИИ ищет идеи в корпоративных чатах
В VK Tech решили систематизировать все сообщения в корпоративных мессенджерах с помощью нейросети, рассказал руководитель направления ИИ компании Роман Стятюгин на ЦИПР.
💬 Мы получили возможность по ключевым словам находить интересные решения, на которые в общем потоке переписок по каким-то причинам не обратили внимание, – отметил эксперт.
Так ИИ открывает возможность не пропус…
Уважаемые прекрасные руководители, отправьте, пока лето, сотрудников на удалёнку.
И пробок меньше и ажиотаж ниже будет...
Тем более что где-то он есть, где-то его нет
Всем будет проще
🗑«AI работает у 85% компаний». Серьёзно? (лонгрид!)
В январе EY выпустила свежий CEO Outlook 2026. Опросили 1200 CEO крупных компаний. Главный заголовок, который цитируют все: подавляющее большинство руководителей говорят, что их AI-инициативы оправдали или превзошли ожидания.
Умереть не вставать - это было неожиданное заявление.
Цифра разошлась и красуется на каждой второй презентации про внедрение ИИ.
Звучит как…
✍️Есть большинство — те, кто купили лицензии Copilot, провели пилот, отчитались «мы внедрили AI» — и продолжают работать как раньше. Эффект на производительность — около нуля.
Это парадокс Солоу 2.0.
Что с этим делать руководителю?
Не верить ни одному источнику в отрыве от остальных.
🔘 EY показывает направление — куда смотрят CEO, какие приоритеты в инвестициях
🔘 PwC, NBER, MIT показывают результат — что реально…
💚Друзья, прошу помощи — нужны ваши ответы
Запустил исследование: как люди на самом деле относятся к ИИ.
Не нравится мне теория с конференций, и пресс-релизы вендоров
Нужна живая картина — кто пользуется, кто игнорирует, кто опасается, кто разочарован. Результаты войдут в мою научную публикацию.
Что важно:
➡️ Опрос полностью анонимный — не собираю ни имени, ни почты, ни IP
➡️ Нет правильных ответов. Если вы ИИ н…
Наконец-то упростили экспериментальные правовые режимы для ИИ
10 июня — параллельно с отклонением маркировки ИИ-контента — Госдума одобрила другую инициативу: расширение экспериментальных правовых режимов (ЭПР) для технологий искусственного интеллекта.
Что изменилось:
➡️ Запуск экспериментов теперь быстрее — упрощены процедуры согласования
➡️ Расширены сферы применения: транспорт, медицина, финансы, госуслуги
➡️ С…
👍4❤1🔥1
Showing the 12 most recent of 19 posts we hold for @KaskovLive. 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.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Верификатор. Отношусь к AI-коду как к коду от джуна Ловлю дыры41%
Архитектор потока. Не прошу код - проектирую пайплайн на ИИ: кодинг - тесты - сборка - доставка29%
Системный дирижёр. Задаю принципы по которым конвейеры строятся себя сами. Код генерится и чинится24%
The shares total 148%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none.The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100.Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 19 most recent posts we hold, published 1 April 2026 to 30 July 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Citation-graph rank
Citation-graph rank — 922,742 of 1,160,990entries 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
Names
Channels on the register whose handles appear in this channel's posts.
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 10 August 2026 — this
entry's latest reading, not the date you are reading this.
“ValentinChiefIT” (@KaskovLive), 1,383 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/KaskovLive.
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.