Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 97% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
31 measurements spanning 43 days, net -139. 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 10,628–10,809 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 31
Measured (UTC)
Subscribers
Change
18 Sept 2026, 03:17
10,649
-8
15 Sept 2026, 19:02
10,657
-9
14 Sept 2026, 02:38
10,666
-7
12 Sept 2026, 12:00
10,673
-15
10 Sept 2026, 07:57
10,688
-16
7 Sept 2026, 03:00
10,704
-12
4 Sept 2026, 10:55
10,716
-10
1 Sept 2026, 23:05
10,726
-1
31 Aug 2026, 21:45
10,727
-9
30 Aug 2026, 20:45
10,736
-1
29 Aug 2026, 22:03
10,737
-1
28 Aug 2026, 18:36
10,738
+1
27 Aug 2026, 21:23
10,737
-4
26 Aug 2026, 18:07
10,741
-3
25 Aug 2026, 15:33
10,744
-1
24 Aug 2026, 18:43
10,745
-2
22 Aug 2026, 23:55
10,747
-6
21 Aug 2026, 11:18
10,753
-4
20 Aug 2026, 11:07
10,757
-7
19 Aug 2026, 10:37
10,764
first reading
Engagement
29 posts held, back to 16 June 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 40 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
11.5%
avg views ÷ 10,649 subscribers
Avg views / post
1,220
4 posts measured
Reaction rate
2.10%
reactions ÷ views · ER floor
Posts in window
4
of 29 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 31 August 2026
Posts held
29 (16 June 2026 – 31 August 2026)
Views total
4,897
Reactions total
103
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
1 Sept 2026, 20:26 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
1,690 reactions across 28 posts, in 21 distinct kinds. The most used accounts for 70.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,184
70.1%
🔥
244
14.4%
❤🔥
89
5.27%
👍
56
3.31%
😁
27
1.60%
👏
24
1.42%
😭
17
1.01%
👀
11
0.651%
💔
11
0.651%
🐳
7
0.414%
🥰
5
0.296%
👌
4
0.237%
🤔
2
0.118%
🥴
2
0.118%
👎
1
0.059%
💅
1
0.059%
💯
1
0.059%
😴
1
0.059%
🙏
1
0.059%
🤮
1
0.059%
1 further kind
1
0.059%
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 29 of the 29 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 1,690 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 29 most recent posts we hold, published 16 June 2026 to 31 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.
Что делать, если надо прокачивать новые навыки, а сил и энергии нет?
Этот вопрос прислали, пока мы готовили завтрашний эфир о том, как адаптироваться к рынку труда в 2027 году с Вероникой Климовой.
Ответ вам понравится:
не пытаться освоить всё, а сфокусироваться на задачах, которые становятся критическими для бизнеса и вашей роли.
Смотреть не на AI-инструменты в целом, которые «надо освоить». Масштаб этой задачи б…
В 2026-м, похоже, мы вошли в эпоху пожизненной смены карьеры.
Как мы к этому пришли?
2005–2013: эпоха «деньги — статус — стабильность»
Золотые годы корпоративной лестницы. Ты выбирал направление, держался его и собирал должности. Менять работу раз в два года было красным флагом. Единственный альтернатива найму — свой бизнес, но это дорого, гемморойно и точно не для всех.
2014–2019: эпоха «найди своё призвание»
Пре…
Суперкомбо этой осени: зарплата перестала соответствовать стоимости жизни + задачи не развивают + статус больше не впечатляет + неопределённость рынка.
По отдельности всё это ещё терпимо. Но в комбинации превращается в ощущение: «Всё, надо менять».
Что, собственно, вы и хотите сделать, судя по результатам опроса на прошлой неделе 🙂.
Как бороться с этим комбо? (которое вынимает всю душу)
Понимать контекст и то, на…
12 супер востребованных профессий в сфере AI ➡️LinkedIn выкатил очередной мини-репорт
Но, кажется, правильнее называть их не новыми профессиями, а сочетаниями навыков. А в отчете интересны циферки: сколько можешь зарабатывать, если умеет встроить AI в свою профессиональную экспертизу. И еще он фиксирует, что женщины получают меньше.
Все 12 ролей можно разложить на три блока.
1️⃣ Строители — Builders
AI Engineer, …
3 смена. Отряд «Веретьево».
Неделю назад вернулась из лагеря для взрослых. Он же коливинг. Он же какая-то прекрасная дурь около речки, ради которой люди летят в Подмосковье и ждут этих двух недель весь год.
Не фестиваль. Не ретрит. Не закрытый клуб. Ты просто две недели живёшь, работаешь и тусишь в обществе приятных людей: часть знаешь, часть видишь впервые. И все это на магии самоорганизации. Программа состоит из …
Моя роль исчезает и ее очень меняет AI, а что дальше не знаю16%
Хочу поменять ВСЕ: зп, нишу, компанию, переехать, что делать?66%
Как стать востребованным и AI first в моей профессии?30%
The shares total 112%, 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.
Созванивались на этой неделе с Вероникой Климовой, очень люблю, как она въедливо смотрит на вакансии в мире и России и подмечает тренды в изменениях требований.
Говорили, как развиваться в профессии, если смысла в работе не видишь и кажется, что везде одна и та же бессмысленная хрень.
Мой ответ такой: не быть заложником профессии, её названия и не вешать на себя ярлык. Вместо этого двигаться на основе навыков и выб…
Эксперимент на американский рынок или дорога кринжа
Переделала позиционирование в LinkedIn. В качестве эксперимента по выходу на новый рынок — как Founder AI-компаньона по сопровождению в карьерном переходе.
До этого LinkedIn у меня был, но там стояло позиционирование для консалтинга: Founder advisor и фасилитатор. Гипотеза была такая: Телега и Insta — для экспертизы в перепридумывании, рассказа о моих сервисах, Ла…
IKEA переучила 8 500 человек и в итоге отрастила 3% новой выручки.
Нормальная такая точка роста, если у тебя уже давно работающий бизнес.
Я тут искала кейсы AI-автоматизации и рылась в том, как автоматизируют поддержку. Support сегодня первый кандидат на трансформацию и оптимизацию: с одной стороны, многое можно оцифровать и перевести на ботов, с другой — это фронтир компаний, где скапливается много данных, и интер…
🔥70❤45👌2
Showing the 12 most recent of 29 posts we hold for @coachpolishuk. 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.
Posts edited after publishing
@coachpolishuk edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
26 August 2026
Most recent edit
26 August 2026
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.
Моя роль исчезает и ее очень меняет AI, а что дальше не знаю16%
Хочу поменять ВСЕ: зп, нишу, компанию, переехать, что делать?66%
Как стать востребованным и AI first в моей профессии?30%
The shares total 112%, 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 29 most recent posts we hold, published 16 June 2026 to 31 August 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.
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 7 registered channels — 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Девушка с Деньгами @devushkasdengami · 28,215 Telegram ranks this channel #5 of 85 here — alongside 84 others — read 9 September 2026
Olymarkes Daily @markesdaily · 28,205 Telegram ranks this channel #5 of 85 here — alongside 84 others — read 9 September 2026
Канал Вари Веденеевой @varya_daily · 31,642 Telegram ranks this channel #6 of 86 here — alongside 85 others — read 5 September 2026
Нагуглила карьеру @dreamcatchme · 27,083 Telegram ranks this channel #31 of 92 here — alongside 91 others — read 12 September 2026
Matskevich - brains, love and robots @Matskevich · 25,302 Telegram ranks this channel #38 of 98 here — alongside 97 others — read 14 September 2026
Dasha’s notes | люди и смыслы @technohumanist · 37,699 Telegram ranks this channel #44 of 95 here — alongside 94 others — read 1 September 2026
This channel appears in 6 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Полищук. Карьерная проводница” (@coachpolishuk), 10,649 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/coachpolishuk.
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.