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 10 September 2026 and assigned it the closest of 31 fixed categories, at 50% 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
34 measurements spanning 43 days, net -45. 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 20,643–20,745 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 34
Measured (UTC)
Subscribers
Change
17 Sept 2026, 12:21
20,688
-2
15 Sept 2026, 10:58
20,690
-7
13 Sept 2026, 18:36
20,697
-10
11 Sept 2026, 22:21
20,707
+18
9 Sept 2026, 11:38
20,689
+7
6 Sept 2026, 02:40
20,682
+27
3 Sept 2026, 23:58
20,655
-5
2 Sept 2026, 12:45
20,660
-6
1 Sept 2026, 09:44
20,666
+3
31 Aug 2026, 10:35
20,663
+7
30 Aug 2026, 13:02
20,656
-6
29 Aug 2026, 12:15
20,662
-5
28 Aug 2026, 15:32
20,667
+2
27 Aug 2026, 15:33
20,665
+2
26 Aug 2026, 14:44
20,663
+5
25 Aug 2026, 13:37
20,658
-11
24 Aug 2026, 16:07
20,669
-4
22 Aug 2026, 21:37
20,673
-5
21 Aug 2026, 11:18
20,678
-14
20 Aug 2026, 10:24
20,692
first reading
Engagement
40 posts held, back to 26 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 58 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
5.75%
avg views ÷ 20,688 subscribers
Avg views / post
1,190
6 posts measured
Reaction rate
3.04%
reactions ÷ views · ER floor
Posts in window
6
of 40 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 2 September 2026
Posts held
40 (26 July 2026 – 2 September 2026)
Views total
7,142
Reactions total
217
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 18:24 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
10m 32s
Average length
10m 32s
Measured directly from 1 video 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
1,144 reactions across 40 posts, in 27 distinct kinds. The most used accounts for 34.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
391
34.2%
🔥
359
31.4%
👍
121
10.6%
❤🔥
120
10.5%
💯
42
3.67%
👏
26
2.27%
🙈
19
1.66%
⚡
10
0.874%
🤔
8
0.699%
🍾
7
0.612%
✍
5
0.437%
🙏
4
0.35%
🤮
4
0.35%
🦄
4
0.35%
👎
3
0.262%
😁
3
0.262%
🤣
3
0.262%
💋
2
0.175%
💩
2
0.175%
🤡
2
0.175%
7 further kinds
9
0.787%
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 40 of the 40 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 1,144 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 40 most recent posts we hold, published 26 July 2026 to 2 September 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
3
across the posts below
Posts paid on
3
of 40 we hold a reading for · 8%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @thefutureofwork. 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 40 most recent posts we hold for this entry, published 26 July 2026 to 2 September 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.
Друзья, напоминаю, что на сайте the-future-of-work.ru можно посмотреть актуальные репорты и исследования. Вчера обновили данные за август. Это + 25 документов.
На какие я бы обратил внимание в первую очередь:
1. Рынок искусственного интеллекта России (AIANA)
2. HR-тренды 2026 (Kept)
3. Трансформация профессиональных компетенций под влиянием ИИ: взгляд разработчиков (ВШЭ)
4. The state of AI in 2026: On the road t…
Как оценить способность
работать в неопределенности?
Если для менеджера умением справляться с неопределенностью является одним из ключевых навыков, то как его можно было бы заранее оценить?
Stanford d.school придумали опросник из 20 вопросов. 10 из них оценивают Ambiguity Attitude, и ещё 10 — Ambiguity Actions.
Я эти вопросы перевёл и выложил пдф в комментариях. Кажется этим и правда можно пользоваться. По крайней…
8 главных навыков менеджера
Всем понравился пост про сороколетнию карьеру. Но у Уилла Ларсона есть ещё неплохой текст, где он рассказывает про универсальные менеджерские навыки.
Буквально рассказывает — у него на YouTube есть про это видео со слайдами. Саму презентацию я выложил в комментариях.
Итак, что это за навыки:
1. Execution
Способность доводить работу до результата.
2. Team
Собирать сильную команду и фор…
А вот Билл Гейтс молодец! Всё расписал очень достойно и содержательно.
Выделил нам ключевые идеи:
1. AI может как сильно улучшить нашу жизнь, так и увеличить неравенство. Но хороший сценарий сам по себе не воплотится. Надо всем профессиональным сообществом сфокусироваться и спроектировать этот переход.
2. Рабочих мест станет значительно меньше, чем сегодня. А исторические аналогии с предыдущими технологическими р…
Марк Цукерберг не понимает как жить
Если помните, три недели назад делал нам дайджест манифестирующих высказываний про AI, и там первой в списке была попытка Марка Цукерберга отыграть роль большого визионера — и его The AI Future Is for Everyone.
Попытка, на мой взгляд, слабая и невнятная. В очередной раз мы убедились, что Цукерберг весьма посредственный визионер и коммуникатор.
Текст очень многословный. Заряженны…
AI автоматизирует вашу работу — но не мою
Behavioural Insights Team опросила 3500 работающих британцев на тему того, как они оценивают риски автоматизации своей профессии, и профессии других людей.
43% опрошенных считают, что в ближайшие 10 лет AI сможет выполнять большинство задач в работе других людей. Однако, когда речь заходит об их собственной работе, этот показатель падает до 35%.
Что особенно интересно: мол…
Сорокалетняя карьера
Вроде бы есть такая установка, что чем выше неопределенность, тем короче должен быть горизонт планирования.
И что вот сейчас как раз те самые времена, когда нельзя планировать больше чем на, условно, 3 года.
Вообще не понимаю эту идею. Неопределённость сокращает горизонт прогноза. Но почему она должна сокращать горизонт стратегии?
А сейчас, наоборот, как будто особенно важно видеть перспектив…
Будущее рекрутмента
Есть такой известный американский рекрутмент-эксперт-инфлюенсер Matt Charney. И он выложил свою презентацию, с которой сейчас ходит и рассказывает по конференциям про будущее рекрутмента.
Целиком презентация в комментариях (45 слайдов). Вдруг вам пригодится.
В преддверии People Tech Camp обсудили с Катей Грачёвой мои смелые идеи про будущее работы.
Некоторые из этих идей наверняка где-то даже проявляются и в программе кэмпа.
Который, я напоминаю, состоится 17-19 сентября. И с подробностями вы можете ознакомиться на сайте peopletech.ru
Интервью целиком читайте тут: https://peopletech.ru/evgeni-volnov
А ещё Катя написала такой замечательный пост.
8 организационных метафор Гарета Моргана
«Организация как психическая тюрьма» — это одна из восьми метафор организации, которую придумал Гарет Морган 40 лет назад.
Интересно, что один из самых знаковых исследователей организаций вообще-то был бухгалтером.
Но вдруг у него начал проявляться интерес (и талант) к известной проблеме: организации и процессы действуют по формальным и рафинированным правилам, а люди с их …
Организация как психическая тюрьма
Пересматривал тут свои архивы сохраненных ссылок и статей. И наткнулся на хит почти двадцатилетней давности. Венкатеш Рао в своём когда-то очень популярном блоге Ribbonfarm расписал концепцию «The Gervais Principle».
На базе сериала «Офис» он предложил странную (пато)психологическую теорию организации. В которой есть три типа участников:
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Социопаты принес…
Да, теперь и книжный клуб. Тема осеннего сезона: видение лидера — и как это видение формирует культуру компании.
Тема, которая и меня очень интересует. И как будто весьма актуальная для текущего положения вещей в мире.
Вчера в коммьюнити Димы Фалалеева рассказывал о том, почему для эффективного лидерства так важны хорошие книги и хорошая теория. И я правда считаю, что книги — самый лучший (и самый недооцененный) сп…
🔥22❤🔥10❤7👏3
Signed Evgeniy Volnov
Showing the 12 most recent of 40 posts we hold for @thefutureofwork. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@thefutureofwork 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
21 August 2026
Most recent edit
23 August 2026
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 15 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 26 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
Dasha’s notes | люди и смыслы @technohumanist · 37,666 Telegram ranks this channel #6 of 95 here — alongside 94 others — read 1 September 2026
Dumik @dumik · 22,244 Telegram ranks this channel #7 of 98 here — alongside 97 others — read 21 September 2026
FounderWoman @FounderWoman · 44,913 Telegram ranks this channel #7 of 95 here — alongside 94 others — read 27 August 2026
Daily Reminder @justakindreminder · 36,572 Telegram ranks this channel #18 of 98 here — alongside 97 others — read 1 September 2026
Matskevich - brains, love and robots @Matskevich · 25,245 Telegram ranks this channel #44 of 98 here — alongside 97 others — read 14 September 2026
AgileFluent: карьера без границ @agilefluent · 46,131 Telegram ranks this channel #46 of 95 here — alongside 94 others — read 28 August 2026
HR-аналитика @hranalitycs · 34,128 Telegram ranks this channel #51 of 100 here — alongside 99 others — read 3 September 2026
Авито Работа @avito_jobs · 21,452 Telegram ranks this channel #58 of 97 here — alongside 96 others — read 23 September 2026
Образование, которое мы заслужили @ru_education · 42,533 Telegram ranks this channel #62 of 98 here — alongside 97 others — read 29 August 2026
Пригодится! 🍎 Библиотека для HR @savetoreadlater · 22,278 Telegram ranks this channel #64 of 100 here — alongside 99 others — read 21 September 2026
Живое обучение @prolearning · 20,688 Telegram ranks this channel #67 of 100 here — alongside 99 others — read 26 September 2026
Карьера в топ от Анны Знаменской @annaznamenskaya · 30,771 Telegram ranks this channel #69 of 98 here — alongside 97 others — read 6 September 2026
hh.ru @hh_ru_official · 90,584 Telegram ranks this channel #71 of 83 here — alongside 82 others — read 10 September 2026
ХУЦПА <-> Женя Давыдов @hutzp · 45,113 Telegram ranks this channel #72 of 98 here — alongside 97 others — read 27 August 2026
topcareer @topcareerschool · 23,425 Telegram ranks this channel #80 of 100 here — alongside 99 others — read 18 September 2026
Соколова наизнанку @naiznankuo · 58,573 Telegram ranks this channel #82 of 95 here — alongside 94 others — read 23 August 2026
СберУниверситет @sber_university · 24,091 Telegram ranks this channel #85 of 100 here — alongside 99 others — read 17 September 2026
Витрина стартапов @showstartup · 27,089 Telegram ranks this channel #86 of 90 here — alongside 89 others — read 11 September 2026
Skolkovo School of Management @skolkovo_channel · 43,308 Telegram ranks this channel #91 of 100 here — alongside 99 others — read 28 August 2026
This channel appears in 19 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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“The Future Of Work” (@thefutureofwork), 20,688 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/thefutureofwork.
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.