Просто и понятно о менеджменте, хорошем управленческом вкусе и здравом смысле. От управленца с двадцатилетним опытом.
Написать мне: @skolganov
Донатить: 410012702121366 (Ю.Money)
Реестр РКН: https://clck.ru/3Egbsg
Папка пользы: https://clck.ru/3Kgs6t
Created
10 January 2018 — measured — cross-checked against a third-party dataset (ext.tg_channel)
Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 98% 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 the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 19 comparable posts for this entry, running 20 July 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Of the group of 2 channels, the one whose matching posts we hold earliest is @psilonsk — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim 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.
60 measurements spanning 96 days, net -293. 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 15,687–16,068 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)
Subscribers
Change
10 Nov 2026, 00:36
15,731
-8
8 Nov 2026, 16:20
15,739
-12
7 Nov 2026, 06:38
15,751
-5
6 Nov 2026, 03:07
15,756
-2
5 Nov 2026, 00:17
15,758
-4
3 Nov 2026, 21:15
15,762
+2
2 Nov 2026, 18:17
15,760
-8
1 Nov 2026, 16:25
15,768
-8
31 Oct 2026, 12:48
15,776
-6
30 Oct 2026, 09:55
15,782
-2
29 Oct 2026, 06:20
15,784
-7
28 Oct 2026, 06:35
15,791
-2
27 Oct 2026, 09:28
15,793
+6
26 Oct 2026, 10:37
15,787
-2
25 Oct 2026, 09:31
15,789
-2
24 Oct 2026, 12:59
15,791
+2
23 Oct 2026, 14:40
15,789
-5
22 Oct 2026, 13:54
15,794
-9
21 Oct 2026, 05:47
15,803
-4
20 Oct 2026, 04:17
15,807
first reading
Engagement
81 posts held, back to 20 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 70 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
12.3%
avg views ÷ 15,731 subscribers
Avg views / post
1,930
31 posts measured
Reaction rate
2.25%
reactions ÷ views · ER floor
Posts in window
31
of 81 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. It is computed over the 29 of 31 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 10 November 2026
Posts held
81 (20 July 2026 – 10 November 2026)
Views total
59,890
Reactions total
1,258
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
10 Nov 2026, 17:47 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
Photos
≈8
Videos
≈1
Links
≈2,040
Lifetime counters from Telegram’s own channel header, read 10 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
17s
Average length
17s
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
3,858 reactions across 68 posts, in 32 distinct kinds. The most used accounts for 44.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
1,716
44.5%
🔥
536
13.9%
💯
501
13.0%
👎
324
8.40%
😁
229
5.94%
🤔
177
4.59%
❤🔥
80
2.07%
🤝
48
1.24%
🍓
44
1.14%
👏
33
0.855%
👌
24
0.622%
✍
23
0.596%
🙈
17
0.441%
🙏
16
0.415%
🤣
16
0.415%
🤯
13
0.337%
🥱
11
0.285%
🗿
9
0.233%
💊
7
0.181%
💔
7
0.181%
12 further kinds
27
0.7%
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 74 of the 81 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 4,181 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 81 most recent posts we hold, published 20 July 2026 to 10 November 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.
Advertising
Ad load
3.70%
3 of 81 posts carry an ad marker
Regulatory tokens
3
posts carrying an erid · 3 distinct tokens
Median views · ads
1,720
over 3 measured posts
Median views · rest
2,210
over 78 measured posts
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor. A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.
Advertising tokens recorded on this entry
erid
Posts
First seen
Last seen
2VtzquavUQE
1
3 November 2026
3 November 2026
2VtzqucgHpz
1
9 November 2026
9 November 2026
2W5zFGMQoBG
1
5 November 2026
5 November 2026
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 81 most recent posts we hold, published 20 July 2026 to 10 November 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 31 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Вышло новое бесплатное приложение Meeting Companion!
Начался созвон, приложение это замечает и само предлагает включить запись. Жмете «да» и спокойно разговариваете. Не надо пытаться успеть за всеми и потом гадать, что значит «Петрову зад. до пт». 😉
После встречи у вас два файла:
✔️ Полная расшифровка, где видно, кто что сказал.
✔️ Краткий протокол: главные тезисы, решения и задачи.
С приватностью тоже все аккурат…
🔍 Разница
Вот сидит менеджер Еремей, работает. Вдруг приходит коллега из соседнего отдела и говорит: «Задолбали твои сотрудники! Ходят и спрашивают одну и ту же фигню каждый день!»
Еремей думает: «Да, тупые у меня сотрудники! Так команду подставляют! Надо их наказать. И запретить ходить в соседний отдел с дурацкими вопросами. Щас разберусь!»
Еремей плохой менеджер.
Вот сидит менеджер Жанна, работает. Вдруг приход…
Не успеваете за ИИ-гонкой? Обучите команду ИИ-навыкам быстро и прозрачно на платформе Грейд от Яндекс Практикума
Половина сотрудников в России уже использует ИИ в работе. Но реальный эффект от автоматизации видят те компании, которые внедряют ИИ системно: обучают, отрабатывают реальные сценарии, делятся опытом экспертов.
Попробуйте готовое решение для быстрого обучения команд ИИ-навыкам — Грейд от Яндекс Практикума…
🕸 Невыносимая тишина
Разраб бился над тяжелой задачей, передал очередную сборку и ждет подтверждения, что все в порядке. А заказчик молчит. Ни замечаний, ни согласования. Неделю молчит, вторую, третью. Пишет мутные письма, обещает, что скоро возьмется за проверку. Менеджер проекта где-то там бегает, у него еще пяток таких проектов.
И что теперь? Разраб, конечно, себе занятие найдет, бэклоги пустыми не бывают. Но э…
🚪 Комментарии к задачке 1226-1998
Обычно кандидат идет к незнакомому начальнику и гадает, какой он. Самодур или адекватный? Деспот или партнер? Токсик или няшка? ) У вас не так: вы потенциальную начальницу Соню знаете, причем с той стороны, с какой подчиненные начальство обычно не видят. Вроде бы это преимущество. Но знанию пятнадцать лет, и неясно, поможет ли оно принять верное решение. Давайте разберемся.
Сначал…
👠 Тренажер для менеджеров и не только 1226-1998
Вы — опытный менеджер, ищете новую работу. И, похоже, нашли: крупный банк, высокая управленческая должность, хорошие деньги. Сейчас интервью с будущим руководителем.
Офис шикарный. Вас проводят в переговорку: дерево, кожа, вид на столицу. Открывается дверь, и входит... Соня!
Лет пятнадцать назад вы пришли управлять крошечным отделом, где она работала. Соня сама метил…
Представьте, что ваши разрабы, как и во многих других компаниях, начали писать код с помощью ИИ. Кто и что от этого выиграл?
Разрабы-то довольны: скучное теперь делает ИИ, а им остается интересное.
Но что получил бизнес, компания в целом? Непонятно. Продукт релизят не чаще: код пишут быстрее, но его все так же надо проверить и выкатить. Клиенты вряд ли видят разницу. Затраты на разработку не только не снизились, но…
👀 Наблюдаемая надежность
Мой менти руководит большой проектной командой, занятой важными и дорогими продуктами. Команда распределена по стране, и он пожаловался, что сложно сплачивать удаленщиков.
Некоторые думают, что лучший способ людям сплотиться — съесть вместе пуд соли. Дескать, команду объединяют страдания и кризисы. В этом есть правда, но если команда сплачивается только в кризисных ситуациях, то либо они в…
📈 Бесплатный гайд Яндекс Практикума по AI Adoption в компании
Компании покупают подписки на ИИ-сервисы, проводят обучение, запускают пилоты. А через пару месяцев выясняется, что инструментами пользуются единицы.
Гайд Яндекс Практикума поможет пройти путь от покупки лицензий до системного внедрения ИИ.
С ним вы:
✅Определите, на каком этапе AI Adoption вы находитесь сейчас
✅Разберётесь, как снять страхи и сопротивле…
🏋🏾♂️ Сто двадцать процентов
Мой менти, владелец средней компании, пожаловался, что сотрудники не хотят учиться. Он им по доброте душевной оплатил классные курсы, а они филонят. Я спросил, что он снял с людей на время учебы. Он удивился вопросу. Мне эта картина хорошо знакома, причем изнутри.
На заре карьеры я обожал учиться, чего уж скрывать, гораздо больше, чем сейчас. И однажды пошел на курс за свой счет. Хотел…
📤 Три письма
Если договариваешься о чем-то с человеком по почте, есть простое правило: не договорились за три письма, дальше переписываться бессмысленно.
Причем три письма — это не три твоих, а три во всей переписке. Ты написал, тебе ответили, ты ответил еще раз. Если после этого вопрос не решен, четвертое письмо сделает только хуже.
Дальше каждый спорит с текстом, а не с человеком. Письма становятся длиннее, поз…
👍36✍14💯5🔥5👎1
Showing the 12 most recent of 81 posts we hold for @psilonsk. 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 recorded as deleted after publishing
We recorded 1 post on @psilonsk as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
16 August 2026
Most recent seen missing
16 August 2026
Median time before seen missing
10 days
Seen missing in the last 30 days
0
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.
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.
Менеджер от боженьки @pm_god · 25,037 Telegram ranks this channel #3 of 98 here — alongside 97 others — read 14 September 2026
pmclub — учим управлять @pmclub · 20,691 Telegram ranks this channel #9 of 97 here — alongside 96 others — read 26 September 2026
🔥 Дмитрий Ирешев: AI • Продукты • Проекты @dmitrii_ireshev_Agile_PMP · 35,144 Telegram ranks this channel #9 of 97 here — alongside 96 others — read 12 September 2026
Про Управление @ProYpravlenca · 34,308 Telegram ranks this channel #10 of 99 here — alongside 98 others — read 6 September 2026
Про Проекты и карьеру в ИТ | Романова @proProject1 · 40,483 Telegram ranks this channel #11 of 97 here — alongside 96 others — read 1 September 2026
Нормально делай, нормально будет / Саша Клименко @normalno_delaj · 21,965 Telegram ranks this channel #12 of 96 here — alongside 95 others — read 22 September 2026
Black product owner | Тигран Басеян о продакт менеджменте и стартапах @blackproduct · 21,248 Telegram ranks this channel #16 of 93 here — alongside 92 others — read 24 September 2026
Индекс дятла @dindex · 22,222 Telegram ranks this channel #17 of 98 here — alongside 97 others — read 21 September 2026
Регулярный менеджмент для руководителей (Евгений Севастьянов) @regularmanagement · 22,735 Telegram ranks this channel #17 of 96 here — alongside 95 others — read 19 September 2026
Product Management & AI @ruspm · 25,014 Telegram ranks this channel #17 of 97 here — alongside 96 others — read 14 September 2026
Fresh Product Manager @FreshProductGo · 19,877 Telegram ranks this channel #18 of 95 here — alongside 94 others — read 29 September 2026
Продукторий Владимира Меркушева @vladimir_merkushev · 21,822 Telegram ranks this channel #22 of 96 here — alongside 95 others — read 21 September 2026
Я — РУКОВОДИТЕЛЬ @iRukovoditel · 30,925 Telegram ranks this channel #22 of 98 here — alongside 97 others — read 6 September 2026
Teamlead Good Reads – ежедневные советы про менеджмент людей и команд @leadgr · 31,685 Telegram ranks this channel #26 of 96 here — alongside 95 others — read 10 September 2026
Дашич, беги🚀 @dashich_begi · 41,038 Telegram ranks this channel #32 of 96 here — alongside 95 others — read 1 September 2026
No Flame No Game @proproduct · 38,615 Telegram ranks this channel #36 of 96 here — alongside 95 others — read 31 August 2026
Стартап дня. Александр Горный. @startupoftheday · 62,560 Telegram ranks this channel #36 of 97 here — alongside 96 others — read 22 August 2026
Продакты не нужны @betternotworse · 28,396 Telegram ranks this channel #41 of 96 here — alongside 95 others — read 9 September 2026
Hard Client @hardclient · 22,912 Telegram ranks this channel #42 of 97 here — alongside 96 others — read 19 September 2026
Максим Дорофеев: Прокрастинация и джедайские техники @mnogosdelal · 25,891 Telegram ranks this channel #42 of 97 here — alongside 96 others — read 14 September 2026
Образование, которое мы заслужили @ru_education · 42,248 Telegram ranks this channel #45 of 98 here — alongside 97 others — read 29 August 2026
The Edinorog 🦄 @Theedinorogblog · 44,082 Telegram ranks this channel #46 of 97 here — alongside 96 others — read 29 August 2026
GoPractice! @gopractice · 29,393 Telegram ranks this channel #47 of 97 here — alongside 96 others — read 9 September 2026
FEDOR BORSHEV @pmdaily · 23,648 Telegram ranks this channel #49 of 97 here — alongside 96 others — read 17 September 2026
This channel appears in 34 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“Сергей Колганов - psilonsk - об управлении проектами” (@psilonsk), 15,731 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/psilonsk.
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.