Самые интересные статьи, видео и новости, связанные с управлением людьми, командами, разработкой и продуктами.
РКН: https://gosuslugi.ru/snet/67b4386d2a44e21839a0f87f
Продуктовая папка: https://t.me/addlist/YvmnHCHUp700Nzky
Реклама: @tanyasanovna
Created
9 December 2017 — measured — cross-checked against a third-party dataset (ext.tg_channel)
8 measurements spanning 6 days, net -57. 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 28,357–28,432 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 17:13
28,366
-10
11 Aug 2026, 15:52
28,376
-13
10 Aug 2026, 18:16
28,389
-6
9 Aug 2026, 19:51
28,395
-2
8 Aug 2026, 16:53
28,397
-8
7 Aug 2026, 19:24
28,405
-12
6 Aug 2026, 18:13
28,417
-6
6 Aug 2026, 06:02
28,423
first reading
Engagement
27 posts held, back to 16 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 17 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
19.7%
avg views ÷ 28,366 subscribers
Avg views / post
5,580
27 posts measured
Reaction rate
0.626%
reactions ÷ views · ER floor
Posts in window
27
of 27 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 12 August 2026
Posts held
27 (16 July 2026 – 12 August 2026)
Views total
150,720
Reactions total
943
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 21:51 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
≈369
Videos
≈4
Links
≈1,850
Lifetime counters from Telegram’s own channel header, read 12 August 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.
Reaction mix
874 reactions across 24 posts, in 4 distinct kinds. The most used accounts for 40.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
357
40.8%
👎
198
22.7%
❤
161
18.4%
🔥
158
18.1%
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 27 of the 27 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 943reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 27 most recent posts we hold, published 16 July 2026 to 12 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.
Telegram Stars
Stars received
5
across the posts below
Posts paid on
2
of 27 we hold a reading for · 7%
Most on one post
4
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @leadgr. 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 27 most recent posts we hold for this entry, published 16 July 2026 to 12 August 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.
Advertising
Ad load
11.1%
3 of 27 posts carry an ad marker
Regulatory tokens
3
posts carrying an erid · 3 distinct tokens
Median views · ads
5,220
over 3 measured posts
Median views · rest
5,660
over 24 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
2SDnjcsadbZ
1
5 August 2026
5 August 2026
2Vtzqug4oJi
1
23 July 2026
23 July 2026
2Vtzquo2GYz
1
4 August 2026
4 August 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 27 most recent posts we hold, published 16 July 2026 to 12 August 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.
LLM вознаграждают экспертизу
Все мы используем одни и те же модели, и по умолчанию получаем одни и те же усредненные ответы. Чтобы добиться от модели действительно качественного результата, нужно знать, в какую сторону ее запушить, какие ответы принимать, за какие идеи зацепиться. А именно это и требует глубокой экспертизы в вопросе.
Например, не зная хорошо своей кодовой базы, вы не сможете оценить, насколько пред…
Как руководить, когда цели размыты, а результат нужен прямо сейчас?
«Срочно перестраиваем план»
«Конкуренты уже внедрили ИИ, нам тоже надо»
«Это приоритет, ищите варианты»
Бизнес часто спускает цели без достаточной конкретики, а руководителю нужно превратить их в понятный план для команды — без такого плана легко потратить ресурсы впустую.
А это задача не из легких: нужно одновременно разобраться, чего именно хоче…
Эффект Даннинга-Крюгера под вопросом
На всякий случай напомню, что суть эффекта Даннинга-Крюгера состоит в том, что некомпетентные в какой-то области люди склонны переоценивать свои способности в ней.
В качестве доказательства этого эффекта чаще всего приводят график из оригинального исследования (первая картинка), в котором студентов просили дать прогноз своей оценки за тест, а затем сравнивали с реальной оценкой.…
Как стафф инженеру найти достойные проблемы
Большинство компаний сходятся на том, что главная черта, отличающая стаффа от сеньора – это умение самостоятельно находить самые ценные точки приложения своих усилий. Вот простой алгоритм, как можно это делать:
👉Накапливайте знания о проблемах в вашей области компетенции, на которые жалуются люди.
👉Не бросайтесь на первую проблему, которая показалась важной. Дайте им нако…
Лето, ИТ-Пикник и музыка известных артистов уже через несколько дней!
8 августа в Коломенском пройдет ИТ-Пикник.
В программе — выступления проекта LAB Антона Беляева, IOWA, Cream Soda, Pompeya, мартина и Совы.
А днем — научпоп-лекции, дискуссии об ИИ и больших языковых моделях, мастер-классы и интерактивы. Полезные знакомства и развлечения тоже будут.
Зарегистрироваться и узнать подробности можно на сайте меропри…
Про скорость ради скорости
Задумайтесь – а насколько часто, когда вы пытались ускориться сами, или просили об этом команду, это действительно было важно? В нашей индустрии уже довольно давно стало моветоном не пытаться всеми силами оптимизировать time to market. А итоги у этого не всегда положительные:
👉Предложения замедлиться и подумать по умолчанию воспринимаются как контрпродуктивные.
👉Многие ненужные фичи делаю…
AI в разработке уже прошел стадию «нужен или нет» и стал вопросом процессов: как считать эффект, как перестроить ревью, кто отвечает за код агента и что делать с выгоранием, которое приходит вместе с AI-слопом.
Об этом будет говорить TeamLead Сибирь — конференция для тимлидов и руководителей. AI-трансформация заняла самый большой трек, 15 докладов о реальных внедрениях:
🔸 как считать экономику внедрения ИИ и вести …
Не понимать кодовую базу – нормально
Один из стандартных набросов на LLM – это то, что разработчики, слишком сильно полагающиеся на агентов, довольно быстро теряют понимание кодовой базы проекта. Но если задуматься – а насколько это понимание было и раньше, когда код писали руками? А если подумать не про сравнительно компактные кодовые базы, а огромные энтерпрайзные проекты?
Планируя изменение программы, мы всегда …
😔 79% уволившихся называют причиной ухода недостаток признания.
Руководители переоценивают частоту похвалы: им кажется, что они говорят «спасибо» каждую неделю, на самом деле сотрудники получают признание в лучшем случае несколько раз в год. Результат — выгорание, демотивация и уход лучших.
Команда Яндекс Практикума собрала гайд из 30 способов похвалы, которые реально работают с любым бюджетом. Внутри:
✅ Идеи от п…
Огромная библиотека постмортемов
Кто-то собрал на одном сайте гигантскую подборку из 650 постмортемов от разных компаний. Использовать можно и для того, чтобы посмотреть, как деградируют ваши любимые сервисы, и для того, чтобы вдохновиться форматом и процессами.
Почему CTO сейчас стало особенно тяжело
Всю прошлую неделю в Твиттере обсуждали интересный тренд – многие CTO / VP of Engineering / Head of Development в стартапах и компаниях среднего размера сейчас жестко выгорают и увольняются, проработав буквально пару месяцев. Причины называют вот такие:
👉Роль, на которую их взяли, довольно расстрельная, с нереалистичными ожиданиями из-за AI
👉У компании нет никакой стратегии и…
👍29🔥11❤7👎1
Signed Egor Tolstoy
Showing the 12 most recent of 27 posts we hold for @leadgr. 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.
Citation-graph rank
Citation-graph rank — 299,293 of 1,151,006entries 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 2 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.
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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“Teamlead Good Reads – ежедневные советы про менеджмент людей и команд” (@leadgr), 28,366 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/leadgr.
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.
