Technology — 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 15 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
12 measurements spanning 48 days, net -5. 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 2,878–2,888 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
24 Sept 2026, 22:00
2,879
-1
16 Sept 2026, 17:01
2,880
-5
12 Sept 2026, 23:40
2,885
-2
8 Sept 2026, 19:40
2,887
+2
3 Sept 2026, 17:16
2,885
+1
31 Aug 2026, 15:44
2,884
+2
21 Aug 2026, 08:33
2,882
-2
17 Aug 2026, 22:33
2,884
-1
14 Aug 2026, 18:13
2,885
+1
11 Aug 2026, 07:08
2,884
+2
7 Aug 2026, 20:26
2,882
-2
7 Aug 2026, 10:16
2,884
first reading
Engagement
20 posts held, back to 2 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 2 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 10 June 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
5m 15s
Average length
29s
Measured directly from 11 videos 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
222 reactions across 20 posts, in 9 distinct kinds. The most used accounts for 46.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😁
104
46.8%
❤
48
21.6%
🔥
39
17.6%
👍
23
10.4%
💯
4
1.80%
❤🔥
1
0.45%
🌚
1
0.45%
😭
1
0.45%
🤯
1
0.45%
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 20 of the 20 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 222 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 2 June 2026 to 10 June 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.
🧑💻 Как меняется современная разработка
В Anthropic произошла не просто автоматизация, а смена парадигмы: больше 80% кода в их основном репозитории сегодня пишет ИИ, а один инженер выпускает в 8 раз больше кода, чем год назад. Ключевой пример - Claude внёс более 800 исправлений API-ошибок за месяц, на что человеку потребовалось бы около четырёх лет.
При этом качество кода нейросети уже сравнялось с человеческим, а …
🚫 Что делать, когда сотрудник тормозит команду
Если ваш сотрудник в команде занимается бесполезными задачами и блокирует работу - обычная просьба "перестань" не сработает. Она запускает стрессовую реакцию и оборону. Вместо этого нужно понять, что человек пытается защитить своими сомнениями и начать разговор с признания его опасений. Только после этого можно предлагать новый путь.
Прежде чем говорить с сотрудником, …
❌ Почему роль Delivery Manager не работает
Delivery Manager - это не координатор задач и не "пожарный", а архитектор устойчивой системы поставки. Его цель - сделать так, чтобы проекты проходили через конвейер разработки предсказуемо, без героизма и с минимальными рисками.
Проблема большинства компаний не в конкретных людях, а в том, что роль DM встроена в систему неправильно: зона ответственности размыта, нет метри…
📊 Базовый минимум метрик, который реально работает
Мы привыкли думать, что разработка - это магия, но на деле это сложный конвейер с Jira, CI/CD и вечным вопросом от бизнеса: "Когда в прод?". Команды, которые выживают в финтехе и других сферах, отличаются умением измерять путь идеи до продакшена, а не только чистотой кода. Метрики нужны не для отчётов, а чтобы честно ответить, где и почему застревают задачи и как ус…
⌛️ Как выделить 4 часа и не отвлекаться
Утром вы садитесь за сложную задачу, а через час обнаруживаете 12 вкладок, три непрочитанных сообщения и пустоту вместо результата. Знакомо? Это классическая ловушка поверхностной работы, когда занятость подменяет продуктивность.
Кэл Ньюпорт ввел понятие Deep Work - состояние полной концентрации, в котором мозг выдает результаты, недостижимые в режиме "галочки". И главный инс…
Showing the 12 most recent of 20 posts we hold for @pmbbk. 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.
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.
Про Проекты и карьеру в ИТ | Романова @proProject1 · 37,537 Telegram ranks this channel #81 of 97 here — alongside 96 others — read 1 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 24 September 2026 — this
entry's latest reading, not the date you are reading this.
“Project Management Black Book” (@pmbbk), 2,879 subscribers as measured 24 September 2026. Telegram Register, tgregister.com/channel/pmbbk.
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.
