8 measurements spanning 20 days, net -53. 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 7,254–7,323 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
26 Aug 2026, 19:04
7,262
-9
23 Aug 2026, 17:07
7,271
-8
20 Aug 2026, 02:04
7,279
-6
17 Aug 2026, 10:48
7,285
-5
13 Aug 2026, 13:26
7,290
-17
10 Aug 2026, 11:30
7,307
-6
7 Aug 2026, 16:34
7,313
-2
7 Aug 2026, 01:01
7,315
first reading
Engagement
31 posts held, back to 8 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 15 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
21.5%
avg views ÷ 7,262 subscribers
Avg views / post
1,560
16 posts measured
Reaction rate
1.56%
reactions ÷ views · ER floor
Posts in window
16
of 31 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 19 August 2026
Posts held
31 (8 July 2026 – 19 August 2026)
Views total
25,034
Reactions total
390
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
20 Aug 2026, 11:48 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
716 reactions across 28 posts, in 27 distinct kinds. The most used accounts for 31.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😁
227
31.7%
🔥
136
19.0%
❤
129
18.0%
💯
50
6.98%
🤣
36
5.03%
🤡
23
3.21%
⚡
20
2.79%
💩
17
2.37%
🫡
12
1.68%
❤🔥
10
1.40%
😐
10
1.40%
🤔
7
0.978%
💊
6
0.838%
🥰
5
0.698%
🖕
4
0.559%
🦄
4
0.559%
custom 5208695071095937061
3
0.419%
👌
3
0.419%
😢
3
0.419%
✍
2
0.279%
7 further kinds
9
1.26%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it isTelegram’s.
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 31 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 716reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 31 most recent posts we hold, published 8 July 2026 to 19 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.
Ладно, парни. Побайтил вас пару дней с этим вашим клодом.
Конечно, я не спорю, что все модели хорошие. Все инструменты крутые, нужно просто грамотно их применять и научиться пользоваться ими.
Мир. Дружба. Жвачка
Все, кроме клода
Вчера один уважаемый коллега сказал мне, что клод плохо работает с не родными моделями. Типо если подключить в него, например, Kimi, то он будет работать хуже, чем если юзать модели Антропика.
Ну чтож. Проверим!
Вчера перед сном попросил адаптировать Добрыню с курсора под клод и запустил на ночь выполнение задач. Отгадайте сколько тикетов этот монстр вайбкодинга сделал к утру?
Курсор лучше Клода
Год это повторяю, а в опросах всё равно побеждает Клод Код. И я так и не понял почему.
Так уж вышло, что активно вайбкодить я начал с DeepMatch. Взял тогда самый нормальный инструмент, который был - Cursor. И до сих пор на нём. DeepMatch на 99.9% написан курсором. Добрыня - мультиагентная система, которая забирает задачи из трекера, гоняет груминг, разработку, тесты, баги, MR, это все тоже живёт …
Теперь на вопрос "Кто занимается разработкой DeepMatch?" я буду гордо отвечать Добрыня
Немного про Добрыню. Добрыня - это мультиагентная система, которая забирает задачи из таск трекера по тегу и прогоняет ее через несколько фаз:
- грумминг
- разработка
- тестирование
- поиск багов в реализации
- правка багов
- создание MR
На каждом шагу Добрыня пишет комментарии в таск трекер. На этапе тестирования прикладыв…
Число удалёнщиков в России сократилось до 968 тыс. человек, упав за прошлый год на 21,8%. Сейчас работать из дома в основном разрешают в качестве привилегии специалистам высшей квалификации. Всех остальных работодатели активно возвращают в офисы или переводят на гибридный режим. По прогнозам экспертов, к концу 2026 года количество работников на удалёнке в стране уменьшится до 600-800 тыс. @banksta
Не буду писать, чт…
Где заканчивается no-code
Ассистента сейчас собирают в конструкторе: блоки соединяются мышкой, кода нет вообще. Так работает, пока задачи простые.
Когда нужно настроить качество поиска, переключить модель или задать логику поведения - блоков уже не хватает. Тут начинается код.
Об этом пройдет бесплатный вебинар karpovꓸcourses «Прототипирование LLM (большие языковые модели): как создаются ИИ-ассистенты для реальных…
🔥8❤5🫡4🤡3💩2🖕2🙈2✍1
Signed Vasiliy
Showing the 12 most recent of 31 posts we hold for @dev_yttg. 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
@dev_yttg 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
12 August 2026
Most recent edit
12 August 2026
Citation-graph rank
Citation-graph rank — 437,601 of 1,621,120entries 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.
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.
Осознанная Меркантильность | Антон Назаров @m0rtymerr_channel · 79,747 Telegram ranks this channel #10 of 87 here — alongside 86 others — read 18 August 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 26 August 2026 — this
entry's latest reading, not the date you are reading this.
“Деплой | Ваня Ботанов” (@dev_yttg), 7,262 subscribers as measured 26 August 2026. Telegram Register, tgregister.com/channel/dev_yttg.
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.