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Channel

Константин Доронин

@kdoronin_blog

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry

8,365subscribers

+2,001 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001245391218
TypeChannel
Username@kdoronin_blog
DescriptionПо любым вопросам, которые не хотите задавать в комментариях, можете писать напрямую – @kdoronin
CreatedBetween 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live7 November 2026
Measurements held26
Confirmed unchanged1 time, most recently 7 November 2026
On Telegramt.me/kdoronin_blog

Topic

Hacking & security — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 86% 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.

Growth

6,3648,3657,364.56 August 2026 — 6,364 subscribers6 August 2026 — 6,364 subscribers7 August 2026 — 6,371 subscribers9 August 2026 — 6,364 subscribers13 August 2026 — 6,377 subscribers16 August 2026 — 6,387 subscribers19 August 2026 — 6,430 subscribers22 August 2026 — 6,489 subscribers25 August 2026 — 6,514 subscribers28 August 2026 — 6,521 subscribers31 August 2026 — 6,524 subscribers3 September 2026 — 6,571 subscribers8 September 2026 — 6,595 subscribers12 September 2026 — 6,633 subscribers16 September 2026 — 6,638 subscribers24 September 2026 — 6,678 subscribers4 October 2026 — 6,692 subscribers10 October 2026 — 6,721 subscribers14 October 2026 — 6,733 subscribers16 October 2026 — 6,754 subscribers23 October 2026 — 6,766 subscribers25 October 2026 — 6,774 subscribers29 October 2026 — 7,185 subscribers1 November 2026 — 7,566 subscribers4 November 2026 — 8,028 subscribers7 November 2026 — 8,365 subscribers6 August 20267 November 2026
26 measurements spanning 93 days, net +2,001. 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 6,064–8,665 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)SubscribersChange
7 Nov 2026, 07:378,365+337
4 Nov 2026, 03:118,028+462
1 Nov 2026, 12:387,566+381
29 Oct 2026, 02:397,185+411
25 Oct 2026, 18:486,774+8
23 Oct 2026, 01:316,766+12
16 Oct 2026, 21:556,754+21
14 Oct 2026, 05:476,733+12
10 Oct 2026, 14:006,721+29
4 Oct 2026, 17:216,692+14
24 Sept 2026, 23:416,678+40
16 Sept 2026, 18:206,638+5
12 Sept 2026, 11:566,633+38
8 Sept 2026, 09:586,595+24
3 Sept 2026, 09:416,571+47
31 Aug 2026, 09:146,524+3
28 Aug 2026, 08:346,521+7
25 Aug 2026, 08:066,514+25
22 Aug 2026, 09:566,489+59
19 Aug 2026, 10:576,430first reading

Engagement

44 posts held, back to 29 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 18 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
35.5%
avg views ÷ 8,365 subscribers
Avg views / post
2,970
6 posts measured
Reaction rate
1.33%
reactions ÷ views · ER floor
Posts in window
6
of 44 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
WindowRolling 30 days · latest post in window 1 November 2026
Posts held44 (29 June 2026 – 1 November 2026)
Views total17,830
Reactions total237
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Nov 2026, 12:25 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
880
Videos
379
Links
570

Lifetime counters from Telegram’s own channel header, read 7 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
7h 48m
Average length
1h 06m

Measured directly from 7 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

1,245 reactions across 40 posts, in 18 distinct kinds. The most used accounts for 37.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥46737.5%
❤34427.6%
👍25020.1%
😁14611.7%
👏80.643%
💯60.482%
🤯60.482%
💘30.241%
👌20.161%
👎20.161%
💩20.161%
🤝20.161%
🤡20.161%
❤‍🔥10.08%
🎉10.08%
🏆10.08%
🤣10.08%
🤮10.08%

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 42 of the 44 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 1,307 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 44 most recent posts we hold, published 29 June 2026 to 1 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.

Telegram Stars

Stars received
77
across the posts below
Posts paid on
16
of 43 we hold a reading for · 37%
Most on one post
51
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @kdoronin_blog. 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 44 most recent posts we hold for this entry, published 29 June 2026 to 1 November 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.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 6 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).

1 Nov 2026, 18:11 UTC≈2,460 views32 reactionsread 7 November 2026
Photo

AI Dev Live. Версия 2026. Вот и год прошёл с прошлого AI Dev. По насыщенности – как будто все 5. Год назад мы с другими AI-блогерами провели онлайн-конференцию. Без опыта проведения конференций, бюджета, организаторов (спикеры занимались организацией самостоятельно)... Но с огромным желанием сделать действительно круто! Эксперимент удался. Онлайн-конференция собрала 3000 зрителей и множество позитивных отзывов. …

❤16🔥9👍6🏆1

28 Oct 2026, 19:34 UTC≈3,420 views72 reactionsread 7 November 2026
Photo

Тем временем, в приложении Amazon стала доступна Alexa. И сразу создала парадокс:

😁63❤5🔥4

26 Oct 2026, 12:36 UTC≈3,400 views37 reactionsread 7 November 2026
Photo

7 жизней за день. Наткнулся на интересную игру, созданную с помощью Claude Code. https://1in8b.life/ – вот она. Суть в том, что вы случайно рождаетесь где-то в мире (прямо сейчас/в недалёком прошлом или будущем) и проживаете жизнь. По пути ждёт некоторое количество важных решений, формирующих личность. Как и в жизни, чем раньше принимается то или иное решение, тем большее влияние на оставшуюся жизнь оно окажет. …

🔥23👍9❤5

22 Oct 2026, 16:58 UTC≈2,870 views30 reactionsread 7 November 2026
Forwarded from @countwithsashaPhoto

Продал рекламу в канале и сделал ИИ-скилл для продажи рекламы Так как я уже 20 лет работаю в рекламе и на собственной шкуре (а также на шкуре моего DGX Spark) ощущаю всю радость от оформления документов на рекламу в агентстве, то я очень сильно не хотел связываться с размещением рекламы у себя в телеграм-канале: маркировка, ОРД, подготовка договоров, напоминания сделать скриншоты статисткии…. бррр. Но там где есть …

🔥15❤9👍5😁1

19 Oct 2026, 18:02 UTC≈2,600 views37 reactions1 Starread 7 November 2026
Video

Запись стрима про FRIDA decision с таймкодами. Также доступна на YouTube. Полезный стрим для ML-специалистов, а также тех, кто работает с GenAI и хочет лучше разобраться во внутреннем устройстве моделей. Таймкоды: 0:00:00 — Настройка звука и старт эфира 0:08:51 — Знакомство со спикерами и историей команды 0:15:35 — Эволюция эмбеддеров и появление модели FRIDA 0:22:38 — Что такое Decision-модели и их преимущества …

🔥16👍11❤9👏1

13 Oct 2026, 18:22 UTC≈3,080 views29 reactions2 Starsread 7 November 2026
Video

Чуть с запозданием принимаю эстафету от Саши по генерации видео для своих скиллов/продуктов. В качестве "рекламируемого" взял свой мини-проект Video Analyzer, которым я сам регулярно пользуюсь. Попробовал два варианта генерации. Сперва взял расширенный промпт, чтобы агент не только github проанализировал, но и изучил мои посты про Video Analyzer. Получился большой промпт, адаптированный под мою задачу, который не …

🔥14❤6👍6👎2💯1

8 Oct 2026, 15:05 UTC≈8,170 views18 reactions1 Starread 7 November 2026

Мы начинаем наш стрим про FRIDA! https://youtube.com/live/XbmlQvcYc_E – подключайтесь по ссылке

🔥11❤5💘2

6 Oct 2026, 13:01 UTC≈12,400 views40 reactions2 Starsread 7 November 2026
Photo

Сентябрь ознаменовался бумом decision-моделей. Всё началось с Jev, который доступен только через API. То есть на передачу данных можно потратить больше времени, чем на работу модели. Я тоже попробовал decision-модели. Но только те, что работают локально. А потом узнал, что модель FRIDA Decisions всего на 0.8 миллиарда параметров выбивает в бенчмарках результаты, сравнимые с Jev. Приятно ещё и то, что мы с создате…

🔥26❤8👍6

4 Oct 2026, 11:17 UTC≈2,230 views32 reactions1 Starread 7 November 2026
Forwarded from @countwithsasha

Собрал статистику по банам Claude из комментариев в канале Пост с разбором телеметрии, которую видит Claude собрал несколько публичных репостов и тонны комментариев, поэтому я решил изучить все дискуссии в своём канале, а также в канале у Валеры Ковальского, чтобы выделить общие паттерны для бана и способы снижения рисков. 🔁 Общие черты во всех блокировках • Тариф. Все баны — это Max $100+, тариф Pro не трогали. В…

❤12😁8👍7🔥4🤝1

30 Sept 2026, 18:16 UTC≈3,610 views48 reactions1 Starread 7 November 2026
Photo

Утро началось с письма счастья от OpenAI. Суть письма со скриншота примерно в следующем: Теперь за $200 ты будешь получать в два раза меньше токенов. Вот тебе модель GPT-6.1-sol – начинай экономить. Можешь вот ещё по $500 в месяц тратить, если экономия тебе претит. Но там будет лишь немногим больше лимитов, чем у тебя сейчас (но мы их отберём в конце октября, потому что можем) Интересно, что пару дней назад я гово…

❤26👍15🔥6💯1

28 Sept 2026, 03:59 UTC≈3,070 views23 reactions1 Starread 7 November 2026
Photo

Сегодня, 28 сентября, участвую в гостевом прямом эфире. Время начала – 18:00 (GMT+3) Тема эфира: "Мышление в IT подорожало: какие компетенции стали дефицитными, когда код подешевел?" Пригласила к себе Елена Логачева, кризис-ментор для руководителей в IT, эксперт по развитию эмоционального интеллекта. В дискуссии также будет участвовать Александр Киселев – коллега по AI-блоггингу и Python-разработчик. Затронем, п…

❤10👍6🔥5😁2

27 Sept 2026, 18:48 UTC≈2,970 views29 reactionsread 7 November 2026
Video

"Отстойный промпт" © Нравится, как Gemini 3.8 Flash решает задачи в video-to-text. Посмотрел на неделе фильм "Удачи, веселья, не сдохни". Отдыхаю от взаимодействия с AI за просмотром фильма про взаимодействие с AI. Понравился эпизод, который, как мне кажется, наглядно показывает проблемы контекст-менеджмента. Чтобы его вытащить отдельным видео, нужно найти несколько конкретных отрывков в 2-часовом материале, прав…

👍10❤8🔥7😁2🎉1👌1

Showing the 12 most recent of 44 posts we hold for @kdoronin_blog. 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.

Forward network

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 21 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.

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 7 November 2026 — this entry's latest reading, not the date you are reading this.

“Константин Доронин” (@kdoronin_blog), 8,365 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/kdoronin_blog.

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.