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Второй канал t.me/glebkudr
Личка t.me/glebkudr1
Created
Between 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
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 10 September 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.
Growth
60 measurements spanning 92 days, net +2,428. 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 13,960–17,126 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)
Subscribers
Change
6 Nov 2026, 03:18
16,761
+138
5 Nov 2026, 02:56
16,623
+52
4 Nov 2026, 05:32
16,571
+161
3 Nov 2026, 04:38
16,410
+143
2 Nov 2026, 06:20
16,267
+82
1 Nov 2026, 04:10
16,185
+39
31 Oct 2026, 04:07
16,146
+130
30 Oct 2026, 06:21
16,016
+153
29 Oct 2026, 08:48
15,863
+370
28 Oct 2026, 09:37
15,493
+140
27 Oct 2026, 09:29
15,353
+115
26 Oct 2026, 07:48
15,238
+22
25 Oct 2026, 05:27
15,216
+27
24 Oct 2026, 02:55
15,189
+34
23 Oct 2026, 03:14
15,155
+31
22 Oct 2026, 05:41
15,124
+85
20 Oct 2026, 21:36
15,039
+138
19 Oct 2026, 19:21
14,901
+8
18 Oct 2026, 19:38
14,893
-1
16 Oct 2026, 21:54
14,894
first reading
Engagement
86 posts held, back to 22 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 60 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
34.9%
avg views ÷ 16,761 subscribers
Avg views / post
5,840
30 posts measured
Reaction rate
1.20%
reactions ÷ views · ER floor
Posts in window
30
of 86 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 6 November 2026
Posts held
86 (22 July 2026 – 6 November 2026)
Views total
175,310
Reactions total
2,096
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Nov 2026, 16:32 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
314
Videos
30
Links
228
Lifetime counters from Telegram’s own channel header, read 6 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
1m 55s
Average length
38s
Measured directly from 3 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
5,450 reactions across 81 posts, in 46 distinct kinds. The most used accounts for 27.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
😁
1,492
27.4%
🔥
1,011
18.6%
👍
834
15.3%
❤
699
12.8%
💯
531
9.74%
🤣
310
5.69%
😎
54
0.991%
😢
47
0.862%
😭
46
0.844%
🤔
40
0.734%
🤷♂
36
0.661%
🙉
30
0.55%
💅
28
0.514%
🤯
26
0.477%
👏
24
0.44%
💔
24
0.44%
🤨
22
0.404%
👀
19
0.349%
🕊
19
0.349%
🤷♀
19
0.349%
26 further kinds
139
2.55%
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 84 of the 86 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 5,620 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 86 most recent posts we hold, published 22 July 2026 to 6 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
39
across the posts below
Posts paid on
10
of 85 we hold a reading for · 12%
Most on one post
11
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @gleb_pro_ai. 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 86 most recent posts we hold for this entry, published 22 July 2026 to 6 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: 15 of 30 posts held from the last 30 days (50.0%) 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).
Я работаю сейчас в основном с архитектурными проектами (не микросервисы, а мосты, дороги, нефтетрубы). Но тут пришли товарищи из мира мебели, и попросили помочь им с ИИ.
Ну что ж — вызов принят. В качестве упражнения, решил оценить, насколько агенты справляются с типичными клиентскими заказами.
Взял рандомную картинку из интернетов, обвесил некоторым количеством скиллов, и отдал опусу.
2 часа пил чай и лениво вбил…
Сейчас ситуация это буквально казино, "угадай, на каком сетапе из говна и палок будут инфериться топовые модельки через пол-года. Верно один из пяти, остальное в утиль. "😁
Очень коротенький апдейт про датацентр.
Во время написания поста цены на видяхи и память были в 1.5 раз меньше, чем сейчас. Моделька сходилась. Интерес был хороший, и даже предварительно договорился на несколько чеков.
Но пока туда-сюда, резко скакнула цена видеокарт. И честная модель сходиться перестала, ну точнее перестала удовлетворять критериям венчурности.
Мой прогноз на 2027, кстати, остается таким, что желе…
Я решил начать проводить открытые лекции Лабы. У нас очень крутой контент и хочется его показывать более широкой аудитории.
Первая публичная лекция будет завтра в четверг, в 18:00 по Москве
Перепрограммируем свою клавиатуру с агентами и под агентов
Разнообразные кастомные/программируемые/сплит клавиатуры существуют давно. Но недавно у нас, в очередной раз, изменился сам способ взаимодействия с нашими устройствами.…
Я завел морских свинок. Дети очень просили.
И что бы вы думали я теперь делаю?
Правильно, опус чертит мне систему для проращивания травы с автоматическим поддержанием уровня воды 😁
Этим, к слову, объясняется народная любовь к готовым промптам.
Если ты уже видел результат, и он тебя устраивает, то достаточно теперь получить заклинание, которое именно его от ЛЛМ и требует. А значит, сокращает тонну мозговой активности для его формулирования (и часто это уровень, который для среднего пользователя без готового промпта может быть в принципе недостижим).
Это давно уже общее место, но почему-то поймал себя сегодня на месте, что единственный вопрос который я задаю в работе сейчас — это "как мы поймем, что сделано то, что нужно".
Ну т.е. буквально вся работа определяется через этот вопрос. Если его в достаточной степени описать в рамках способностей ллм, то дальше выполнение это просто сколько-то часов агента.
Т.е.
— ваша способность сформулировать словами критерии п…
Собираю конфу про ИИ
Короче. Есть у меня любимый чатик. В нем всего 26 человек, зато все — это известные вам ИИ блогеры.
Мы там обсуждаем харнесы, агентов, новости индустрии, политику и т.д. Общение тесное и доверительное. Гача-стикеры — ежедневная норма, а уж логотип и я вообще не буду показывать.
Именно там, например, я познакомился с Валерой, а теперь у него в подвале стоит мой комп с видюхой под OCR.
Отличаемся…
Есть такой движ — build in public. Суть в том, чтобы рассказывать о своем пути разработки продукта задолго до его релиза.
Со началом вайбкодинга данная парадигма вступила в эру кризиса. Билдеров и продуктов стало слишком много, чтобы на них хватало внимания публики.
Гвоздь в крышку забила череда недавних скандалов, когда копии свеже-анонсированных продуктов начали появляться через 1-2 дня после рассказа о них в соц…
Товарищи, я хочу найти звукаря для геймдева, который способен выдать качество уровня Noita
Что нужно?
Есть игра. Нужно подобрать музыку, переходы, звуки монстров и механизмов, плюхи и шлепы заклинаний, а так же их программные миксы так, чтобы уши были в экстазе, а игрок получал то настроение, которое задумано от данной локации.
Нейронки сами по себе так не умеют. Совсем без нейронок это делать долго. А с нейронкам…
😁16🔥14❤7🤣1
Showing the 12 most recent of 86 posts we hold for @gleb_pro_ai. 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.
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 26 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“Глеб Кудрявцев — мастер AI” (@gleb_pro_ai), 16,761 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/gleb_pro_ai.
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.