Честный взгляд на внедрение ИИ в бизнесе и в жизни.
Мои клиенты уже сделали это: 500+ компаний, 3+ тыс учеников
Бесплатный мини-курс по ИИ
https://go.cyber-misha.ru/HphoaJn
AI_разработка, корпоративное обучение
напишите мне: @ai_petukhov
Created
Between 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
9 measurements spanning 7 days, net +34. 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 25,838–25,882 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 07:06
25,877
+3
12 Aug 2026, 21:56
25,874
+7
11 Aug 2026, 22:58
25,867
+4
11 Aug 2026, 01:11
25,863
+5
9 Aug 2026, 23:37
25,858
+4
9 Aug 2026, 02:51
25,854
+1
8 Aug 2026, 06:17
25,853
+10
7 Aug 2026, 13:00
25,843
no change
7 Aug 2026, 12:59
25,843
first reading
Engagement
31 posts held, back to 23 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 19 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
5.41%
avg views ÷ 25,877 subscribers
Avg views / post
1,400
31 posts measured
Reaction rate
2.04%
reactions ÷ views · ER floor
Posts in window
31
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 14 August 2026
Posts held
31 (23 July 2026 – 14 August 2026)
Views total
43,404
Reactions total
885
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
14 Aug 2026, 15:53 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
730
Videos
177
Links
775
Lifetime counters from Telegram’s own channel header, read 14 August 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.
Reaction mix
885 reactions across 31 posts, in 8 distinct kinds. The most used accounts for 36.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
320
36.2%
🔥
283
32.0%
❤
258
29.2%
🦄
9
1.02%
🐳
8
0.904%
🤔
4
0.452%
👀
2
0.226%
custom 5274195706066781810
1
0.113%
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 31 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 885reactions 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 23 July 2026 to 14 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
1,002
across the posts below
Posts paid on
3
of 31 we hold a reading for · 10%
Most on one post
1,000
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @cyber_misha. 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 31 most recent posts we hold for this entry, published 23 July 2026 to 14 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.
Я устроил тест, а ИИ спалил правильный ответ
Кибер-привет, товарищи❗️
Вчера я дал вам две презентации из одной и той же фактуры и предложил определить, где нейросеть работала со скиллом.
Раскрываю ответ: скилл использовался в презентации №2.
Хотя нейросеть решила немного помочь и мелким шрифтом оставила на первой презентации подпись «БЕЗ СКИЛЛА».
Вот и вся интрига 😂
Внимательные товарищи нашли подсказку, часть …
СОБЫТИЕ ЛЕТА
Уже сегодня.
Самая закрытая трендсессия.
Эксперты — экспертам.
Обсудим:
- Рынок elite / deluxe: состояние сегмента и прогноз
- Куда уходят клиенты люкс-сегмента
- Инсайты по неиспользуемому потенциалу радио и прессы
- Кто звонит в классифайдах?
- Тренды применения медиа направлений в России и мире
- Об усилении роли бренда в текущей ситуации
- Мировые события, которые глобально повлияли на развитие, т…
В какой презентации ИИ работал со скиллом?
Выше прикрепил две презентации по 3 слайда.
Обе собраны из одной и той же фактуры.
Но в одном случае нейросеть получила обычный запрос, а в другом работала по скиллу с правилами и проверкой результата.
Изучите обе презентации и попробуйте определить, где использовался скилл.
Ставьте реакцию:
👍, если выбираете презентацию 01.
🔥, если выбираете презентацию 02.
Позже по…
Разница в скиллах.
Кибер-привет, товарищи❗️
Вчера я разобрал 6 частей рабочего скилла: цель, входные данные, шаги, примеры, стоп-лист и проверку.
Сегодня покажу, что они меняют на практике.
Возьмём тестовую фактуру:
«В компании подготовка еженедельного отчёта занимала три часа. ИИ-агент собирает данные из таблиц и готовит черновик за двадцать минут. Руководитель проверяет цифры перед отправкой».
Сначала просим н…
Что лежит внутри скилла, кроме длинного промта?
Кибер-привет, товарищи❗️
Вчера я показал разницу между промтом, ассистентом и скиллом на поиске новостей.
Промт ставит одно поручение. Ассистент хранит контекст. Скилл закрепляет способ работы и проверку результата.
Сегодня открыл один из наших рабочих скиллов для создания презентаций. Внутри не простыня текста, а шесть отдельных частей.
🔤 Когда включаться.
Скилл …
ИИ нашёл новость, а проверить дату снова забыл
Кибер-привет, товарищи❗️
Вчера я спросил, в какой задаче вам чаще всего приходится заново объяснять ИИ одни и те же правила.
Победили поиск и проверка информации: 42% и 22 голоса.
Поэтому на этой задаче покажу, где заканчивается промт и начинается скилл. Допустим, каждую неделю вам нужно найти пять важных новостей об ИИ, проверить их и собрать короткий дайджест со сс…
Что руководитель не имеет права отдавать ИИ?
Кибер-привет, товарищи❗️
Я внедряю ИИ в компании и постоянно вижу одну закономерность.
Сначала нейросети отдают тексты и отчёты. Затем документы, решения по клиентам, контроль сотрудников и управления над важными процессами.
Машина работает быстро, но если руководитель уже не понимает, почему принято решение и кто отвечает за ошибку, компания получает скорость вместе с…
Как перестать объяснять ИИ одни и те же правила?
Кибер-привет, товарищи❗️
В пятницу я разобрал четыре уровня ИИ-агентов: от готового сервиса до собственного сотрудника компании.
В финале оставил 2 вещи, без которых своего агента не собрать: скиллы и вайбкодинг.
Эту неделю посвящаем скиллам.
Сейчас многие называют скиллом любой длинный промт. Сохранили инструкцию на три страницы, вставляют её в каждый новый чат и…
ИИ в Telegram: куда на самом деле уходят ваши сообщения?
Кибер-привет, товарищи❗️
Я опубликовал новый ролик о том, что скрывается под знакомыми логотипами ChatGPT и Claude в Telegram-ботах.
В ролике разобрал:
🔤почему вместо обещанной модели вам может отвечать старая и дешёвая.
🔤 как сообщение проходит через сервер владельца бота до нейросети.
🔤 кто технически может получить ваши договоры, базы клиентов и рабочи…
4 уровня ИИ-агентов: от подписки до своего сотрудника.
Кибер-привет, товарищи❗️
Вчера я показал вам ChatGPT Work и Claude Cowork. Но это только один вид агентов.
Сейчас словом «агент» называют вообще всё: сохранённый промт, чат с инструкцией, отдельный сервис и систему, которая управляет половиной компании.
Сначала разделим два понятия.
• Ассистент хранит промт и отвечает на запрос.
• Агент получает задачу, раз…
Бесплатный мини-курс, здесь
Кибер-привет, товарищи❗️
Многие использует ИИ в своих проектах/бизнесах, как отдельные инструменты.
В одной ИИ сделали пост, в другой картинку, в третьей сайт и т.д
А что, если можно сделать целую систему, благодаря которой вы закроете 80% своих задач, и для этого не нужно кучу подписок.
Я записал полноценный бесплатный мини-курс из 3х уроков о том, как выбрать рабочий процесс, собрат…
❤12🔥12👍8🦄4
Showing the 12 most recent of 31 posts we hold for @cyber_misha. 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.
Citation-graph rank
Citation-graph rank — 96,844 of 1,345,403entries 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 6 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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“Кибер-Миша | ИИ для бизнеса” (@cyber_misha), 25,877 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/cyber_misha.
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.