Personal blog — 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 22 September 2026 and assigned it the closest of 31 fixed categories, at 54% 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
7 measurements spanning 43 days, net -2. 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 345–353 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
19 Sept 2026, 14:01
350
+1
10 Sept 2026, 11:41
349
+3
31 Aug 2026, 12:55
346
-3
15 Aug 2026, 15:53
349
-2
8 Aug 2026, 06:47
351
no change
8 Aug 2026, 03:00
351
-1
7 Aug 2026, 18:37
352
first reading
Engagement
16 posts held, back to 3 May 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 1 page 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 16 posts for this entry, the most recent from 31 July 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
45m 36s
Average length
15m 12s
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
392 reactions across 15 posts, in 10 distinct kinds. The most used accounts for 36.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
144
36.7%
❤
116
29.6%
❤🔥
67
17.1%
👍
48
12.2%
✍
10
2.55%
⚡
2
0.51%
💯
2
0.51%
👏
1
0.255%
🙏
1
0.255%
🫡
1
0.255%
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 15 of the 16 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 392 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 16 most recent posts we hold, published 3 May 2026 to 31 July 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
4
across the posts below
Posts paid on
4
of 16 we hold a reading for · 25%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @am1rkhairullin. 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 16 most recent posts we hold for this entry, published 3 May 2026 to 31 July 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 не вывез операционку...
Ладно, на самом деле вывез, но не хватило времени и сил на блог)
Более месяца меня не было в медиа поле: ни в тгк, ни в соцсетях,даже в личке много сообщений висят - ну да, я пропал, признаюсь.
Но пропадал я не просто так, я очень много работал. Делал как срочные задачи, так и принимал стратегические решения.
Сейчас тезисно расскажу как прошла моя первая половина лета и затем будет серия …
Если ты не умеешь продавать, то не сможешь зарабатывать
звучит логично, но…
предыстория
24 мая была встреча Поколенцев. Не виделись со всеми уже долгое время. По всем заскучал, было приятно со всеми встретиться.
Тема встречи была продажи.
Нам дали практику. Нужно было продать фитнес абонемент за 24.000
Цель была продать так, чтобы клиент чувствовал что он в выигрыше, а не очередное втюхивание.
Мое решение было…
Я не спал целые сутки
На прошлой неделе я был на хакатоне (это командное соревнование по программированию где нужно решить бизнес задачу)
Ради этого события, приехала моя команда из Москвы
Перед нами стояла задача:
Разработать платформу которая объединяет госзакупщиков и поставщиков. Если конкретнее, то: поставщик вбивает товар, система сама находит 10 аналогов с Wildberries, Ozon, Яндекс Маркета и других российск…
После ролика с Кириллом мне написало очень много людей
У всех примерно одно и тоже. Хотят зайти в нишу, что то пробовали, но не получается. И в техническом плане есть вопросы, и с поиском клиентов.
С каждым кто написал я созвонился лично.
Вчера даже поздним вечером решил провести созвон. Парень чуть чуть знает техничку, но опыта в продажах вообще не было.
Пообщавшись с ним мы разобрали его ошибки и я составил ему…
Знакомьтесь, это Кирилл
Мой ученик, 18 лет, первый курс.
До работы со мной он был обычным парнем, 0 дохода, было желание начать зарабатывать.
После работы со мной: закрыл первого клиента на 100 000 рублей, а сейчас работает с Егором Настоящим. Сам себя обеспечивает и помогает родителям.
Я записал с ним интервью, где он подробно рассказал, с чего он начинал, где искал первых клиентов и что ему помогло выйти на так…
Новый проект на 500к рублей.
Позавчера записывал вам кружок где упоминал что начал работу с новой компанией.
Так вот, это топовый мебельный поставщик Беларуси. Не могу называть название компании, из-за NDA.
Проведя ряд созвонов, мы выяснили проблему, что:
Люди тратят минимум 2 часа в день на поиск информации по внутренней базе знаний. Вручную по документам. Это просто огромнейшая потеря времени и денег.
Наше реш…
С добрым утром ребята, всем видео отправил, сори за задержку - тг очень плохо грузил🤷
Ролик обязателен к просмотру тем, кто в расфокусе и не понимает, что ему делать в ИИ.
+ в конце жирный бонус от моей команды)
Как я вышел на 100к/мес в ИИ-агентах с полного нуля
(И вы можете повторить тоже)
Если ты сейчас смотришь YouTube, пробуешь что-то делать, но клиентов всё нет, то этот ролик снял специально для тебя.
Я прошёл этот путь сам. С кредитом 60к, без кейсов, без связей. И разобрал всё по шагам чтобы тебе не пришлось тратить месяцы на то что не работает.
В ролике я разобрал:
🫠Как приехал в Питер с кредитом 60к и нулём на…
Showing the 12 most recent of 16 posts we hold for @am1rkhairullin. 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.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Какая сейчас твоя главная проблема в ИИ-автоматизации?
Не знаю как найти клиентов42%
Боюсь продавать и вести созвоны14%
Нет технических знаний25%
Не понимаю какой продукт предлагать бизнесу25%
Еще не начал, не знаю с чего начать41%
The shares total 147%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 16 most recent posts we hold, published 3 May 2026 to 31 July 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Mentions
Named by 1 registered channel — 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 19 September 2026 — this
entry's latest reading, not the date you are reading this.
“Амир Хайруллин” (@am1rkhairullin), 350 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/am1rkhairullin.
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.
