3 measurements spanning 7 days, net +6. 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 691–699 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 14:14
698
+6
7 Aug 2026, 09:56
692
no change
7 Aug 2026, 09:48
692
first reading
Engagement
18 posts held, back to 16 October 2025 — 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 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
32.2%
avg views ÷ 698 subscribers
Avg views / post
225
2 posts measured
Reaction rate
6.22%
reactions ÷ views · ER floor
Posts in window
2
of 18 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 31 July 2026
Posts held
18 (16 October 2025 – 31 July 2026)
Views total
450
Reactions total
28
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 09:48 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
250 reactions across 17 posts, in 5 distinct kinds. The most used accounts for 58.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
147
58.8%
😁
38
15.2%
❤
36
14.4%
👍
27
10.8%
👎
2
0.8%
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 17 of the 18 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 250reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 16 October 2025 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
50
across the posts below
Posts paid on
15
of 18 we hold a reading for · 83%
Most on one post
12
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @surkiz_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 18 most recent posts we hold for this entry, published 16 October 2025 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.
ИИ есть, а доступа нет 🤖
Несколько лет назад, когда популярные ИИ сервисы один за другим начали блокировать доступ россиянам, я подумал: ну фигня какая-то. Мы уж точно найдём, как всё это обойти, оплатить и настроить.
Оказалось, я сильно недооценил проблему.
За последнее время я провёл несколько воркшопов в компаниях по работе с ИИ-агентами. И был неприятно удивлён: даже опытные разработчики и вполне технические л…
Телеком умер, да здравствует телеком! 📡
В далеком 2004 году я устроился админом в КрафтСвязь Новосибирск. Админил хостинг, почтовые серверы, D-link, Cisco, MERA, SIP, Asterisk и пр. Потом были Новотелеком, он же Электронный город, ИнфоСвязь... В общем, успел поработать во всех крупных провайдерах Новосибирска.
Прошло 20 с лишним лет, и я снова пишу про телеком. Только теперь про AI.) В прошлую технологическую волну…
Смотри, всю неделю был дождь. У меня грязная машина, мне нужно ее помыть.
И всего в пяти минутах ходьбы есть замечательная мойка.
А сейчас на улице прекрасная солнечная погода. Тепло, светло, зелено.
Как думаешь, мне лучше пройтись пешком или доехать на машине? Давай взвесим плюсы и минусы
Отправил этот вопрос почти во все модели, которые были под рукой.
Справилась только одна. Угадайте, какая?
@surkiz_blog
Моя новая статья в Forbes вышла сегодня 🖌️
Следующий шаг ИИ – не интеллект, а действие в реальном мире.
ИИ уже умеет планировать поездку, рекомендовать ресторан, составлять план работы. Но он до сих пор не может забронировать, оплатить или подтвердить. Разрыв между «вот что тебе нужно сделать» и «готово» – это и есть следующее поле конкуренции.
В статье разбираю:
— Что на самом деле нужно для ИИ-агентности в реаль…
Сегодня закончили обучение по внедрению агентного ИИ в процессы разработки одной крупной компании. Руководство и менеджмент довольны, а сотрудников и технарей ждут перемены. Сейчас особенно важно быть готовым учиться новому и перестраивать свои рабочие процессы 🦾
Некоторые только-только освоили ChatGPT, как он устарел 😔 (я сам уже несколько месяцев как перестал им пользоваться). Год-два назад мне казалось, что техно…
Жизненный цикл разработки ПО мертв? 😨
Борис Тейн написал статью я перевёл и выложил её тут.
Главный тезис: ИИ-агенты не ускорили SDLC – они его убили. 😵
Вместо цепочки «требования → дизайн → код → тесты → ревью → деплой → мониторинг» осталось: «намерение → агент → наблюдение → повтор.»
И я это наблюдаю на себе и когда строишь продукт с агентами, классический SDLC реально рассыпается, а Jira в этом процессе как фак…
— "Что делается… Раньше шубы, мотоциклы доставали. Теперь детей доставать начали."(с) Кот Матроскин 🙀
А теперь награды за токены раздают) 🤖
Поздравляю нас!
@surkiz_blog
2PR.io v2.0
Ислам, мой партнер по Copilot2trip перезапускает свой стартап 2PR.io на Product Hunt!
В прошлый раз они уже выиграли и если у вас есть аккаунт на PH поддержите upvot’ом!
https://www.producthunt.com/products/2pr-2?launch=2pr-v-2-0
Спасибо! 🙏
Чуть больше полутора лет спустя, новое интервью оказалось ещё лучше предыдущего.
Вам нужно его посмотреть! 💯
P.S.
Больше всего мне нравится наблюдать за работой их зеркальных нейронов) за тем, как братья научились синхронизировать два своих мозга в единое целое и это безусловно дает им преимущество! 🧠+🧠=🖐️
https://youtu.be/wp7izqZmiWM
@surkiz_blog
🔥6👍3❤1
Showing the 12 most recent of 18 posts we hold for @surkiz_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.
Citation-graph rank
Citation-graph rank — 606,377 of 1,549,376entries 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
Republishes
Channels on the register whose posts this channel has forwarded.
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 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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“Макси́м Сурки́з – Создаю продукты” (@surkiz_blog), 698 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/surkiz_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.