8 measurements spanning 7 days, net +72. 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 16,168–16,262 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 01:36
16,251
+15
10 Aug 2026, 22:12
16,236
+2
9 Aug 2026, 22:21
16,234
+24
8 Aug 2026, 22:22
16,210
+10
7 Aug 2026, 22:11
16,200
+11
6 Aug 2026, 20:28
16,189
+10
6 Aug 2026, 02:19
16,179
no change
5 Aug 2026, 22:00
16,179
first reading
Engagement
21 posts held, back to 24 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 17 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
22.4%
avg views ÷ 16,251 subscribers
Avg views / post
3,630
21 posts measured
Reaction rate
1.17%
reactions ÷ views · ER floor
Posts in window
21
of 21 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 12 August 2026
Posts held
21 (24 July 2026 – 12 August 2026)
Views total
76,320
Reactions total
892
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Aug 2026, 00:59 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
Video runtime
2m 08s
Average length
32s
Measured directly from 4 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
825 reactions across 19 posts, in 22 distinct kinds. The most used accounts for 33.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
277
33.6%
❤
199
24.1%
🔥
176
21.3%
✍
46
5.58%
👏
28
3.39%
🤯
19
2.30%
👎
12
1.45%
👾
10
1.21%
⚡
9
1.09%
🦄
9
1.09%
😁
8
0.97%
🏆
6
0.727%
🕊
6
0.727%
🤩
6
0.727%
🤓
3
0.364%
😍
2
0.242%
🙈
2
0.242%
🤔
2
0.242%
🥰
2
0.242%
👨💻
1
0.121%
2 further kinds
2
0.242%
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 21 of the 21 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 892reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 24 July 2026 to 12 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
26
across the posts below
Posts paid on
6
of 21 we hold a reading for · 29%
Most on one post
10
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @TochkiNadAI. 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 21 most recent posts we hold for this entry, published 24 July 2026 to 12 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.
Несу вам классную шпаргалку.
Это 114 сервисов, которыми пользуюсь сам или пользовался и считаю достойными внимания. Разложены по 18 категориям и 7 главам: чаты и поиск, редакторы и кодинг-агенты, голос и документы, дизайн, данные, инфраструктура.
Что внутри:
→ каждое название кликабельно и ведет сразу на сайт
→ у каждой категории подводка о том, зачем она вообще нужна
→ выбор инструмента за четыре вопроса
→ две шпа…
Разобрал актуальную для многих тему – как уговорить AI-модель писáть нормально
Разбираю подход через создание и улучшение скилла для копирайта, убивающего ии-слоп в текстах.
Статья тут.
Вчера почему-то в твиттере завирусилось видео Антропиков про Managed Agents, хотя ему уже больше 2 месяцев
НО лекция актуальна, поэтому я решил дополнить ее важными поинтами из официальной документации и собрал небольшой гайд, чтобы разобраться в теме.
Внутри три главы:
- зачем это нужно: что такое агентный цикл, почему свой харнесс дорого стоит и что платформа забирает на себя;
- из чего собран агент: Agent, Envi…
Периодически пишу тут про Second Brain, а сегодня обновил емкий гайд с основной информацией для разворачивания минимально-жизнеспособного Второго Мозга.
(кстати, сам термин "секонд брейн" уже как будто бы оброс пошлостью, учитывая как часто пишут об этом в соц. сетях и блогах, иногда не понимая сути и предмета. Может быть у вас есть идеи другого названия для такой офигенной системы?)
Короткое определение – Second B…
А ролик Фримана про ИИ уже вышел
Черно-белый трикстер как всегда ковыряет социальные проблемы и колючие вопросы современного общества. На этот раз через призму AI индустрии, кризиса на рынке труда и всего сопутствующего.
Смотрим тут!
Внезапно начал все чаще попадать в рейтинг лучших тг-блогов на VC
В последние дни стабильно держу третью позицию, посты получают хорошие охваты и постоянно мелькают в разделе популярных.
В связи с этим решил сделать скилл для агента, который будет переносить статьи с сайта на VC, с учетом верстки и разметки, чтобы не делать этого руками.
Конечно же, первым делом попросил агента понять как это делать быстрее, с уче…
Несу вам еще один полезный скилл для агента.
Называется human-review, он превращает работу с HTML и маркдаун в Google Docs‑лайк интерфейс.
Открываешь файл или локальную страницу через human-review и видишь визуальный редактор.
Слева – превью, справа – панель с фидбэком и комментариями по конкретным элементам.
Можно править текст/форматирование, двигать и ресайзить картинки прямо в интерфейсе.
Все правки и ком…
Как создавать и поддерживать ваши сайты при помощи агентов
Несколько раз за последние 2 недели получал вопросы из разряда – как подключить агента к сайту на Тильде, на Вордпрессе, на условном конструкторе.
Ответ: вам это не нужно, точно-точно. Точнее, можно, но проблема в том, что сайт останется запертым внутри чужого платного редактора с кучей ограничений.
Я свои сайты веду иначе, и вся работа давно свелась к одн…
Вот нам с вами еще несколько сервисов в коллекцию, которые можно отдать вашим агентам, чтобы дизайн стал заметно симпатичнее:
canvasui.dev – WebGL-эффекты поверх живого HTML.
beam.jakubantalik.com – анимированный эффект светящейся рамки.
originkit.dev – бесплатная библиотека анимированных компонентов.
aicss.dev – UI-компоненты для чатов с AI-агентами.
transitions.dev – базовые переходы для веб-приложений.
metal…
Как начать выводить сайт в топ выдачи поисковиков и в ответы LLM-моделей
Выпустил статейку на фоне последних рабочих сессий с агентом.
До этого, конечно, тоже многое в этом направлении с ним пробовали и собирали, про что-то я даже писал тут в канале в формате постов, можете тоже почитать и отдать своему агенту.
И да, эту свежую статью тоже в первую очередь собирал для ваших агентов на основе опыта моего агента.
В…
Испытываю огромную благодарность скиллу для создания слайдов
Первую его версию я собрал в декабре 2025 года. Цель – собирать презентации в единой стилистике для эфиров и лекций AI Кэмпа.
С тех пор я регулярно его обновлял: добавлял новые шаблоны, корректировал промпты, тестировал разные модели для генерации в API. Сейчас папка скилла – это десятки емких интрукций и шаблонов + несколько скриптов.
Из последних новов…
Внезапный камбэк острого, злободневного и во-многом философского героя нашего времени
Мне вчера написал Павел и прислал эту ссылку.
И более того, поделился не то что бы инсайдом, но жирным намеком на то, что тема нового Мистера Фримана будет во-многом совпадать с темой этого канала.
Чур я вам не говорил.
Итак. Премьера 6 августа 2026 года
Mr. Freeman, part 16 // ждем
🔥15🦄9❤8👍4👎3
Showing the 12 most recent of 21 posts we hold for @TochkiNadAI. 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 — 19,863 of 1,160,990entries 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 15 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 13 August 2026 — this
entry's latest reading, not the date you are reading this.
“Точки над ИИ” (@TochkiNadAI), 16,251 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/TochkiNadAI.
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.
