4 measurements spanning 6 days, net +10. 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 3,199–3,212 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
11 Aug 2026, 18:42
3,210
+4
9 Aug 2026, 00:51
3,206
+6
6 Aug 2026, 04:49
3,200
no change
6 Aug 2026, 04:35
3,200
first reading
Engagement
16 posts held, back to 10 April 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 3 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
59.2%
avg views ÷ 3,210 subscribers
Avg views / post
1,900
2 posts measured
Reaction rate
4.16%
reactions ÷ views · ER floor
Posts in window
2
of 16 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 3 August 2026
Posts held
16 (10 April 2026 – 3 August 2026)
Views total
3,800
Reactions total
158
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 23:42 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
30s
Average length
30s
Measured directly from 1 video 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
998 reactions across 16 posts, in 23 distinct kinds. The most used accounts for 36.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
359
36.0%
🔥
291
29.2%
👍
141
14.1%
😁
51
5.11%
🤣
43
4.31%
🎉
35
3.51%
⚡
13
1.30%
👏
13
1.30%
🏆
11
1.10%
🆒
6
0.601%
🐳
6
0.601%
😴
6
0.601%
🤔
4
0.401%
🍓
3
0.301%
🤡
3
0.301%
🦄
3
0.301%
🌚
2
0.2%
👾
2
0.2%
🥰
2
0.2%
❤🔥
1
0.1%
3 further kinds
3
0.301%
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 16 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 998reactions 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 10 April 2026 to 3 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
152
across the posts below
Posts paid on
13
of 16 we hold a reading for · 81%
Most on one post
36
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @max_dot_sh. 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 10 April 2026 to 3 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.
Это я интересно на новое место вышел.
Только пришел и сразу переезд в новый офис.
Сочный вид на город и центральный вокзал с террасы на крыше.
Еще и набор лего подарили. Воспроизведение культовой партии AlphaGo против Lee Sedol, где машина сделала тот самый ход 37.
Если кто не смотрел документальный фильм про альфа го, то к просмотру обязательно. Драма уровня праймового Нолана.
Некоторые место работы выбирают по…
Еще одна идея над которой успел поработать перед уходом из стартапа – это AI код ревьюеры.
В какой-то момент, как и многие стартапы, мы стали строить свою Software Factory (воркшоп от Курсора, если интересуетесь) с идей того, чтобы 0) cтать настоящей AI Native Dev компанией 1) еще быстрее шипить новый софт 2) продавать это другим.
Агентские код ревьюеры – это один из блоков такой фабрики, я и исследовал, какие суще…
Начинаю рассказывать, что интересного получилось поделать в свой финальный отрезок работы в стартапе.
И начну с статьи. Почитать можно тут.
Из приятного, ее недавно приняли на KDD – такая конфа с фокусом на приложения ML в индустрии, датасеты и эвалы. В этом году пройдет в Корее (что-то на азию всех потянуло, сейчас там проходит ICML).
Теперь к сути. К нам часто приходили энтерпрайзы с одними и теми же вопросами:…
💼 Career Update. Ухожу из стартапа
Расскажу чем занимался последний год и куда двинулся теперь.
⏹️Чуть больше года назад я присоединился к раннему стартапу Tessl (писал тут). Первая идея компании была сделать движок для Spec Driven Development (SDD) и развить вокруг него экосистему: что-то типа нового Github-а, но для спецификаций. Большой раунд ($125M), опытный фаундер, талантливая команда и идеальное время, чтобы…
⚽️ Чемпионат мира по футболу стартанул и это повод сделать еще один небольшой проект.
Так появился GoalStake – площадка, где можно создать турнир, пригласить друзей, выдать всем стартовый капитал игровых монет и соревноваться в прогнозах на исходы матчей, используя реальные вероятности исходов. Весело (потому что играешь с друзьями). Непредсказуемо (потому что чемпионаты всегда такие)
Ссылку на проект публично не ш…
🕹 Давно хотел сделать клон старенькой игры Ice Rage, в которую рублися c друзьями в школе на переменах. К сожалению, на свежих iOS в нее уже не поиграть... Но для этого и нужны агенты!
Поиграть в браузере можно тут, на телефоне тоже запускается, но с ноута сильно комфортнее.
За одно и возможность потестить агентов на реальных Long Horizon Tasks.
Длинные автономные сессии агентов один из тренд текущего года. Вместо…
Хочу поделиться крутым образовательным ресурсом. А именно ссылкой на ютуб канал рисерчера и профессора из университета Мэриленда Jia-Bin Huang (он еще будет себе осенью набирать phd студентов – кому актуально)
Здесь можно найти множество интересных разборов из современного DL, а последние видео точечно рассказывают про концепции из архитектур и обучения свежих LLM-ок:
- Как устроен оптимизатор Muon
- Как дизайнить …
Реклама AI инструментов продолжает захватывать Лондонскую подземку.
В коллекцию к JetBrains и Lovable добавляется Vercel
Если первые две компании точно все знают, то Vercel не такой очевидный (ну или мне так кажется). Они делают тулы для быстрого/безопасного деплоя веб приложений. Отмечу что действительно очень удобно и круто (Next.js тоже был разработан ими).
Сейчас ударились в агентов и предлагают какие-то автом…
А вы знали, что в стандартном механизме внимания есть неэффективность?
Она называется attention similarity bias.
Разберемся. В стандартной формуле attention для каждого токена мы считаем query, key и value, затем считаем attention scores: насколько query текущего токена похож на ключи других токенов. После этого агрегируем value векторы с attention-весами и получаем выходной вектор для токена, условный y.
Оказывае…
Вчера стартап Миры Мурати, Thinking Machines, анонсировал новый продукт – Interaction Model: реал-тайм мультимодального голосового ассистента.
Анонс вышел тихим. Выкатили технический блог пост и записали несколько демок (комментарии к видео отключены 😁 ) Возможно так тихо, потому что показать пока реально нечего – обещают лимитированное ревью в течение следующих месяцев. Более крупный запуск обещают когда-то в этому…
How Well Do Agentic Skills Work in the Wild?
Про скиллы для кодинг агентов не слышал уже наверное только ленивый. Их легко создавать, появляются маркетплейсы, чтобы их было легче распространять и они точно помогают заставить агента учитывать преференции каждого конкретного инженера.
А вот исследований, чтобы численно померить импакт от скиллов, как делать их эвалы (сейчас в вялом режиме пишу статью для воркшопа на …
🔥24❤9👍4🐳3🆒1
Showing the 12 most recent of 16 posts we hold for @max_dot_sh. 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 — 61,068 of 1,151,006entries 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 4 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 11 August 2026 — this
entry's latest reading, not the date you are reading this.
“max.sh” (@max_dot_sh), 3,210 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/max_dot_sh.
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.
