Telegram RegisterThe public register of Telegram
Telegram profile photo for LLM Кунг-фу 🥋

Channel

LLM Кунг-фу 🥋

@llmkungfu

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Polls · Citations · Cite this entry

215subscribers

+53 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1004318824144
TypeChannel
Username@llmkungfu
CreatedBetween 1 June 2026 and 22 July 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live16 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 16 August 2026
On Telegramt.me/llmkungfu

Growth

162215188.57 August 2026 — 162 subscribers8 August 2026 — 171 subscribers8 August 2026 — 171 subscribers16 August 2026 — 215 subscribers7 August 202616 August 2026
4 measurements spanning 8 days, net +53. 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 154–223 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
16 Aug 2026, 05:22215+44
8 Aug 2026, 14:46171no change
8 Aug 2026, 07:32171+9
7 Aug 2026, 20:27162first reading

Engagement

19 posts held, back to 22 July 2026the 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
125.3%
avg views ÷ 215 subscribers
Avg views / post
269
19 posts measured
Reaction rate
1.32%
reactions ÷ views · ER floor
Posts in window
19
of 19 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. It is computed over the 10 of 19 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held19 (22 July 20267 August 2026)
Views total5,117
Reactions total40
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 14:46 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

40 reactions across 10 posts, in 8 distinct kinds. The most used accounts for 40.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍1640.0%
😁615.0%
💊512.5%
🔥512.5%
🤡410.0%
👎25.00%
12.50%
👏12.50%

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 10 of the 19 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 40reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 22 July 2026 to 7 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.

Recent posts

7 Aug 2026, 12:20 UTC279 views9 reactionsread 8 August 2026
Photo

Дешевые токены OpenAI/Claude Мы все про дипсик да про дипсик, в противовес жирным подпискам на "настоящий" фронтир, с его конскими ценами. Но так то есть и другие варианты, с приемлемыми ценами, прямым API и без рисков блокировки в РФ (если бы еще оплату хотя бы криптой прикрутили - цены бы им не было) А именно - нашим китайским братьям тоже хочется потыкать новые модельки у антропиков и альтмана, и они точно так ж

👍71😁1

6 Aug 2026, 11:13 UTC192 viewsread 8 August 2026

Reasonix, часть вторая Итак, вчера сидел над еще одним фан проектом, уже более близкий к реалиями веб приложений, и определенно есть изменения: 1. Агент стал работать намного дольше. Плюс за счет того, что все вызовы утилит и размышления сворачиваются (тогда как в опенкоде тебе просто летит весь поток сознания от модели) - кажется что оно тормозит. Но нет, оно просто больше работает 2. Больше спрашивает разрешений

6 Aug 2026, 11:13 UTC262 views1 reactionsread 8 August 2026

В общем, посмотрим, с агентской оберткой точно получается дичь по расходам, с промтами оно еще более-менее бы вытягивало по ценами апи (думаю, что в опенкоде я бы ту же работу впихнул бы в 100-150м токенов, не давая ему слишком сильно гулять, но и ручного контроля и правок от меня было бы намного больше конечно - причем изначально поиск по теме я там вел, и переиспользовал данные), а вот «агентом» уже кажется что по

👍1

4 Aug 2026, 20:30 UTC193 views6 reactionsread 8 August 2026
Photo

Reasonix - десктоп IDE под дипсик Пастухов меня опередил, у него в комментах увидел ссылку, скачал, установил - и офигел) ( https://reasonix.io/ ) После него опенкод - это просто чатик с табами, где почти все надо настраивать ручками или через чат. Ну и со всеми обертками оно стало умнее раза в два, хотя на некоторых вопросах все еще подвисает. Конечно, больно смотреть на утекающие центы (закинул денег на оффициаль

👍5🔥1

1 Aug 2026, 13:09 UTC303 views5 reactionsread 8 August 2026
Photo

Итоги июля, потсоны! Немного перебор теории и разовых задач (пора уже отдельного агента делать для создания отчетов, а то дефолтный дипсик всегда пилит темную тему, мелкие шрифты и плохо рисует графики с двумя датасетами), но в целом для первого месяца вкатывания отлично) Вчера докачалась выгрузка данных из гугла, поиграл со статой из ютуба, жаль она с 2023-го (50к видосов, большая часть шортсы, ибо не разделяет он

😁5

31 Jul 2026, 18:09 UTC284 views6 reactionsread 8 August 2026
Video

Deep research, deep research! Сегодня дипсик: • Не смог найти это видео в загрузках (но тут я тоже виноват, помню обрывками, и в гугле я тоже его не нашел) • • Не стал мне искать абузоустойчивых хостеров (illegal activity) • • Сделал рисерч по малостраничникам и отчет (кожанный аналитик за это брал 5к в часах работы) • • Сделал одностраничный генератор коллажей из фото (дольше искать бесплатное приложение или апп, и

🔥4👍2

30 Jul 2026, 19:12 UTC282 viewsread 8 August 2026
Photo

Внимательно читаем мелкие примечания... Лучший способ контроля расходов - это платить за токены, а не за подписку) Я к этому еще не пришел, но внимательно изучаю. Вот например, что вы видите на скрине выше? там всего один лишний нолик в оплате за кеш, подумаешь. Но по факту у остальных провайдеров даже со скидкой 62% - цена кеша в 15 (!!!) раз выше, чем у самого дипсика на сайте. А в кодинге это 95% трат токенов, то

28 Jul 2026, 10:51 UTC262 views4 reactionsread 8 August 2026
Forwarded from @pastukhov_blog

Some Simple Economics of AGI - на удивление проницательная статья по тематике ИИ от людей с экономическим образованием. В этом и есть ее ценность: авторы смогли увидеть за технологиями реальность будущего. И в этом светлом будущем вопрос уже будет отнюдь не в технологиях, а именно в тех областях, где технологии не справятся "из коробки". Основная идея статьи - в том, что проблема уже отнюдь не в генерации (она стала

🤡4

26 Jul 2026, 15:18 UTC814 views5 reactionsread 8 August 2026
Photo

Awesome Liveinternet Stats Если кто помнит, я давно делал скрипт-дашборд личартс для просмотра статистики нескольких сайтов на одной странице, подгружающий данные с LiveInternet аналитики. И вот долгожданная реинкарнация для 3.5 олдфагов) На этот раз я пошел с другой стороны, вместо скрипта который надо где-то размещать, закрывать паролем, добавлять сайты, дублировать функционал - я сделал расширение для хрома, кот

💊5

26 Jul 2026, 09:42 UTC334 viewsread 8 August 2026
File

Анализ данных стал как никогда прост) Глядя на табличку опенроутовских моделей - захотелось узнать, а сколько там реально тратится в деньгах, а не в токенах. Табличку парсить моветон, залез в консоль - разумеется там в источниках json на 3мб (а вы думали почему страница столько грузится… без впна не покажет) Скормил её дипсику - там не только данные по ценам и траты токенов, но еще и распределение токенов (можно вы

25 Jul 2026, 17:29 UTC265 views1 reactionsread 8 August 2026

Человеческий фактор в вайбкодинге Не совсем очевидный для меня вывод, но таки менеджерские скиллы архиважны при агентском программировании, что подтверждают техлиды/CTO, которые этим занимаются. Для них воркфлоу с внедрением LLM почти не меняются (в личной разработке), только сами инструменты, а так все как и везде в менеджерских тасках - если без ТЗ, то результат ХЗ. То есть вот какими способами приличный тимлид ил

👏1

25 Jul 2026, 17:29 UTC284 viewsread 8 August 2026

Из забавного - попросил выписать базовые штуки в контекст, где описание проекта, доступы, особенности и прочее, думал вот я какой умный. После сжатия сессии - видно, что не прочитал контекст. Спрашиваю какого хрена - я не я, корова не моя, не читал, не было в агенте. Окей, пропиши в агенте, что первым делом читать контекст. Будет ли модель его читать при сжатии сессии - насяльника я не знаю, при открытии новой сессии

Showing the 12 most recent of 19 posts we hold for @llmkungfu. 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.

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.

24 Jul 2026, 12:05 UTCAnonymous Poll3,290 voters approx.

Мой основной инструмент для AI coding это...

  1. ничем не пользуюсь2%
  2. Codex37%
  3. Claude Code37%
  4. Github Copilot1%
  5. Opencode7%
  6. Cursor8%
  7. chatgpt/claude/deepseek (копирую из чата в IDE и обратно)3%
  8. другое (напишу в комменты)5%

Shares as published. No per-option vote count is published by Telegram, so none is 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 19 most recent posts we hold, published 22 July 2026 to 7 August 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.

Citation-graph rank

Citation-graph rank — 422,089 of 1,481,306entries 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 2 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 16 August 2026 — this entry's latest reading, not the date you are reading this.

“LLM Кунг-фу 🥋” (@llmkungfu), 215 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/llmkungfu.

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.