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Channel
@tugunx
On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry
30subscribers
-1 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002171415085 |
|---|---|
| Type | Channel |
| Username | @tugunx |
| Created | Between 1 June 2024 and 30 September 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 29 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 2 times, most recently 29 August 2026 |
| On Telegram | t.me/tugunx |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 22 Aug 2026, 17:47 | 30 | -1 |
| 11 Aug 2026, 03:00 | 31 | no change |
| 7 Aug 2026, 04:18 | 31 | first reading |
20 posts held, back to 19 March 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 pageof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 10 August 2026 |
|---|---|
| Posts held | 20 (19 March 2026 – 10 August 2026) |
| Views total | 58 |
| Reactions total | 15 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 11 Aug 2026, 03:00 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.
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.
90 reactions across 16 posts, in 11 distinct kinds. The most used accounts for 42.2% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 38 | 42.2% | |
| ⚡ | 11 | 12.2% | |
| ❤ | 8 | 8.89% | |
| 👏 | 7 | 7.78% | |
| 💯 | 7 | 7.78% | |
| 🏆 | 6 | 6.67% | |
| 👍 | 6 | 6.67% | |
| ❤🔥 | 4 | 4.44% | |
| 🎉 | 1 | 1.11% | |
| 👌 | 1 | 1.11% | |
| 👨💻 | 1 | 1.11% |
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 20 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 90reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 19 March 2026 to 10 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @tugunx. 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 20 most recent posts we hold for this entry, published 19 March 2026 to 10 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.
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На выходных немного откатился назад. Не в коде 🙂 А в истории TugunX. Открыл старые версии проекта, первые схемы, заметки и решения, которые когда-то казались правильными. Посмотрел, с чего мы вообще начинали и насколько далеко ушли от первоначальной идеи. Когда долго находишься внутри разработки, это не всегда замечаешь. Каждый день меняешь что-то небольшое, решаешь очередную проблему, переделываешь то, что вчера …
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Несколько недель назад AI Builder существовал только у нас в голове. Сегодня это уже рабочая часть TugunX. В этом видео показываю текущий прогресс. Сейчас AI Builder уже умеет: • анализировать описание процесса обычным языком; • постепенно формировать понимание процесса; • задавать уточняющие вопросы там, где действительно не хватает информации; • показывать своё понимание процесса ещё до построения автоматизации;…
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Я много писал о том, каким должен стать AI Builder в TugunX. О том, что пользователь должен описывать процесс обычным языком, а система понимать его логику, задавать уточняющие вопросы и только после этого строить автоматизацию. На скриншоте результат одного из последних тестов. Процесс согласования командировок был разобран, структурирован и превращён в полноценный Flow с ветвлениями, проверками, статусами и увед…
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Пока все обсуждают AI-агентов, мы решаем другую проблему. Я заметил интересную вещь во время разработки AI Builder. Оказалось, что заставить AI нарисовать красивую схему процесса - относительно просто. Гораздо сложнее научить его задавать правильные вопросы. Настоящий бизнес-аналитик не задаёт двадцать вопросов подряд: - Он постепенно строит понимание процесса. - Он уже не спрашивает то, что понял. - Не возвраща…
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В предыдущем посте я писал, что автоматизация начинается не с выбора CRM, ERP или AI. Сначала нужно понять сам процесс. Но здесь возникает следующий вопрос: А что будет, если человеку больше не придётся самостоятельно собирать автоматизацию по шагам? Сегодня большинство платформ работают одинаково. Пользователь уже должен знать: - с чего начинается процесс; - какие действия нужно выполнить; - где поставить услов…
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Очень много думаю о том, куда вообще движется рынок автоматизации. Ещё совсем недавно всё сводилось к одному: открываешь визуальный редактор, соединяешь между собой ноды, настраиваешь интеграции, получаешь автоматизацию. Сейчас всё чаще появляются AI-first платформы, где достаточно описать задачу обычным языком, а AI сам предлагает первый вариант рабочего процесса. И, честно говоря, мне кажется, что это абсолютно …
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За последнее время разработки TugunX я понял одну неприятную вещь. Практически каждый разговор об автоматизации начинается одинаково. - Нам нужна CRM. - Нужно внедрить ERP. - Давайте подключим AI. - Может, перейти на другую систему? И почти никогда не начинается с вопроса: А как вообще сейчас работает наш процесс? За последние несколько лет мне довелось работать с разными системами: SAP, Bitrix24, Excel, Telegram,…
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Теперь разбирать прогоны стало в разы проще Мы сильно прокачали execution-страницу и аналитику прогонов. Что изменили: - сделали правую панель заметно удобнее для разбора - добавили переключение по нодам прямо из схемы - теперь при клике показываются данные именно выбранной ноды - вынесли Input / Output / Meta в понятный формат для анализа - убрали лишний шум и дублирование - улучшили читабельность и компоновку, чт…
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Хочу немного свериться с вами по развитию TugunX 👀 Сейчас постепенно выходим на этап активного расширения интеграций внутри платформы. И здесь хочется идти не куда все идут, а туда, где это реально нужно в работе. Поэтому интересно узнать, какие 5 интеграций для вас были бы самыми полезными? Это может быть что угодно. Можно просто списком в комментариях. Будет очень полезно для определения следующих направлений …
Долго думал над тем, какая фича могла бы по-настоящему отличать TugunX от других сервисов автоматизации в части работы с данными и expressions. Почти во всех no-code платформах есть один общий момент: когда нужно что-то преобразовать, почистить, достать из массива или посчитать - пользователь быстро упирается в формулы, функции, синтаксис и технические нюансы. - Где-то это выглядит как набор функций. - Где-то как J…
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Showing the 12 most recent of 20 posts we hold for @tugunx. 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 — 485,073 of 1,627,445entries 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.
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.
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.
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 22 August 2026 — this entry's latest reading, not the date you are reading this.
“No-Code Startup: путь разработки” (@tugunx), 30 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/tugunx.
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.