Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 98% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear word for word on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (6 of the pairs behind the counts below)
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 14 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 21 comparable posts for this entry, running 19 June 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Across the whole group of 2, the earliest publisher we hold is @interra_ai. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_copy, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
26 measurements spanning 88 days, net -152. 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 7,753–7,951 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)
Subscribers
Change
3 Nov 2026, 03:07
7,776
-4
31 Oct 2026, 05:59
7,780
-5
28 Oct 2026, 15:17
7,785
-13
25 Oct 2026, 23:29
7,798
-5
23 Oct 2026, 10:09
7,803
-5
20 Oct 2026, 20:21
7,808
-6
17 Oct 2026, 15:37
7,814
-3
14 Oct 2026, 19:48
7,817
-5
11 Oct 2026, 12:20
7,822
-8
5 Oct 2026, 00:57
7,830
-19
26 Sept 2026, 09:37
7,849
-8
15 Sept 2026, 12:57
7,857
-5
11 Sept 2026, 17:37
7,862
-6
6 Sept 2026, 17:41
7,868
-5
2 Sept 2026, 07:35
7,873
-7
30 Aug 2026, 13:44
7,880
-3
27 Aug 2026, 19:27
7,883
-6
25 Aug 2026, 04:37
7,889
-5
22 Aug 2026, 11:55
7,894
-1
19 Aug 2026, 12:07
7,895
first reading
Engagement
63 posts held, back to 19 June 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 23 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.999%
avg views ÷ 7,776 subscribers
Avg views / post
77.7
21 posts measured
Reaction rate
0.94%
reactions ÷ views · ER floor
Posts in window
21
of 63 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 4 of 21 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 4 November 2026
Posts held
63 (19 June 2026 – 4 November 2026)
Views total
1,632
Reactions total
3
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
4 Nov 2026, 23:51 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
Photos
≈1,140
Videos
≈42
Links
≈407
Lifetime counters from Telegram’s own channel header, read 4 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Reaction mix
29 reactions across 20 posts, in 5 distinct kinds. The most used accounts for 55.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
16
55.2%
❤
8
27.6%
❤🔥
3
10.3%
👎
1
3.45%
💯
1
3.45%
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 63 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 29 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 63 most recent posts we hold, published 19 June 2026 to 4 November 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
Telegram’s own ‘edited’ marker: 0 of 21 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
А вы замечали: самые спокойные клиенты — те, у кого уже был плохой опыт с фрилансерами.
Они знают, чего хотят, и не торгуются. Не пишут в 23:00. Не меняют ТЗ на ходу.
Не потому что у них бездонный бюджет. А потому что они уже заплатили дороже: срывом сроков, переделками и нервным поиском нового исполнителя.
Такие клиенты ищут не «подешевле», а «понадёжнее». И для них ваш спокойный тон, чёткие сроки и понятный процесс…
ИИ как тренажёр для сложных разговоров: готовимся к обсуждению цены
🎭Разговор о цене пугает многих: заранее прокручиваешь в голове возражения, готовишь аргументы, а в момент встречи всё равно теряешься и соглашаешься на скидку. Дело не в слабой позиции, а в том, что к такому разговору почти никто не репетирует.
Нейросеть здесь работает как безопасный тренажёр. Её можно попросить сыграть клиента: торгующегося, сомнева…
Запускаем рубрику "Вопрос-ответ". Задавайте свои вопросы 👇
Нужно ли мне знать английский для вайбкодинга?
Нет. С современными инструментами можно работать на русском. Английский помогает читать документацию, но это не обязательное условие для старта.
Достаточно знать 5–10 базовых терминов (prompt, deploy, debug) — остальное подтянете в процессе (если будет нужно). А если встретите сложный текст, ИИ сам переведёт и о…
Дайджест недели: меньше тревоги, больше ясности
На этой неделе говорили о том, как спокойнее относиться к работе с ИИ: не бояться клиентов, не гнаться за каждой новинкой и выбирать инструменты под свои задачи. Собрали главное, чтобы не искать в ленте.
🤫 «Боюсь, что клиенты узнают, что я использую ИИ»
Откуда берётся стыд за работу с нейросетью, что делать, если клиент сбивает цену из-за ИИ, и как говорить об этом спок…
Как выбрать свой первый инструмент для вайбкодинга
🧰Один из самых частых стопоров на старте, звучит примерно так: «Инструментов много, а я не знаю, какой выбрать, и боюсь потратить время не на то». И сегодня мы постараемся этот момент сгладить: искать «лучший» инструмент не нужно. Выбор проще делать от задачи, а не от названия платформы.
Для начала ответьте себе на вопрос: что именно вы хотите получить в итоге?
🔹 Лен…
Парадокс ИИ: чем больше инструментов ты знаешь, тем меньше используешь.
🧰В прошлом посте мы говорили, что успеть за всеми новинками невозможно. У этой гонки есть любопытный итог.
На старте хочется попробовать всё: собираешь подборки, оформляешь подписки, тестируешь. А через пару месяцев смотришь на свой зоопарк из десяти сервисов и понимаешь: большую часть задач закрывают всего два-три. Остальное просто шум и переклю…
«Я должен всё знать»
Как учиться, когда новое выходит каждую неделю
📱Новая модель, новый инструмент, новая функция, которая «меняет всё». Лента полна заголовков, и вместе с ними приходит тихое ощущение: я не успеваю, все уже разобрались, а я безнадёжно отстаю. Знакомо?
Стоит сказать прямо: успеть за всем невозможно. Даже те, кто занимается ИИ профессионально, не пробуют каждую новинку. Они выбирают, что им нужно, и с…
3 фразы, которые выдают страх в переписке с клиентом:
«Если это выше вашего бюджета, давайте обсудим скидку»
➖ Вы торгуетесь с собой раньше, чем клиент возразил. Назовите цену и поставьте точку.
«Это, конечно, только моё мнение, но…»
➖ Зачем платить за решение, в которое исполнитель сам не верит? Пишите: «Рекомендую так, потому что [аргумент]».
«Мне несложно, могу посмотреть и в выходные»
➖ Сигнал, что ваше время нич…
«Боюсь, что клиенты узнают, что я использую ИИ»
🤫Этот страх редко обсуждают вслух, но он знаком многим. Сделал работу с помощью нейросети, и внутри неприятное ощущение, будто «сжульничал». А вдруг клиент узнает и решит, что платил зря? Или наоборот: узнает и начнёт сбивать цену под предлогом «ну это же всё делает ИИ».
Откуда это берётся? Из привычной логики, что настоящая работа это когда тяжело и долго, а если получ…
Дайджест недели: основа для работы на себя
На этой неделе говорили о том, из чего складывается спокойная и устойчивая работа: от сил и режима до договора, портфолио и первых собственных продуктов. Собрали главное, чтобы не искать в ленте.
🍂 Осенняя усталость на удалёнке: почему осенью всё идёт тяжелее
Почему в октябре сил меньше и какие мягкие практики помогают: утренний свет, прогулка как «дорога на работу», посильн…
Цифровой продукт из своей экспертизы: с чего проще начать
💡В прошлом посте мы показали три маленьких инструмента, которые маркетолог может собрать за вечер. Логичный следующий шаг: понять, что из своего опыта можно превратить в продукт, который работает без вас. Начинать для этого с большого курса совсем не обязательно.
Три простых формата:
🔹 Чек-лист
Один вечер. Собираете в короткий список то, что сами делаете по п…
Как собрать портфолио, если клиентов ещё не было
🔄Замкнутый круг, знакомый почти каждому новичку: клиенты просят примеры работ, примеров нет, потому что не было клиентов. Выглядит тупиком, но на деле портфолио не обязано состоять из заказов. Оно должно показывать, что вы умеете и как мыслите.
Вот из чего его можно собрать.
➖ Учебные проекты
Всё, что вы сделали в процессе обучения: лендинг, бот, автоматизация, контен…
Showing the 12 most recent of 63 posts we hold for @interrabz. 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.
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 3 November 2026 — this
entry's latest reading, not the date you are reading this.
“Interra | Школа профессий” (@interrabz), 7,776 subscribers as measured 3 November 2026. Telegram Register, tgregister.com/channel/interrabz.
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.