Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 13 September 2026 and assigned it the closest of 31 fixed categories, at 94% 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 why it has no browse page of its own yet.
Growth
14 measurements spanning 44 days, net -117. 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 3,968–4,844 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
18 Sept 2026, 23:00
4,069
-15
14 Sept 2026, 05:01
4,084
-62
10 Sept 2026, 15:01
4,146
-72
5 Sept 2026, 11:15
4,218
-80
1 Sept 2026, 19:08
4,298
-35
29 Aug 2026, 23:07
4,333
-111
26 Aug 2026, 22:58
4,444
-81
23 Aug 2026, 20:38
4,525
+2
19 Aug 2026, 19:34
4,523
+14
16 Aug 2026, 17:06
4,509
-141
12 Aug 2026, 22:33
4,650
-93
9 Aug 2026, 15:11
4,743
+491
6 Aug 2026, 13:22
4,252
+66
6 Aug 2026, 05:07
4,186
first reading
Engagement
10 posts held, back to 22 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 6 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 10 posts for this entry, the most recent from 11 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
49s
Average length
25s
Measured directly from 2 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
223 reactions across 8 posts, in 9 distinct kinds. The most used accounts for 61.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
136
61.0%
🔥
35
15.7%
👍
17
7.62%
🥰
15
6.73%
❤🔥
9
4.04%
😍
6
2.69%
💘
2
0.897%
🤔
2
0.897%
🦄
1
0.448%
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 10 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 289 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 10 most recent posts we hold, published 22 July 2026 to 11 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
6
across the posts below
Posts paid on
1
of 10 we hold a reading for · 10%
Most on one post
6
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @academypoetti. 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 10 most recent posts we hold for this entry, published 22 July 2026 to 11 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.
Когда, если не в августе?
Наступил идеальный период, чтобы выжать из арбузного сезона максимум! Мы соединили главный продукт этого месяца с любимым кофейным хитом.
Встречайте арбузный эспрессо-тоник 🍉
Как приготовить:
1. Отделите мякоть арбуза от кожуры и удалите косточки. Нарежьте его небольшими кусочками.
2. Переложите их в блендер и взбейте до однородной консистенции. Если хотите получить более нежную текстуру, …
Сегодняшний пост для тех, кто никогда не может выбрать между чаем и кофе! 🙋
Каскара в переводе с испанского означает «шелуха» или «кожура». Это высушенная мякоть кофейной ягоды, которая остается после извлечения самого зерна.
🍵 Каскару используют как естественное удобрение на плантациях, но у неё есть и гастрономическая ценность. Из-за способа приготовления её часто называют «кофейным чаем» — заваривают горячей вод…
Кофе давно перестал быть просто продуктом — сегодня это культура, наука и искусство. Но как мы к этому пришли? ✨📖
В новом выпуске подкаста Poetti раскрываем секреты «кофейных волн». Вместе с нашим экспертом Галиной Белоусовой обсуждаем, как менялись наши вкусовые привычки и как кофейни завоевали мир.
Слушайте по ссылке! 🎧
Подписывайтесь на «Кофе без фильтров» в МАКС | ВКонтакте | Telegram
Сладкий, как летний день 🐝
Заменили привычные топпинги на натуральный мёд и создали освежающий напиток с потрясающей кремовой шапкой из эспрессо и сливок.
Как приготовить:
1. В низкий стакан добавьте 15 г мёда. Влейте немного воды и тщательно перемешайте, чтобы мёд полностью растворился.
2. Наполните стакан льдом.
3. В отдельной высокой ёмкости соедините сливки, оставшиеся 10 г мёда и двойной эспрессо. Для этого ре…
Работа бариста — это ещё и серьезные тренировки вкусовых рецепторов! ☕️
Мы активно готовимся к ежегодным слепым тестам. На днях наша команда проводила дегустацию: главным героем дня стал продукт Soul of Rome, а ключевой целью — точная калибровка рецепторов всех бариста Poetti.
Калибровка — это сложный процесс, когда вся команда должна прийти к единому пониманию оттенков вкуса, плотности и аромата 🤌
Под конец встре…
Перед тем как лето передаст эстафету осени, успейте наполнить август новыми впечатлениями, знаниями и, конечно, хорошим кофе ☕️✨
Сохраняйте расписание и выбирайте мастер-класс, который давно хотели посетить:
8 августа — «Основы домашнего приготовления»
Начало в 12:00
11 августа — «Введение в кофе»
Начало в 11:00
13–14 августа — «Навыки бариста. Основы»
Начало в 11:00
15 августа — «Миксология* дома»
Начало в 12:0…
Из самого сердца кофейного мира — с любовью, вдохновением и твёрдыми стандартами!
Мы готовы подвести итоги нашей большой рабочей поездки в Бразилию 🌍✨
Наша команда провела десятки часов за дегустационными столами, изучила передовые технологии производства и наладила прямые контакты с лучшими фермерами, чтобы на 100% быть уверенными в качестве нашего продукта.
Читайте нашу новую статью! Там мы поделились главными о…
Кофе и вишня — союз, созданный для летних дней 🍒🧊
Предлагаем приготовить вишнёвый бамбл! В одном бокале мы объединили насыщенный двойной эспрессо и сочную кислинку вишнёвого сока. Напиток удивляет эффектным видом ещё до первого глотка, а затем полностью покоряет своим плотным ягодным вкусом.
Заглядывайте на наш сайт: там мы делимся видео с пошаговым процессом приготовления!
Подписывайтесь на «Кофе без фильтров» в …
Есть отличные новости!
Наш бренд-бариста, визионер и ведущий тренер Академии Poetti Александр Абдуллаев принимает вызов и участвует во Всероссийском чемпионате бариста «Золотое сечение» 🏆
И вы можете присоединиться к нему на этом празднике вкуса! 😍
Участие — это классная возможность выиграть гастротур по мишленовским ресторанам Юго-Восточной Азии и выйти на новый уровень мастерства. Здесь вы получите живую обратную…
Showing the 10 most recent of 10 posts we hold for @academypoetti. 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.
Mentions
Named by 5 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Елена Ландэ @elenalande_chef · 71,491 Telegram ranks this channel #19 of 83 here — alongside 82 others — read 20 August 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Кофе без фильтров” (@academypoetti), 4,069 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/academypoetti.
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.