Technology — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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.
Growth
24 measurements spanning 87 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 7,081–7,240 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 24
Measured (UTC)
Subscribers
Change
2 Nov 2026, 08:47
7,105
+6
29 Oct 2026, 23:56
7,099
-1
27 Oct 2026, 00:54
7,100
-9
23 Oct 2026, 22:49
7,109
-21
20 Oct 2026, 18:46
7,130
-5
18 Oct 2026, 03:30
7,135
+3
14 Oct 2026, 20:01
7,132
+1
11 Oct 2026, 14:19
7,131
-7
5 Oct 2026, 11:15
7,138
-19
27 Sept 2026, 16:21
7,157
+11
18 Sept 2026, 06:38
7,146
+5
13 Sept 2026, 19:59
7,141
+5
10 Sept 2026, 00:58
7,136
-14
4 Sept 2026, 18:58
7,150
-22
1 Sept 2026, 13:03
7,172
-7
29 Aug 2026, 08:27
7,179
-7
26 Aug 2026, 14:33
7,186
-6
23 Aug 2026, 08:08
7,192
-6
19 Aug 2026, 10:48
7,198
-3
16 Aug 2026, 20:49
7,201
first reading
Engagement
25 posts held, back to 20 May 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 13 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
18.2%
avg views ÷ 7,105 subscribers
Avg views / post
1,290
1 post measured
Reaction rate
0.698%
reactions ÷ views · ER floor
Posts in window
1
of 25 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 22 October 2026
Posts held
25 (20 May 2026 – 22 October 2026)
Views total
1,290
Reactions total
9
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Nov 2026, 13:43 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
237
Videos
105
Links
101
Lifetime counters from Telegram’s own channel header, read 3 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
5m 58s
Average length
33s
Measured directly from 11 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
815 reactions across 25 posts, in 12 distinct kinds. The most used accounts for 63.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
517
63.4%
👍
134
16.4%
⚡
34
4.17%
🤯
33
4.05%
😁
27
3.31%
👾
21
2.58%
👏
20
2.45%
🥰
8
0.982%
🍌
7
0.859%
👎
7
0.859%
😱
5
0.613%
🤔
2
0.245%
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 25 of the 25 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 815 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 25 most recent posts we hold, published 20 May 2026 to 22 October 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.
🛠 Могу ли я завайбкодить ЭТО?
Есть сайт, название которого и есть вопрос:
→ canivibecodeit.com
Внутри около 1100 платных сервисов. У каждого вердикт: YES / KINDA / NOT REALLY, то есть заменит ли его приложение, написанное нейросетью. И готовый промпт, чтобы попробовать самому
Это не реверс-инжиниринг, но как карта «за что больше не стоит платить подписку» работает отлично. Выше всех в рейтинге по голосам тех, кто…
🐺 Seedance 2.5 делает такие мультики?!
Для такого ролика в духе классической мультипликационной погони я составил промпт для Seedance 2.5. Главное здесь — задать не только внешний вид, но и последовательность событий: рисунок, побег птицы, реакция койота и финальный удар.
Вот промпт для этого видео 👀
Create a 30-second cinematic slapstick cartoon with photorealistic animals, 16:9. Setting: a sunlit desert canyon …
🎨 99 команд для картинок в ChatGPT
Сложный промпт писать не обязательно: допишите к запросу короткий тег, и модель сразу поймёт нужный стиль, свет или ракурс. Теги можно комбинировать 👇
кот в кофейне /cinematic /goldenhour /bokeh
Я проверил большинство — работают отлично. Сохраняйте 📌
📸 Качество
/4k — детализация 4K
/8k — сверхдетализация
/hdreal — усиленный фотореализм
/ultrarealistic — максимальный реализм
/cin…
⚡️GPT-6 Astra — это безумие.
Мы давно вышли за рамки статических моделей. Теперь ИИ создает живые миры в коде. В этой демо нет «файлов 3D-моделей». Оба поезда генерируются во время выполнения из кода Codex. использованием размеров, профилей и функций геометрии. Движение колёс и анимации взрыва/сборки также полностью управляются кодом. Работает невероятно плавно прямо в браузере.
Наблюдается всплеск жалоб на работу ряда популярных нейросетей, в том числе от Google, OpenAI и Anthropic.
Информации о причинах сбоев нет 🫠
У меня тупит Claude, а сайт ChatGPT вообще не открывался
🎙️ Стрим: настраиваем Hermes Agent с нуля
Без теории — открываем чистую машину и доводим агента до рабочего состояния в прямом эфире.
Ссылка: https://www.youtube.com/watch?v=pdSDWaa5-BA
👕 Примерил одежду с маркетплейсов прямо на себе — показал на видео
Затестил расширение Anywear (Live Virtual Try-On) для Chrome. Идея простая: загружаешь своё фото → выбираешь товар на маркетплейсе → ИИ «надевает» вещь на тебя.
Прогнал по разным площадкам — лучше всего сработало с Яндекс Маркетом: подхватывает карточки, примерка выглядит адекватно, видно как реально сидит вещь
У ребят есть открытый API на опенроут…
Красивые UI-компоненты для вайбкодинга — просто копируешь и вставляешь. Сохрани 👇
→ canvasui.dev — WebGL-эффекты поверх живого HTML
→ beam.jakubantalik.com — анимированный луч света для рамок
→ originkit.dev — бесплатная библиотека анимированных компонентов
→ aicss.dev — UI-компоненты для чатов с ИИ-агентами
→ transitions.dev — переходы для веб-приложений
→ metal.jakubantalik.com — эффект жидкого металла для кнопок
…
🖤 Собрал 3 скилла, которые лечат AI от «одинакового дизайна»
Вы наверняка замечали: попросишь Claude накидать интерфейс - и на выходе одинаковые градиенты, одинаковые шрифты, одинаковые вложенные карточки. Это называют «AI slop» - генерик-дизайн, который штампует любая модель
👇
🌕 Impeccable
Автор: Paul Bakaus (экс-Google)
Не просто набор правил, а целая дизайн-система: 1 скилл, 20 команд, куратированные антипат…
🔁 Промпт — это одноразовая команда. Loop — это цикл, который гоняет агента до результата
Нашел сайт loops.elorm.xyz — библиотека готовых лупов для Cursor, Claude Code, Codex. Штука простая до неприличия, но меняет то, как ты работаешь с агентом
🎯 В чем суть
Обычно как: пишешь промпт → агент делает → ты смотришь → говоришь «не работает, чини» → снова смотришь. И так по кругу руками. Ты сам являешься циклом
Луп уб…
🔥16⚡14👾7
Showing the 12 most recent of 25 posts we hold for @andreiaiai. 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.
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 2 November 2026 — this
entry's latest reading, not the date you are reading this.
“АндреИИч” (@andreiaiai), 7,105 subscribers as measured 2 November 2026. Telegram Register, tgregister.com/channel/andreiaiai.
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.