6 measurements spanning 10 days, net +4. 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 999–1,007 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
16 Aug 2026, 17:06
1,004
-2
13 Aug 2026, 07:26
1,006
+4
10 Aug 2026, 13:04
1,002
+1
7 Aug 2026, 17:58
1,001
+1
6 Aug 2026, 20:46
1,000
no change
6 Aug 2026, 20:34
1,000
first reading
Engagement
20 posts held, back to 23 October 2025 — 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 12 July 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
382 reactions across 17 posts, in 15 distinct kinds. The most used accounts for 29.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
113
29.6%
❤
109
28.5%
👍
90
23.6%
🫡
19
4.97%
🗿
18
4.71%
💯
16
4.19%
🦄
5
1.31%
🕊
3
0.785%
🙈
3
0.785%
❤🔥
1
0.262%
🆒
1
0.262%
🎅
1
0.262%
🐳
1
0.262%
👎
1
0.262%
🙏
1
0.262%
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 17 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 382reactions 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 23 October 2025 to 12 July 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
17
across the posts below
Posts paid on
7
of 18 we hold a reading for · 39%
Most on one post
11
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @gulyaev_it. 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 23 October 2025 to 12 July 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.
Я думал, что проблема в дисциплине 🤔
Не так давно начал делать собственную систему геймификации жизни. Думал, что проблема моей продуктивности в visibility задач, фокусе на рутине и отсутствии ощущения прогресса. Хотел собрать систему, которая сама будет постоянно подталкивать меня двигаться вперед.
Сделал MVP, расписал задачи на неделю... и снова выполнил только обязательное. Созвоны, работа, ученики — без вопросо…
Менторство В С Ё? 💧
Слышу это из каждого чата и от каждого знакомого. Согласен с тем, что поиск работы усложняется, поэтому помощь ментора для трудоустройства становится более ценной.
Рынок меняется, становится сложнее вкатываться в IT, особенно, для 20-летних ребят без университета. С опытом работу искать проще, но без понимания того, как себя подавать, как проходить собесы — можно надолго зависнуть с поиском рабо…
Как все успевать | Часть 1
Больше месяца не писал и не выкладывал новые видео.
Регулярность - это вообще сложная штука.
Думаю, у каждого есть список вещей, которые нужно делать регулярно:
— Спорт
— Работа
— Учеба
— Уборка
— Режим по сну и питанию
Но почему так часто мы не делаем то, что нам так нужно? Почему мы можем все выходные смотреть ютуб или тик-токи, а не делать те дела, на которые на неделе у нас не хвата…
Все типы лайвкодинга | Мок-собеседование
С каждым годом растет планка hard-skills, которые достаточны для прохождения собеседования. В этом году уже на 70+ процентов интервью так или иначе спрашивают код:
- Код-ревью или чтение кода
- Рефакторинг фичи/экрана/сетевого слоя
- Лайвкодинг задачи/компонента/фичи
Гайд на лайвкодинг остается актуальным
Вместе с @mobile_cappuccino записал мок-собеседование по лайвкодин…
Лучшие промпты | Практика 👽
Тут рассказывал про искусство промптинга и прикладывал классные промпты. Получил бурную реакцию и захотел пойти дальше - собрать видео, где на практике показываю как промпты влияют на ответы LLM на примере ChatGPT 5.2
Задачки собрал разнообразные: от логики и креатива до плана внедрения привычек и подготовки к собесам
https://youtu.be/_SkdjxfHEqk
https://youtu.be/_SkdjxfHEqk
https://you…
Итоги разбора ситуаций на рынке
Созвон прошел продуктивно. Направил ~8 человек, многие кейсы пересекались, обсудили:
- Поиск работы в РБ
- Перекат с фронтенда на android
- Вкат в iOS после пет-проекта
- Проблема прохождения собеседований
- Проблему получения оффера для опытных разработчиков
Уверен, что следующие кейсы могут постепенно набираться, поэтому чтобы не ожидать следующего созвона, рекомендую писать в чат …
Напоминаю, что уже завтра в 16:00 по мск пройдет разбор ваших ситуаций на рынке
На трансляции разберем проблемы прохождения техничек, способы получения собеседований, а также можно ли вкатиться в IT без накрутки опыта.
Созвон продлится час, успеем разобрать 5-6 случаев, так что если хотел получить ответы на свои вопросы от меня - это последний шанс
https://forms.gle/xvSGH4EivH4MWEVh9
🏃♂️ Разбор твоей ситуации с поиском работы
Я проводил опрос ситуации на рынке и увидел следующее:
У 70% проблема с приглашением на собес
У 30% проблема с прохождением технической секции и финальной секции
Хочу системно разобрать проблемы, чтобы на примере показать путь к желаемому офферу
📈 Чтобы я ознакомился с твоей ситуацией, а также разобрал ее на эфире, заполни форму.
Участие добровольное
https://forms.gle/X…
⌛️ 2 месяца до бума вакансий
Только за последнюю неделю мы получили 20+ вакансий на Android.
Рынок начинает разгоняться — и это только старт.
В ближайшие 1–2 месяца:
— выплачиваются новогодние премии
— проходят зимние performance review
— часть сильных специалистов уходит из компаний по собственному желанию или из-за оптимизаций
🤔 Эти люди тоже выходят на рынок.
А значит: конкуренция резко вырастет.
Да, вакансий …
❤9👍7🔥4🎅1🙏1
Showing the 12 most recent of 20 posts we hold for @gulyaev_it. 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.
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.
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 20 most recent posts we hold, published 23 October 2025 to 12 July 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 — 1,089,471 of 1,480,975entries 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.
Mentions
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.
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.
“IT crew | Антон Гуляев 🤖” (@gulyaev_it), 1,004 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/gulyaev_it.
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.