Posted without readable text
Signed Katerina Petrova

Channel
@podlodkanews
On this record: Growth · Engagement · What this channel posts · Reactions · Advertising · Posts · Citations · Cite this entry
7,240subscribers
-7 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001383563818 |
|---|---|
| Type | Channel |
| Username | @podlodkanews |
| Created | 9 December 2017 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 16 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 16 August 2026 |
| On Telegram | t.me/podlodkanews |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 16 Aug 2026, 08:35 | 7,240 | -4 |
| 12 Aug 2026, 09:13 | 7,244 | +1 |
| 9 Aug 2026, 17:22 | 7,243 | -4 |
| 6 Aug 2026, 03:16 | 7,247 | no change |
| 6 Aug 2026, 02:03 | 7,247 | first reading |
25 posts held, back to 19 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 10 pagesof 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. It is computed over the 7 of 8 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 11 August 2026 |
|---|---|
| Posts held | 25 (19 May 2026 – 11 August 2026) |
| Views total | 13,323 |
| Reactions total | 154 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 02:13 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.
768 reactions across 24 posts, in 25 distinct kinds. The most used accounts for 19.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🤡 | 147 | 19.1% | |
| ❤ | 146 | 19.0% | |
| 🔥 | 138 | 18.0% | |
| 👍 | 109 | 14.2% | |
| ❤🔥 | 43 | 5.60% | |
| 💊 | 38 | 4.95% | |
| 💅 | 34 | 4.43% | |
| 😁 | 33 | 4.30% | |
| 🥴 | 32 | 4.17% | |
| 🤣 | 19 | 2.47% | |
| 👎 | 6 | 0.781% | |
| 🦄 | 4 | 0.521% | |
| 👀 | 2 | 0.26% | |
| 🕊 | 2 | 0.26% | |
| 😍 | 2 | 0.26% | |
| 🤔 | 2 | 0.26% | |
| 🤝 | 2 | 0.26% | |
| 🤩 | 2 | 0.26% | |
| 👏 | 1 | 0.13% | |
| 👨💻 | 1 | 0.13% | |
| 5 further kinds | 5 | 0.651% |
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 24 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 768reactions 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 19 May 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.
An ad marker, not a judgement about a post. A post is counted here because it carries one of two explicit markings: an erid token, which Russian law has required on paid placements since 2022 and which is issued against a specific advertising contract, or a #реклама / #ad hashtag in the body, which is the channel declaring it itself. The first is documentary; the second is a self-declaration and is weaker. No classifier reads the text and decides — nothing on this site guesses that a post is an advertisement.
This is a floor, and it can only ever be a floor.A channel that runs paid placements without marking them produces no marker for us to count, and an unmarked ad is indistinguishable from an ordinary post on the public surface. The ad load above therefore means “the share of posts that declared themselves”, never “the share of posts that were paid for”. A low figure is not evidence of a channel that runs few ads.
Both figures are medians, and no ratio between them is published. Each is a view reading that actually occurred on a post, picked by percentile_disc rather than averaged, so one viral post cannot move it and no interpolated value is invented between two readings. They are printed side by side with the count behind each rather than as a ratio: an ad and an ordinary post are not otherwise matched — for topic, for length, for hour of day — so the gap between them is a description of two groups and not the effect of one being an ad.
| erid | Posts | First seen | Last seen |
|---|---|---|---|
| 2SDnjbocFa3 | 1 | 14 July 2026 | 14 July 2026 |
| 2SDnjcXQjbR | 1 | 11 August 2026 | 11 August 2026 |
| 2SDnjdBhcfd | 1 | 27 July 2026 | 27 July 2026 |
| 2SDnjdbfsR5 | 1 | 3 August 2026 | 3 August 2026 |
| 2SDnjeJxBbg | 1 | 11 June 2026 | 11 June 2026 |
A token repeated across several posts is one advertising contract placed more than once, which is what the identifier is for. The strings are reproduced exactly as they appeared in the post or in its click-through URL and are not validated against any registry — we record the marker a channel published, and whether it resolves to a real contract is a question for the register that issued it.
Measured over the 25 most recent posts we hold, published 19 May 2026 to 11 August 2026. Views are the latest single reading held for each post, and any reading at or above 1,000 is rounded by Telegram to three significant figures.
Posted without readable text
Signed Katerina Petrova
Внимание, внимание, это теоретически-гипотетический опрос, никого ни к чему не обязывающий и никому ничегошеньки не обещающий! (Пока что 😅) 🤖 Представьте, что мы стали бы чаще выпускать AI-специфичные выпуски. Примеры тем: • Автономные фабрики фичей • Как AI меняет структуру команд • Как строить внутреннюю агентскую платформу (эфемерные окружения, менеджмент доступов и вот это все) • Как разрабатывать сложные легас…
🥴32🤩2
Signed Katerina Petrova
Бреслав и Ложечкин #40 — Типология мышек и ёжиков Обсудили разные "типологии личности", вроде MBTI, Hogan, Big 5, Culture Map. Что в них есть научного и антинаучного? И насколько они могут быть полезны (даже антинаучные)? Как их правильно применять для себя и для своих команд. Партнёр команды Podlodka — наши давние друзья @AvitoTech. Это команда с крутыми процессами, культурой здравого смысла и эксперимента. Узнать…
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Podlodka #489 – Laravel Laravel любят за скорость разработки, ругают за магию и регулярно обвиняют в том, что он плодит жирные контроллеры. Вместе с Аделем Файзрахмановым – автором плагина Laravel Idea для PhpStorm и книги «Архитектура сложных веб-приложений. С примерами на Laravel» – разбираемся, что именно делает этот фреймворк лучшим на сегодняшний день способом писать код на PHP. 🎧 Слушать выпуск 👀 Смотреть в…
🔥7❤3👍3
На следующей неделе пишем выпуск про то, что сейчас происходит со студиями разработки – как AI повлиял на востребованность аутсорса, за что вообще платят клиенты, как изменились предпочтения по платформам и технологиям, и как сейчас строятся команды и процессы внутри. Накидайте ваших интересных вопросов, будем обсуждать!
🔥21👎1😁1
Signed Egor Tolstoy
Podlodka #488 – UX-ресерч в эпоху AI Когда вообще стоит проводить UX-исследование? А когда оно только тратит время и деньги? В этом выпуске разбираемся, в каких случаях ответ уже можно найти в аналитике или саппорте, когда проблема и так очевидна, а когда ещё слишком рано что-либо исследовать, потому что даже гипотезы решения нет. В гостях – Георгий Крутоус, руководитель UX Research в Muse Group (Ultimate Guitar, M…
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Podlodka #487 – Elixir Elixir часто воспринимают как более дружелюбный синтаксис поверх Erlang, но достаточно ли такого объяснения в 2026 году? Вместе с Данилой Поярковым, разработчиком более 50 open source проектов для Elixir с суммарно около миллиона скачиваний, разбираемся, что язык унаследовал от Erlang и BEAM, где его используют сегодня и насколько зрелой стала его экосистема. Обсуждаем Phoenix и LiveView, мет…
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Podlodka #486 – Spec-Driven Development В разработке с агентами нам больше всего не хватает контроля за результатом и уверенности в нем. Один из способов их получить – использовать подход Spec-Driven Development, в котором перед тем, как отправить агента писать код, мы готовим ему понятное описание задачи и с продуктовой, и с архитектурной стороны. Вместе с Алексеем Верховским, мейнтейнером фреймворка BMAD, мы разби…
🔥20❤5👍2❤🔥1👎1
Егор Толстой – ведущий подкаста Podlodka и человек, прошедший за 7 лет путь от руководителя кластера в Avito до первого продакта Kotlin и VP по продукту в JetBrains. Правда, затем выгорел, думал уйти в саббатикал, но обнаружил, что не работать тоже надо уметь, и вернулся руководителем продукта в AI-стартап CodeSpeak. Поговорили о том, чем продакт языка программирования отличается от обычного продакта, почему Егор пр…
🤡37❤17🔥7❤🔥6👍1👎1
Тем временем один ведущий Подлодки (Егор) сходил в гости в подкаст к другому ведущему (Андрею) и рассказал о своей новой работе, самой Подлодке и проектах, которые успели из неё вырасти, а также о том, что нас всех ждёт в мире с AI.
🤡14👍2😍2👎1🔥1
Бреслав и Ложечкин #39 — Зачем писать себе некролог Обсудили в выпуске, зачем писать самому себе некролог и как это связано с практикой Amazon Working Backwards. Если серьёзно - обсудили, как можно относиться к себе, как к продукту, как с помощью LLM сделать себе нормальный план развития и как агентов использовать для того, чтобы самому себе помогать по этому плану идти. Партнёр команды Podlodka — наши давние друзь…
💊38❤🔥5👍4❤2
Podlodka #485 – Терминалы В мире пользовательских интерфейсов каждый год происходят эволюции, а иногда и революции. Терминалы тем временем уже десятки лет как будто бы застыли во времени. Концептуально мало что поменялось, но баззвордов стало много: bash, zsh, tty, GPU acceleration в конце концов. А с приходом AI выросла популярность CLI-тулов, благодаря чему терминалы переживают ренессанс. Так что же там происходит…
❤🔥15👍3🕊2🤝2🔥1🤔1
Showing the 12 most recent of 25 posts we hold for @podlodkanews. 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.
Citation-graph rank — 22,334 of 1,481,306entries 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.
Republishes
Channels on the register whose posts this channel has forwarded.
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 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.
Names
Channels on the register whose handles appear in this channel's posts.
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 16 August 2026 — this entry's latest reading, not the date you are reading this.
“Podlodka Podcast – анонсы и новости подкаста про IT” (@podlodkanews), 7,240 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/podlodkanews.
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.