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Channel

Гриненко про ИИ, бизнес и образование

@devspotting

On this record: Growth · Engagement · Reactions · Advertising · Posts · Citations · Cite this entry

3,069subscribers

+97 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001200168356
TypeChannel
Username@devspotting
CreatedBetween 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/devspotting

Growth

2,9723,0693,020.56 August 2026 — 2,972 subscribers6 August 2026 — 2,972 subscribers9 August 2026 — 3,063 subscribers13 August 2026 — 3,069 subscribers6 August 202613 August 2026
4 measurements spanning 7 days, net +97. 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 2,957–3,084 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 03:153,069+6
9 Aug 2026, 18:413,063+91
6 Aug 2026, 05:022,972no change
6 Aug 2026, 02:472,972first reading

Engagement

12 posts held, back to 26 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
32.7%
avg views ÷ 3,069 subscribers
Avg views / post
1,000
5 posts measured
Reaction rate
1.49%
reactions ÷ views · ER floor
Posts in window
5
of 12 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
WindowRolling 30 days · latest post in window 5 August 2026
Posts held12 (26 June 20265 August 2026)
Views total5,018
Reactions total75
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 00:15 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.

Reaction mix

201 reactions across 12 posts, in 8 distinct kinds. The most used accounts for 37.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥7637.8%
👍7537.3%
3115.4%
😁83.98%
🎉41.99%
💩31.49%
🙏31.49%
😱10.498%

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 12 of the 12 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 201reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 12 most recent posts we hold, published 26 June 2026 to 5 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.

Advertising

Ad load
16.7%
2 of 12 posts carry an ad marker
Regulatory tokens
2
posts carrying an erid · 2 distinct tokens
Median views · ads
458
over 2 measured posts
Median views · rest
1,200
over 10 measured posts

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. The sample on one side is under five posts, which is too thin to compare. The two figures are shown side by side with the count behind each, and deliberately not divided into a headline like “ads get x% fewer views” — an arithmetic that is easy to print and, at this sample size, means nothing.

Advertising tokens recorded on this entry
eridPostsFirst seenLast seen
2VtzqxSCDM415 August 20265 August 2026
2VtzqxdTojx13 August 20263 August 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 12 most recent posts we hold, published 26 June 2026 to 5 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.

Recent posts

5 Aug 2026, 17:16 UTC458 views14 reactionsread 8 August 2026
Advertisementerid 2VtzqxSCDM4

#ГриненкоПро №20: Разработка AI-продуктов с Федей Морозовым — CTO ботов поддержки в Т-Банке Поговорили о том, как превратить недетерминированную LLM в продукт, которому можно доверить действия с реальными последствиями. Разобрали инженерный путь от классического чат-бота и точечных LLM-классификаторов до полноценной агентной системы: контроль качества, разметку, гардрейлы, A/B-эксперименты, контекст и инструменты.

👍8🔥4🎉2

3 Aug 2026, 05:01 UTC680 views12 reactionsread 8 August 2026
Advertisementerid 2VtzqxdTojxPhoto

Разворачиваем LLM в корпоративном контуре и подключаем агента на OpenClaw 6 августа в 16:00 команда VK Cloud проведет практический воркшоп. За 90 минут онлайн-кодинга развернем языковую модель на облачной GPU и подключим агента на OpenClaw — open-source фреймворке для LLM-агентов. Подойдет тем, кто работает с чувствительными данными, но не может использовать внешние API и загружать в сторонние сервисы документы по

👍7💩3🔥2

26 Jul 2026, 12:55 UTC≈1,200 views15 reactionsread 8 August 2026

#ГриненкоПро №19: AI-разработка в продакшне с Алексеем Ярошевичем, руководителем команды в Яндекс Банке и ex-CTO Яндекс Образования https://www.youtube.com/watch?v=AGTtnCMd-z8 Поговорили про накопление интуиции при работе с моделями, о том, что качество AI-разработки сильнее зависит от harness и контекста, чем от размера модели, про оркестрацию (Леша в нее не очень верит), узкие места SDLC и много всего еще — подро

👍9🔥41🎉1

21 Jul 2026, 16:12 UTC≈1,220 views12 reactionsread 8 August 2026

О чем спросить философа? Друзья, у меня в подкасте уже были CTO, арт-директор, продакт, психолог, коуч и, конечно, крутые разработчики и технические руководители. А совсем скоро будем снимать выпуск с самым настоящим философом. Так что если у вас есть вопросы — обязательно напишите в чате https://t.me/grinenko_pro/1885! @devspotting

👍72🔥2😁1

18 Jul 2026, 13:19 UTC≈1,460 views22 reactionsread 8 August 2026

#ГриненкоПро №18: Автотесты с ИИ-агентами с Дмитрием Андрияновым, руководителем команды в Яндекс 360 https://www.youtube.com/watch?v=EZXj-bTG82w Как покрыть legacy и не сломать продукт, может ли ИИ-агент написать автотесты не хуже человека — и как заметить момент, когда он просто подгоняет проверки под зелёный статус? Разбираем практический подход к тестированию с нейросетями: от продуктовых сценариев и legacy-кода

🔥115👍5🙏1

9 Jul 2026, 14:14 UTC≈1,450 views11 reactionsread 8 August 2026

#ГриненкоПро №17: ИИ-продукты, ИИ-работа и ИИ-карьера с Даниэлем Левинишниковым, руководителем AI-продуктов и автором замечательного канала @tldrdaniel https://www.youtube.com/watch?v=URTFgSBexzo Даниэль руководит продуктовым подразделением Т-Банка из 250 человек, а по выходным запускает нейро-пэт-проекты и пишет про GEO-оптимизацию на Хабр. Обсудили, как AI меняет продуктовую разработку, клиентскую поддержку и ст

👍5🔥32🎉1

7 Jul 2026, 07:57 UTC≈5,790 views21 reactionsread 8 August 2026

Браузерный AI-агент в Datalens В #ГриненкоПро №16 поговорили с Андреем Мелиховым, разработчиком Яндекс Облака и автором @melikhov_dev о его опыте создания AI-агента прямо в браузере: как он вызывает тулы, строит чарты, работает с данными, проверяет себя через eval harness и почему нельзя просто так взять и прикрутить LLM в продакшне. https://www.youtube.com/watch?v=chiexp7ncfg В выпуске: — почему готовых фреймворк

👍118🔥2

5 Jul 2026, 10:48 UTC≈1,070 views20 reactionsread 8 August 2026
Photo

Место для обсуждения этих наших нейронок Друзья, я открыл чат канала для всех. Хочу, чтобы в нем появилась жизнь и он превратился в место, где можно задавать вопросы, делиться находками, вместе придумывать, как правильно готовить агентов, и находить единомышленников. Давайте считать, что в чате работает бесконечная AMA-сессия: в любой момент можно спросить меня о чем угодно — про нейронки, AI-инструменты, агентов,

🔥143👍3

2 Jul 2026, 10:24 UTC≈1,220 views14 reactionsread 8 August 2026

ИИ ломает open source В #ГриненкоПро №15 обсуждаем, как LLM изменили жизнь мейнтейнеров с Никитой Пастуховым: автором FastStream (в топ-100 open source проектов 2023), мейнтейнером AG2 и человеком, который живёт внутри современного open source, AI-агентов и бесконечного потока сгенерированных pull request’ов. https://www.youtube.com/watch?v=tBgaOBnpZyg В выпуске: — open source как продукт, карьера и кошмар; — AG2,

👍8🔥42

29 Jun 2026, 11:40 UTC≈1,180 views13 reactionsread 8 August 2026

Субагенты не нужны? AI code review, токены и надёжность https://m.youtube.com/watch?v=Zf9rjUK1A2c Обсуждаем статью Антона Виноградова You don’t need sub-agents. Разбираемся, почему мультиагентная оркестрация не всегда ускоряет разработку, как субагенты множат контекст и токены, когда один агент оказывается быстрее и стабильнее, а когда параллельные агенты всё-таки нужны. В выпуске: — почему «оркестратор + толпа а

🔥9👍31

27 Jun 2026, 11:21 UTC≈1,090 views25 reactionsread 8 August 2026

Как не сойти с нейропаровоза, если я больше не вывожу? https://www.youtube.com/watch?v=h6Hh9OdJpvQ В выпуске #ГриненкоПро №13 говорим с Еленой «Мурсей» Джетпыспаевой @mursyamursya — коучем ICF, продуктовым менеджером в нидерландском финтехе и человеком, который прошёл через выгорание, несколько профессиональных трансформаций, Яндекс, Амстердам, Лондон и переезд в Барселону. Обсуждаем, почему нейросети, которые вро

🔥12👍54🙏2😁1😱1

26 Jun 2026, 13:12 UTC≈1,070 views22 reactionsread 8 August 2026
Photo

В чем ты лучше ИИ? Еще с полей TeamLead Conf — стикеры участников. Умею свистеть Забивать Умею надувать пузыри из жвачки Бухаю. Смеюсь. Грущу. Болею Умею крутить сальто Лучше умею тревожиться Не жру токены Могу бить больно Могу покормить кота Готовлю сырники Могу написать симфонию (если подтянуть сольфеджио) Работаю даже при отключенном интернете Не теряю контекст во время работы Могу копать, могу не копать Могу ус

🔥9😁6👍43

Showing the 12 most recent of 12 posts we hold for @devspotting. 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

Citation-graph rank — 54,417 of 1,160,990entries 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.

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 6 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.

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 13 August 2026 — this entry's latest reading, not the date you are reading this.

“Гриненко про ИИ, бизнес и образование” (@devspotting), 3,069 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/devspotting.

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.