Мне платят за то, что я говорю другим людям что им делать.
Автор книги https://www.manning.com/books/machine-learning-system-design
https://venheads.io
https://www.linkedin.com/in/venheads
Created
7 December 2021 — measured — cross-checked against a third-party dataset (ext.tg_channel)
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 9 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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
36 measurements spanning 52 days, net +234. 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 30,508–30,871 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 36
Measured (UTC)
Subscribers
Change
26 Sept 2026, 19:22
30,808
-21
19 Sept 2026, 13:37
30,829
+7
17 Sept 2026, 03:57
30,822
+7
15 Sept 2026, 01:22
30,815
-7
13 Sept 2026, 09:19
30,822
+3
11 Sept 2026, 10:21
30,819
+6
8 Sept 2026, 15:38
30,813
-10
5 Sept 2026, 11:56
30,823
+18
3 Sept 2026, 11:01
30,805
+10
2 Sept 2026, 05:23
30,795
+6
1 Sept 2026, 04:02
30,789
+1
31 Aug 2026, 02:45
30,788
-7
30 Aug 2026, 02:15
30,795
-1
29 Aug 2026, 05:12
30,796
+4
28 Aug 2026, 06:43
30,792
+12
27 Aug 2026, 03:08
30,780
+8
26 Aug 2026, 00:57
30,772
+19
25 Aug 2026, 03:56
30,753
+25
23 Aug 2026, 22:45
30,728
-15
22 Aug 2026, 09:57
30,743
first reading
Engagement
31 posts held, back to 15 June 2026 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 79 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
45.2%
avg views ÷ 30,808 subscribers
Avg views / post
13,900
5 posts measured
Reaction rate
2.56%
reactions ÷ views · ER floor
Posts in window
5
of 31 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 24 September 2026
Posts held
31 (15 June 2026 – 24 September 2026)
Views total
69,610
Reactions total
1,782
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
26 Sept 2026, 13:51 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
232
Videos
9
Links
471
Lifetime counters from Telegram’s own channel header, read 27 September 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
55m 49s
Average length
27m 55s
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
8,244 reactions across 30 posts, in 43 distinct kinds. The most used accounts for 14.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
1,182
14.3%
💅
1,146
13.9%
😁
1,120
13.6%
👍
1,108
13.4%
🤡
1,098
13.3%
❤
647
7.85%
🖕
578
7.01%
💩
426
5.17%
🤣
299
3.63%
💊
147
1.78%
💯
124
1.50%
👎
78
0.946%
🤮
70
0.849%
✍
26
0.315%
🤯
26
0.315%
😱
24
0.291%
🌭
16
0.194%
🥴
13
0.158%
🦄
13
0.158%
❤🔥
12
0.146%
23 further kinds
91
1.10%
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 31 of the 31 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 8,273 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 31 most recent posts we hold, published 15 June 2026 to 24 September 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
1,628
across the posts below
Posts paid on
14
of 31 we hold a reading for · 45%
Most on one post
1,170
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @cryptovalerii. 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 31 most recent posts we hold for this entry, published 15 June 2026 to 24 September 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.
В последнее время все дружно делают корпоративных AI-агентов и постепенно приходят к замечательной мысли: чтобы модель делала работу, ей надо дать доступ к работе. А не только поле, куда работяга будет заботливо копировать содержимое остальных корпоративных систем.
OpenAI называют это переходом от assistance к execution. Microsoft развивает skills, коннекторы к корпоративным данным и взаимодействие агентов между соб…
Про важное поговорили, теперь можно про ML.
Сейчас читаю ML System Design (который уже неприлично разросся: 5 месяцев и 10+ часов контента только по агентским системам, а всего 60+) в школе ML Inside (запись на текущий поток закрыта).
Мой давний друг и коллега Витя Кантор попросил рассказать про другой его курс.
Онлайн-специализация «Искусственный интеллект и анализ данных»
Это реинкарнация старой специализации п…
С середины лета мегапростыня начала барахлить.
Ну как барахлить — она просто говорила, что меня нет. Я спал, а она говорит: нет, сегодня ты на мне не спал. Сначала пару раз в неделю, потом 3–4, потом уже почти каждый день. Но продолжала но ночам холодить, а по утрам греть и жужжать
Поначалу я подумал, что, возможно, уже достиг такого уровня познания, что по ночам ухожу в астрал. Но затем решил что реальность прозаи…
На днях начал делать ревью А/Б-платформы от Три сигма, позавчера отправил им 9 уточняющих вопросов, и пока они отвечают, попросили прорекламировать их митап в Ташкенте.
На что я говорю: так вы ответьте на вопросы, я в одном посте разбор проведу и заодно про митап расскажу.
Говорят, не успевают, митап уже скоро.
1 октября у них митап в Ташкенте
Data-Driven – от данных к действиям
Прочитал отличную заметку Shopify про gisting — сжатие системного промпта в обучаемые токены.
По сути, это компиляция промпта.
У GraphQL-агента Sidekick системный промпт занимал около 6 000 токенов, которые постоянно приходилось обрабатывать снова и снова.
Prefix caching решает проблему лишь частично. Модели не нужно повторно вычислять KV cache для промпта, но при генерации каждый новый токен всё равно работает со…
На основе пятничного поста про промт:
Сожми документ максимально, не потеряв никакой информации.
Превратили этот подход в отдельный open-source skill — lossless-doc-compress.
Скилл читает документ целиком и относит каждый фрагмент к одной из трёх категорий:
KEEP — содержит информацию и остаётся без изменений;
REMOVE — доказуемо избыточен и удаляется;
FLAG — требует решения автора, поэтому остаётся в документе с пом…
☁☁☁☁☁☁☁
24 сентября Yandex Cloud проведёт флагманскую технологическую конференцию — Yandex Scale 2026.
🎨🎨🎨🎨🎨🎨🎨🎨🎨🎨
🎨🎨🎨🎨🎨🎨🎨🎨🎨🎨
🎨🎨🎨🎨🎨🎨🎨🎨🎨
В программе четыре продуктовых трека — AI, Data, Security и Hybrid Infrastructure & DevOps, — и отдельный углублённый технологический трек DeepTech, который пройдёт только онлайн.
🎨🎨🎨🎨🎨🎨🎨🎨🎨🎨
🎨🎨🎨🎨🎨🎨🎨🎨🎨🎨
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В треке DeepTech откроем программу докладом о том, как мы ускорили Lua …
После ревью документов сегодня (один из дизайнов был на 51 страници!) даю совет всем, кто готовит документацию, пишет дизайн-доки и т. п.
1. То, что это написал агент/LLM, — не проблема, если вы это прочитали, поправили, дали контекст и т. д. Считайте, что отдали работу по редактуре. Если делегировали думать, получается чаще ерунда.
2. Прогоните свой документ через простую команду: «compress this as much as possibl…
Две первые главы книги «Agentic AI System Design» уже написаны и сейчас находятся на ревью у соавторов.
Один соавтор тот же: https://t.me/partially_unsupervised
Два — с курса по ML System Design.
По отзывам вышло неплохо:
Прочитал с кайфом и даже взял на вооружение
Надеюсь, к концу года допишем.
3 года назад я рассказывал про сказочника в своем посте
Но тот случай был хотя бы безвредным, да и, прочитав это, сказочник быстро убрал свои фантазии.
На днях в местах, где я живу, произошла история более печальная и более масштабная со всех сторон.
Профессор Jason Arday, который стал самым молодым черным профессором в истории Кембриджа, оказался не тем, за кого себя выдавал. Оказалось, что докторская его с больш…
Мы с Романом Нестером, Валерием Бабушкиным и Бесланом Курашовым (plevako.ai и karpov.courses) приглашаем вас на наш FuckUp Night 26 августа.
От формата отходить не будем — поделимся своими историями, где всё пошло не по плану. И поговорим про культуру ошибок: как не зацикливаться на промахах и использовать их в свою пользу.
Встречу проведём онлайн, поэтому подключиться можно из любой точки и всем, кто принимает реш…
💅48🔥28❤14👍4👎2
Showing the 12 most recent of 31 posts we hold for @cryptovalerii. 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.
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 13 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 6 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
Инжиниринг Данных @rockyourdata · 23,732 Telegram ranks this channel #1 of 93 here — alongside 92 others — read 17 September 2026
karpov.courses @KarpovCourses · 27,446 Telegram ranks this channel #1 of 96 here — alongside 95 others — read 10 September 2026
Dev & ML Connectable Jobs @dev_connectablejobs · 27,959 Telegram ranks this channel #2 of 94 here — alongside 93 others — read 10 September 2026
kyrillic @kyrillic · 60,982 Telegram ranks this channel #3 of 96 here — alongside 95 others — read 22 August 2026
Сиолошная @seeallochnaya · 79,594 Telegram ranks this channel #3 of 97 here — alongside 96 others — read 19 August 2026
Machine learning Interview @machinelearning_interview · 30,308 Telegram ranks this channel #5 of 98 here — alongside 97 others — read 7 September 2026
Reveal the Data @revealthedata · 27,806 Telegram ranks this channel #6 of 96 here — alongside 95 others — read 10 September 2026
LEFT JOIN @leftjoin · 42,064 Telegram ranks this channel #6 of 95 here — alongside 94 others — read 29 August 2026
LLM под капотом @llm_under_hood · 29,146 Telegram ranks this channel #7 of 96 here — alongside 95 others — read 9 September 2026
Noukash @noukashblog · 21,622 Telegram ranks this channel #8 of 95 here — alongside 94 others — read 23 September 2026
Data Secrets @data_secrets · 94,138 Telegram ranks this channel #8 of 98 here — alongside 97 others — read 17 August 2026
Математик в Лондоне @mathbotan · 26,819 Telegram ranks this channel #10 of 90 here — alongside 89 others — read 11 September 2026
Neural Shit @NeuralShit · 53,680 Telegram ranks this channel #12 of 92 here — alongside 91 others — read 24 August 2026
XOR @xor_journal · 182,317 Telegram ranks this channel #12 of 93 here — alongside 92 others — read 12 August 2026
Яндекс нанимает | Вакансии для разработчиков @ya_jobs · 32,803 Telegram ranks this channel #13 of 96 here — alongside 95 others — read 5 September 2026
Denis Sexy IT 🤖 @denissexy · 137,325 Telegram ranks this channel #13 of 95 here — alongside 94 others — read 13 August 2026
RationalAnswer | Павел Комаровский @RationalAnswer · 107,713 Telegram ranks this channel #14 of 98 here — alongside 97 others — read 15 August 2026
Яндекс Образование @Education_Yandex · 37,959 Telegram ranks this channel #15 of 96 here — alongside 95 others — read 31 August 2026
Yandex for Developers @Yandex4Developers · 28,545 Telegram ranks this channel #17 of 94 here — alongside 93 others — read 9 September 2026
Диджитализируй! @t0digital · 28,573 Telegram ranks this channel #18 of 88 here — alongside 87 others — read 9 September 2026
запуск завтра @ctodaily · 33,699 Telegram ranks this channel #20 of 96 here — alongside 95 others — read 4 September 2026
Поступашки - ШАД, Стажировки и Магистратура @postypashki_old · 45,531 Telegram ranks this channel #24 of 90 here — alongside 89 others — read 28 August 2026
FEDOR BORSHEV @pmdaily · 23,698 Telegram ranks this channel #25 of 97 here — alongside 96 others — read 17 September 2026
AvitoTech @avitotech · 25,625 Telegram ranks this channel #25 of 96 here — alongside 95 others — read 14 September 2026
This channel appears in 85 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 26 September 2026 — this
entry's latest reading, not the date you are reading this.
“Время Валеры” (@cryptovalerii), 30,808 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/cryptovalerii.
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.