4 measurements spanning 6 days, net -12. 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 2,815–2,831 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Aug 2026, 13:35
2,817
-5
10 Aug 2026, 07:24
2,822
-7
7 Aug 2026, 14:46
2,829
no change
7 Aug 2026, 14:33
2,829
first reading
Engagement
12 posts held, back to 24 March 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
26.9%
avg views ÷ 2,817 subscribers
Avg views / post
757
1 post measured
Reaction rate
2.38%
reactions ÷ views · ER floor
Posts in window
1
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
Window
Rolling 30 days · latest post in window 3 August 2026
Posts held
12 (24 March 2026 – 3 August 2026)
Views total
757
Reactions total
18
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 14:46 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
Video runtime
34s
Average length
17s
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
433 reactions across 12 posts, in 12 distinct kinds. The most used accounts for 38.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
168
38.8%
😁
89
20.6%
👍
65
15.0%
😱
34
7.85%
❤
30
6.93%
✍
21
4.85%
🤣
12
2.77%
🥴
5
1.15%
👀
4
0.924%
👌
2
0.462%
🤩
2
0.462%
☃
1
0.231%
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 433reactions 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 24 March 2026 to 3 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.
Telegram Stars
Stars received
5
across the posts below
Posts paid on
1
of 12 we hold a reading for · 8%
Most on one post
5
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @DiaryFlutterDev. 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 12 most recent posts we hold for this entry, published 24 March 2026 to 3 August 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.
👨💻Официальный плагин claude-security от Anthropic
У claude вышел официальный плагин claude-security для поиска дыр проекта. Ставится легко, жрет токены за семерых. Установка:
/plugin install claude-security@claude-plugins-official
/reload-plugins
По доке рекомендуют запускать через /claude-security:scan, но тогда получите
The bare /claude-security:scan command was invoked without arguments, so there's nothing for …
🧑💻 Аудит кодовой базы на Fable 5
Если у вас есть подписка на Claude Code, наверняка вы уже успели потестить новый Fable 5. Говорят, что он не сильно умнее последнего Опуса.
А вот мне зашло другое. На больших задачах Fable ощутимо лучше - анализ качества кода, поиск уязвимостей, разбор кодовой базы разом. Там, где Опус начинал плыть на масштабе, Fable держит контекст
➡️ Что попробовать:
Скормите ему свой проект и …
Скуфизация?
Дескуфизация
До/после
Год регулярных тренировок в зале. Не топ, но в разы лучше, чем было)
🟢P.S. Стас говорит это же дневник, нужно делиться🙂
✍️ Вопрос-ответ
🟢Ответил в чате, возможно и вам будет полезно, как локализовать 8тыс уникальных слов и предложений с ИИ:
➡️ Есть у кого то опыт локализации программ или сервисов через ИИ?
Столкнулся со сложностью перевода одной ERP системы, такие системы и так сложные в понимании, а тут еще надо правильно тексты перевести
Тупо скинуть данные ИИ не помогает - без контекста перевод получается так себе
Пропиши ей кон…
⚡️Как внедрять агентские скилы и какие задачи они решают
Агентские скилы стали закономерным этапом в развитии ИИ, обеспечив моделям переход от простой генерации текста к автономной работе в рамках заданных сценариев. Тема сейчас очень актуальная, но вот стоящих докладов с цифрами и конкретными решениями - меньше, чем хотелось бы. Промежуточными результатами внедрения агентной разработки поделился Егор Федяев из Янде…
Flutter vs Native
Поддержим коллег, записали интересное видео о flutter и нативной разработке👍
https://www.youtube.com/watch?v=-NrQ5hY7DTk
Честно говоря, темы "flutter vs native", "flutter сразу на несколько платформ, а натив ближе к пользователю", "натив помирает, а флаттери жив и наоборот" и тд., со стороны разработчиков уже настолько заезжены) Все все знают
На мой взгляд куда интереснее то, о чём обычно молчат…
Юмора ради) А может и нет
Представляете, у этого приложения только в 1 сторе 1000+ скачиваний. В нем реклама, платные покупки, и.. этим пользуются😄
Моя реакция:
Не удивлюсь, если оно еще и платное
ахахах, оно платное) Там есть покупки
Интересно стату глянуть, какая монетизация. Я в шоке. За такое еще и платят
https://t.me/devhub/10500
🟢Вывод: разработчики создают и зарабатывают даже, с казалось бы, совсем бредовы…
⚡️ Как экономить токены в AI ассистентах
При использовании сodex/сlaude/сursor/gemini или другой AI вы наверняка замечали, как быстро раздувается контекст от обычных команд типа git diff
Большáя доля токенов уходит не на основную задачу, а на неинформативный вывод(мусор): длинные логи тестов, простыни git diff, списки файлов, прогресс-бары, повторяющиеся строки ошибок
➡️ Решение - RTK (Rust Token Killer)
Это CLI‑…
🦖 Умер GetX
Всеми любимая😄, самая популярная Flutter либа getx исчезла с GitHub. Репозиторий github.com/jonataslaw/getx отдаёт 404. Аккаунт автора тоже не открывается
Видимо, аккаунт заблокирован на GitHub
В целом, итак считалось, что либа заброшена. Слабая поддержка - автор пропадал на год-два, issues висят без ответа, а версия 5.0 с Navigator 2 до сих пор в release candidate. И все это с учетом удивительной поп…
⚡️Блокировки акков ИИ
Недавно писал, что оплачиваю агентов через сервис мтс. Сервис не рекомендую, начали массово блокировать аккаунты после оплаты с карт мтс
🟢P.S. Деньги мтс в таком случае возвращает
😱18👌2✍1👍1
Showing the 12 most recent of 12 posts we hold for @DiaryFlutterDev. 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.
Mentions
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.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
1
we ourselves saw one of these resolve, at some point
Never seen alive
0
vacant every time we have ever looked
@DiaryFlutterDev named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
@devhub named in 1 post, 8 August 2026 – 8 August 2026 · confirmed gone 12 August 2026 (two independent sightings — see how we confirm a dead handle)evidenced
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.
“Дневник Flutter-разработчика” (@DiaryFlutterDev), 2,817 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/DiaryFlutterDev.
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.