Channel
@communitysprints
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
4,218subscribers
+0 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1002447475652 |
|---|---|
| Type | Channel |
| Username | @communitysprints |
| Created | Between 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/communitysprints |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 15:26 | 4,218 | -4 |
| 10 Aug 2026, 05:32 | 4,222 | +2 |
| 6 Aug 2026, 20:22 | 4,220 | +2 |
| 6 Aug 2026, 04:20 | 4,218 | no change |
| 6 Aug 2026, 04:19 | 4,218 | first reading |
20 posts held, back to 25 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 5 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.
| Window | Rolling 30 days · latest post in window 30 July 2026 |
|---|---|
| Posts held | 20 (25 March 2026 – 30 July 2026) |
| Views total | 3,934 |
| Reactions total | 59 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 12:02 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.
618 reactions across 20 posts, in 6 distinct kinds. The most used accounts for 47.2% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 292 | 47.2% | |
| 🔥 | 203 | 32.8% | |
| 👍 | 95 | 15.4% | |
| 🎉 | 18 | 2.91% | |
| 👏 | 7 | 1.13% | |
| 🥰 | 3 | 0.485% |
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 20 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 618reactions 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 25 March 2026 to 30 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.
Команда Al-агентов чинит баги за 15 минут ⚡️ #кейс Ильи Бердыша, Co-founder @ mymeet.ai (с конференции AI SKILLS) Ключевой инсайт: не ускоряйте отдельного человека, переводите на AI-агентов целый процесс. То, что годами висело в бэклоге и передавалось между людьми, теперь один человек с AI-агентом закрывает за день ⚡️ 1. Ассистент для багов: с двух-трёх дней до 15 минут Мы делаем notetaker'ы: боты приходят на вст…
❤8🔥7👍6
ОФЛАЙН события в сообществе Community Sprints! ⚡️ #комьюнитипост от Алекса Беляева, активиста в Community Sprints Всем большой привет! Мы делаем очень много онлайн активностей, но иногда сильно скучаем по офлайну В офлайне есть своя уже иногда как будто забытая магия, поэтому мы подготовили аж целых 2 офлайн события в августе! 1. Совместный завтрак в Москве 22 августа 🕺 Здесь можно посмотреть, как мы собирались …
❤11🔥4🎉2
AI-кейс Yango. AI-агенты вместо отдела дизайна ⚡️ #кейс Michael Browk, дизайн-директор @ Yango (с конференции AI Skills) Ключевой инсайт: не садитесь верстать сайт руками на три недели. Соберите контекст и скиллы, отдайте команде AI-агентов, и дальше сайт собирается и правится почти без вас ⚡️ 1. Маркетплейсы не дают выделиться, поэтому мы пошли в свой магазин Мы продаём умные колонки Ясмина в регионе MENA: Египе…
❤10🔥9👏2
AI-кейс Avito. Отчётность, дайджест недели и прогноз выручки за меня теперь делают команды AI-агентов ⚡️ #кейс Алекса Малинского, Head of Analytics @ Avito Travel (с конференции AI Skills) Ключевой инсайт: рутину руководителя аналитики можно собрать в набор AI-агентов: операционные задачи, дайджест и прогноз почти без ручного труда. Но чем сложнее задача, тем больше контекста и валидации остаётся на вас 1. Как свя…
🔥14❤7👏5
Три AI-системы, которые маркетологи собрали для своих команд 🔥 Ключевой инсайт: не ускоряйте человека разовыми скиллами: переведите повторяющийся процесс на AI-агента и создайте этап проверки. При правильной настройке вы увидите рост метрик #кейс Макса Епифанова, VP of performance marketing @ TripleTen Решения по рекламе принимает AI-агент Раньше человек вручную смотрел на цифры и решал, где добавить бюджет, а гд…
❤6👍3🔥2
Live-встреча: AI-native команда в маркетинге ⚡️ Спикеры: • Макс Епифанов, VP of Performance Marketing @ TripleTen • Настя Рябова, AI Strategy & Enablement Lead @ TripleTen • Сева Устинов, Founder @ Plurio Что покажем: 1. Макс Епифанов расскажет, как в TripleTen перестроили перформанс-маркетинг вокруг AI: скиллы, аналитика, бюджеты, креативы. 2. Настя на живом примере покажет весь процесс создания новых воронок че…
🔥7❤5🎉1👍1
Как поднять конверсию новых продуктовых AI-фич в 4 раза? Кейс Miro ⚡️ #кейс Кирилла Баранова, Senior PM (Growth & AI Adoption) @ Miro (с конференции AI SKILLS) Кирилл использовал 5 приёмов adoption новых AI-фичей в продукте Miro, и каждый поднимал конверсию 🔥 Тут все 5 по списку: 1. Ловите момент, а не грузите онбордингом Если показать пользователю онбординг и сказать «изучай», ему тяжело. Контекстное обучение …
❤12🔥8👍1
Кейс из Nebius. Как измерить эффективность внедрения AI в команде? 🤔 #кейс Романа Бунина, AI Adoption Lead @ Nebius (с конференции AI SKILLS) Главный вывод сразу: самооценка эффективности обманывает. AI внедрение надо мерить, как retention продукта ⚡️ 1. Как лидировать AI adoption в компании? У нас в Nebius есть команда AI adoption, которой я руковожу: мы раздаём людям инструменты, обучаем и собираем success stor…
❤22👍11
Материалы, записи и конспекты всех AI-кейсов с конференции уже здесь! ⚡ 2000+ участников, 18 спикеров и невероятное количество очень классных вопросов от участников! Это были потрясающие 3 дня! Спасибо всем, кто подключился и присоединился к этому празднику!) Тут все записи лайвов конференции от команды Community Sprints: День #1: AI-кейсы из Yango, Avito, Miro, HH, Nebius, Plurio, hirehire и TripleTen • Линк н…
❤33👍13🔥13🥰3
Большая конференция про AI-юзкейсы из Miro, Nebius, Avito и других топовых компаний ⚡️ Собрали снова топовых профессионалов вместе, обменяться свежим опытом про использование AI в командах 👀 Это хорошая возможность оставаться на острие возможностей AI в работе На грядущей конференции своим опытом использования AI в работе и бизнесе поделятся продакты, маркетологи, инженеры и основатели из: • Miro • Avito • Yango …
❤17🔥13👍8
AI-персона из транскриптов звонков чинит маркетинговую воронку. До того, как ты потратил бюджет 🔥 #кейc Насти Рябовой, AI Strategy & Enablement Lead @ TripleTen 1. Почему нельзя просто попросить GPT представить, что он твой клиент? Обычно синтетические персоны ломаются в тот момент, когда ты просишь их оценить креатив или лендинг в лоб Модель подстраивается под контекст вопроса, включает sycophancy (склонность по…
❤17👍13🔥9
Закрытая встреча: разбираем кейсы AI в продукте 🔥 Cобираем встречу участников нашего комьюнити ⚡️ На встрече своими AI кейсами в продукте поделятся: • Дима Зборовский, Al & Science director @ Doordash / Deliveroo • Катя Окунева, Lead Product Manager @ MTS AI • Павел Минаев, ex-Ernst & Young • Максим Епифанов, VP of Performance Marketing @ TripleTen • Катя Кириллова, CEO & Founder @ XTIX • Алекс Бенкендорф, Founder…
❤10🎉6👍6
Showing the 12 most recent of 20 posts we hold for @communitysprints. 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 — 110,730 of 1,336,469entries 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.
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 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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“Community Sprints” (@communitysprints), 4,218 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/communitysprints.
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.