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Channel

Олег: raw data

@oleglimited

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

11,616subscribers

+110 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002353892841
TypeChannel
Username@oleglimited
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live6 September 2026
Measurements held25
Confirmed unchanged1 time, most recently 6 September 2026
On Telegramt.me/oleglimited

Growth

11,48711,61611,551.57 August 2026 — 11,506 subscribers8 August 2026 — 11,503 subscribers9 August 2026 — 11,502 subscribers10 August 2026 — 11,499 subscribers11 August 2026 — 11,501 subscribers12 August 2026 — 11,497 subscribers13 August 2026 — 11,498 subscribers14 August 2026 — 11,495 subscribers17 August 2026 — 11,493 subscribers18 August 2026 — 11,496 subscribers19 August 2026 — 11,491 subscribers20 August 2026 — 11,487 subscribers23 August 2026 — 11,504 subscribers25 August 2026 — 11,543 subscribers25 August 2026 — 11,568 subscribers26 August 2026 — 11,574 subscribers28 August 2026 — 11,580 subscribers28 August 2026 — 11,584 subscribers29 August 2026 — 11,589 subscribers30 August 2026 — 11,591 subscribers31 August 2026 — 11,593 subscribers1 September 2026 — 11,595 subscribers2 September 2026 — 11,599 subscribers4 September 2026 — 11,611 subscribers6 September 2026 — 11,616 subscribers7 August 20266 September 2026
25 measurements spanning 30 days, net +110. 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 11,468–11,635 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)SubscribersChange
6 Sept 2026, 14:4111,616+5
4 Sept 2026, 06:4111,611+12
2 Sept 2026, 20:5611,599+4
1 Sept 2026, 21:1311,595+2
31 Aug 2026, 23:1811,593+2
30 Aug 2026, 22:5511,591+2
29 Aug 2026, 21:2811,589+5
28 Aug 2026, 21:4811,584+4
28 Aug 2026, 00:4111,580+6
26 Aug 2026, 23:1511,574+6
25 Aug 2026, 21:4311,568+25
25 Aug 2026, 00:4911,543+39
23 Aug 2026, 13:4511,504+17
20 Aug 2026, 17:5711,487-4
19 Aug 2026, 21:2611,491-5
18 Aug 2026, 18:1711,496+3
17 Aug 2026, 18:5511,493-2
14 Aug 2026, 21:2811,495-3
13 Aug 2026, 13:1611,498+1
12 Aug 2026, 14:4511,497first reading

Engagement

22 posts held, back to 13 September 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 45 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
55.0%
avg views ÷ 11,616 subscribers
Avg views / post
6,390
2 posts measured
Reaction rate
0.869%
reactions ÷ views · ER floor
Posts in window
2
of 22 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 31 August 2026
Posts held22 (13 September 202531 August 2026)
Views total12,780
Reactions total111
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 01:32 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

2,432 reactions across 22 posts, in 10 distinct kinds. The most used accounts for 30.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🤝74530.6%
56223.1%
🙏32313.3%
😎2259.25%
🐳2168.88%
👀1455.96%
🤔1204.93%
🫡712.92%
💊160.658%
🗿90.37%

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 22 of the 22 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 2,432 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 22 most recent posts we hold, published 13 September 2025 to 31 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
250
across the posts below
Posts paid on
19
of 22 we hold a reading for · 86%
Most on one post
86
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @oleglimited. 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 22 most recent posts we hold for this entry, published 13 September 2025 to 31 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.

Recent posts

31 Aug 2026, 13:30 UTC≈4,220 views43 reactions1 Starread 3 September 2026

В новом видосе заставил Kimi K3 разрабатывать и тестировать код в цикле, пока результат не будет отвечать критериям качества. Попробовал несколько различных сетапов, меняя количество агентов и настройки цикла тестирования. Некоторые из запусков уходили работать на 20+ часов) Видос тут: https://youtu.be/u3gbL1cEEUs Все исходники, промпты + созвон по командам агентов тут: club.stefanov.tech

🙏18🐳107🤝5🤔2😎1

22 Aug 2026, 13:07 UTC≈8,560 views68 reactions1 Starread 3 September 2026

Запилил видос, где затестил все способы работы с субагентами на реальных задачах. Заюзал subagents, agent teams, dynamic workflows + запилил свою кастомную гига систему для одновременного запуска 100+ агентов в различных рабочих архитектурах. Видео: https://www.youtube.com/watch?v=gNsjZvzdGEE Примеры видосов, которые собраны через ИИ тут Промпты и исходный код всего из видео: club.stefanov.tech

🙏28🤝23🐳8💊32🫡2👀1🤔1

31 Jul 2026, 12:10 UTC≈11,300 views44 reactions3 Starsread 3 September 2026

Пока готвлю большой видос по командам агентов (который выйдет на следующей неделе), затестил модель M3 от MiniMax в связке с их MiniMax Code. Видос тут: https://www.youtube.com/watch?v=_MAjc4JgFlo Утилита для монтажа в DaVinci Resolve через терминал тут: club.stefanov.tech

😎247👀5🤝4💊3🫡1

1 Jul 2026, 16:24 UTC≈15,000 views101 reactions35 Starsread 3 September 2026

Запилил видос про свои правила промптинга с AI агентами В нем поделился подходами, которые выработал за год работы с Claude Code, Codex и другими ии кодинг тулами. И, конечно, разобрал каждый из них на конкретных примерах. Видео: https://www.youtube.com/watch?v=iZXi1si4sjo

🤝73😎11👀9🤔52🐳1

29 Jun 2026, 12:31 UTC≈12,600 views77 reactionsread 3 September 2026

Что если дать AI агенту возможность редактировать свою память? Есть мысль, что в текущих harness'ах возможно не хватает одной штуки. Сейчас у агентов есть дофига способов обогатить свой контекст (добавить данные в сессию): — memory tools — всякие RAG по документам — MCP серверы, которые ходят в файлы/базы/таски — разные rules/AGENTS.md/CLAUDE.md Но почти все эти вещи лишь добавляют данные в контекст. Сессия расте

🤔5016🐳6🤝3😎2

5 Jun 2026, 12:54 UTC≈12,800 views71 reactionsread 3 September 2026
Photo

15 июня выступаю на конфе Ребята из Podlodka AI Crew собрали сезон "AI-First Development", чтобы обсудить новые инженерные подходы, в которых AI становится частью команды (а не просто инструмент для генерации кода). Я вписался выступить, чтобы рассказать как мы в Salmon пилим автоматизации рутиных процессов с помощью CLI-агентов. Расскажу и покажу: • Что такое CLI агенты и как их использовать для AI-автоматизаций

😎4415🤝10👀2

31 May 2026, 19:03 UTC≈14,000 views129 reactions5 Starsread 3 September 2026

Сделал гайд по Codex. Постарался продемонстрировать все основные фишки этого инструмента, подсветил важные детали + капнул в различные формы кодекса: Codex App, Codex CLI, codex exec, codex app-server (в чем различия, когда что лучше использовать) Ну и запилил пару прикольных проектов по дороге. Видео вот: https://youtu.be/9j9pmM1OnLM Клуб вайб-кодеров тут: https://t.me/tribute/app?startapp=sLrD Там будет фулл со

🙏56🤝44🐳11😎115🫡2

14 May 2026, 13:57 UTC≈15,600 views46 reactionsread 3 September 2026

Запилил небольшой видос, где вайбкожу автоматизацию для постинга видосов, сгенерированных в моем недавнем проекте chertila.app, в x.com Видос: https://youtu.be/P-mUxay7EYg Код автоматизации из видео тут: https://github.com/coderroleggg/x-com-chertila-posting

👀18🐳10🤝8🙏8🗿2

30 Apr 2026, 20:28 UTC≈18,700 views126 reactions5 Starsread 3 September 2026

Я снова попробовал заспидранить создание микро проектов. Так как нейронки становятся все мощнее, решил в этот раз взять в разработку сразу 3 идеи. В итоге управился примерно за 30 часов. Не все прошло идеально, но в целом удалось дойти до какого-то результата. В новом видео рассказал с какими трудностями столкнулся, какие подходы использовал, что в итоге вышло. Видос: https://www.youtube.com/watch?v=ZijGaPNyxBE

67🐳27👀14🤔7🤝7😎3💊1

3 Apr 2026, 15:35 UTC≈18,700 views108 reactions5 Starsread 3 September 2026

Почти год назад я зарелизил Fanfy— мой первый AI микро стартап В новом видео рассказываю всё, что происходило после запуска. Что я улучшал и где дорабатывал. Какие в итоге цифры получились и сколько реально смог заработать. Видос: https://www.youtube.com/watch?v=E0KML1B1ssg Сырые цифры, графики и данные из видео тут: https://t.me/tribute/app?startapp=sLrD (подписывайтесь, если просто хотите поддержать канал, там п

55🙏20🤝16😎10👀4🫡2🗿1

2 Mar 2026, 11:46 UTC≈23,600 views154 reactions5 Starsread 3 September 2026

Сделал видос про AI агентов • Разобрал из чего они состоят, как работают • Какие есть способы работать с памятью: compacting, RAG, Auto memory, графы памяти • Как сделать своего агента • Мультиагентные системы: subagents, agent teams и кое что еще Видео: https://youtu.be/kgSy4NPWZ_4 Клуб по AI. Код проектов из видео тут: https://t.me/tribute/app?startapp=sLrD (подписывайтесь, если просто хотите поддержать канал, т

👀60🤝54🐳15😎118🤔3🙏2🫡1

26 Feb 2026, 19:36 UTC≈19,200 views97 reactions5 Starsread 3 September 2026

Сделал небольшое видео про AI кодинг фронтенда. На примере своего пет проекта показал как можно оформлять UI с ИИ кодинг агентами, не получая в результате базовый фиолетовый AI стиль. Видос: https://www.youtube.com/watch?v=Xh4ydlZ8lPQ Проект из видео тут: https://t.me/tribute/app?startapp=sLrD (подписывайтесь, если просто хотите поддержать канал, там пока просто чат + пару материалов из роликов)

😎3825🤝17🐳6🗿5🤔3🙏2💊1

Showing the 12 most recent of 22 posts we hold for @oleglimited. 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.

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 6 September 2026 — this entry's latest reading, not the date you are reading this.

“Олег: raw data” (@oleglimited), 11,616 subscribers as measured 6 September 2026. Telegram Register, tgregister.com/channel/oleglimited.

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.