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Channel

Жизнь моя жестянка: AI | LLM | Вездеходы

@mrvladdlife

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

332subscribers

+1 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002146425304
TypeChannel
Username@mrvladdlife
CreatedBetween 1 December 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live14 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 14 August 2026
On Telegramt.me/mrvladdlife

Growth

331332331.57 August 2026 — 331 subscribers8 August 2026 — 331 subscribers14 August 2026 — 332 subscribers7 August 202614 August 2026
3 measurements spanning 7 days, net +1. 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 331–332 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
14 Aug 2026, 10:28332+1
8 Aug 2026, 07:16331no change
7 Aug 2026, 11:57331first reading

Engagement

18 posts held, back to 12 July 2025the 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
33.4%
avg views ÷ 332 subscribers
Avg views / post
111
2 posts measured
Reaction rate
2.25%
reactions ÷ views · ER floor
Posts in window
2
of 18 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 4 August 2026
Posts held18 (12 July 20254 August 2026)
Views total222
Reactions total5
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 07:16 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
1m 05s
Average length
33s

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

199 reactions across 18 posts, in 16 distinct kinds. The most used accounts for 47.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥9547.7%
😁3819.1%
👍2613.1%
136.53%
🍓52.51%
🌚42.01%
🫡42.01%
❤‍🔥21.01%
👌21.01%
🤣21.01%
🤯21.01%
🥰21.01%
10.503%
🐳10.503%
💅10.503%
🙏10.503%

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 18 of the 18 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 199reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 18 most recent posts we hold, published 12 July 2025 to 4 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.

Recent posts

4 Aug 2026, 09:42 UTC84 views3 reactionsread 8 August 2026
Forwarded from @master_g_p_t

Около пол года бьюсь над созданием удобного процесса агентной разработки софта и наконец что то интересное стало вырисовываться . По началу набирася в Cursor опыта использования агентов по ролям. Ограниченность контекста заставляла экспериментировать с разного рода memory системами. Весной Дексден подсветил интересный memobank от Влада, там PRD-FT-TASKS, бюрократические протоколы, объем генерируемых служебных файл

👌21

4 Aug 2026, 09:02 UTC138 views2 reactionsread 8 August 2026

https://t.me/master_g_p_t/214 Отрадно видеть, как развивается memobank в различных вариациях Лайк и звездочка

❤‍🔥2

2 Jun 2026, 21:20 UTC426 views7 reactionsread 8 August 2026
Photo

Обновил https://github.com/mrvladd-d/memobank Рекомендую всем попробовать Жду ваших отзывов и предложений Обновлены многие команды . Добавлены идеи из BMAD + specKit

👍7

5 Mar 2026, 22:37 UTC≈2,770 views27 reactionsread 8 August 2026
Photo

🚀 Выложил memobank — свой skill pack для Codex / Claude / agent-first разработки. Это репозиторий, который помогает не просто “запускать агента”, а выстраивать для него нормальную рабочую среду: с памятью проекта, понятными протоколами, задачами, ревью и воспроизводимым флоу до результата. Почему мне самому это было важно: Потому что в какой-то момент стало очевидно: если агент работает только в рамках одного чата,

🔥18👍63

25 Feb 2026, 09:22 UTC707 views15 reactionsread 8 August 2026

Pi — минимальный кодинг-агент, на котором построен OpenClaw 🦞 Пока все обсуждают OpenClaw, я покопался в том, что у него внутри. А внутри — Pi, проект Марио Цехнера. И вот он мне зашёл сильнее, чем сам OpenClaw 👇 Что это такое: cli кодинг с радикально маленьким ядром. Четыре инструмента: Read, Write, Edit, Bash. Всё. Самый короткий системный промпт из агентов, что я видел. Чем цепляет: 🌳 Сессии — деревья. Работаеш

🔥113🐳1

8 Feb 2026, 20:17 UTC587 views20 reactionsread 8 August 2026
Video

Made by https://matreshkastudio.cloud/ Сэртифыкат😂

😁126🔥2

8 Feb 2026, 20:15 UTC518 views13 reactionsread 8 August 2026
Photo

Когда AGI придет , знаете где искать меня 😁

🔥6🫡4🥰2💅1

29 Jan 2026, 20:49 UTC588 views12 reactionsread 8 August 2026
Photo

И так, наш ответ Чемберлену или отечественная платформа - студия для генерации кино и фото прямо у вас в браузере - ! https://matreshkastudio.cloud/ Под капотом: - более 30 топовых моделей по генерации фото или видео - AGENT 🙂 для e2e генерации кино по запросу. Пишет за вас сценарии - подтверждаете и наслаждаетесь сгенерированным контентом (но ест кредитов много)) - Промпт+ - улучшает входной промпт для лучшего рез

🔥7🍓5

24 Jan 2026, 21:08 UTC604 views5 reactionsread 8 August 2026

Экономика должна быть экономной! Всем доброго здравия! Оочень усердно работаю тут над своим пет проектом, скоро на суд представлю, а пока - успел оформить классную тему https://lennysproductpass.com/ В общем платите на год 350$ - и у вас в доступе крутые сервисы bolt/manus/gamma/granola/warp... В соседнем чате сошлись , что на круг выходит раз в 10 дешевле, чем каждый по отдельности покупать P.S: при регистрации ma

🔥5

25 Nov 2025, 11:29 UTC≈1,060 views11 reactionsread 8 August 2026

SGR-Council-Agent - LLM-консилиум для ERC3 на основе идеи Карпаты 🧑‍⚖️ Вдохновился репой Андрея Карпаты и запилил свою реализацию под ERC3.0: 🔗 https://github.com/karpathy/llm-council Идея: вместо одной LLM — совет из нескольких моделей: 1️⃣ Каждая модель независимо предлагает свой план решения задачи 2️⃣ Модели анонимно оценивают планы друг друга (Plan A, B, C — без имён моделей) 3️⃣ Chairman-модель синтезирует ф

🔥8👍3

22 Nov 2025, 14:23 UTC998 views11 reactionsread 8 August 2026

Я продолжаю ковырять ERC3 и STORE-бенчмарк — на этот раз не модель, а обвязку вокруг неё. Оказалось, что один и тот же Qwen3-Coder-480B может показывать 66.6 или 100 баллов в зависимости от того, через какой CLI-агент его запускать 🙃 ⚙️ Коротко: что такое OpenCode и Qwen Code OpenCode — это опенсорсный AI‑кодер для терминала, «клон» Claude Code, но без привязки к одному вендору. Работает как TUI поверх разных LLM (

🔥11

21 Nov 2025, 11:20 UTC869 views11 reactionsread 8 August 2026

Платформа ERC 3.0 уже открыта для тестовых прогонов! Спешу с вами поделиться опытом первых иттераций в статье! Первые опыты с моделью gpt-4o! С ней получилось набрать 80 очков https://teletype.in/@mrvladd/0XcaSkN2l__

🔥11

Showing the 12 most recent of 18 posts we hold for @mrvladdlife. 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.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

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

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

“Жизнь моя жестянка: AI | LLM | Вездеходы” (@mrvladdlife), 332 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/mrvladdlife.

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.