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Channel

boiling point | Kanev Space

@boiling_point_kanev

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

1,302subscribers

-7 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1001748275590
TypeChannel
Username@boiling_point_kanev
CreatedBetween 1 December 2021 and 30 April 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live17 August 2026
Measurements held5
Confirmed unchanged1 time, most recently 17 August 2026
On Telegramt.me/boiling_point_kanev

Growth

1,3021,3091,305.57 August 2026 — 1,309 subscribers7 August 2026 — 1,309 subscribers7 August 2026 — 1,307 subscribers11 August 2026 — 1,305 subscribers17 August 2026 — 1,302 subscribers7 August 202617 August 2026
5 measurements spanning 10 days, net -7. 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 1,301–1,310 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
17 Aug 2026, 18:441,302-3
11 Aug 2026, 05:211,305-2
7 Aug 2026, 23:231,307-2
7 Aug 2026, 22:321,309no change
7 Aug 2026, 18:471,309first reading

Engagement

20 posts held, back to 25 April 2026the 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
22.2%
avg views ÷ 1,302 subscribers
Avg views / post
289
1 post measured
Reaction rate
5.19%
reactions ÷ views · ER floor
Posts in window
1
of 20 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 27 July 2026
Posts held20 (25 April 202627 July 2026)
Views total289
Reactions total15
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 22:32 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

227 reactions across 20 posts, in 9 distinct kinds. The most used accounts for 37.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
custom 53958487821202335148437.0%
🔥6528.6%
4318.9%
❤‍🔥187.93%
👍104.41%
custom 546521156335279250420.881%
20.881%
😱20.881%
😁10.441%

Custom emoji. 2 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.

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 227reactions 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 April 2026 to 27 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.

Telegram Stars

Stars received
2
across the posts below
Posts paid on
2
of 20 we hold a reading for · 10%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @boiling_point_kanev. 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 20 most recent posts we hold for this entry, published 25 April 2026 to 27 July 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

27 Jul 2026, 18:09 UTC289 views15 reactionsread 7 August 2026
Photo

Я отменил подписку на Claude за $200 после одного вечера с GPT-5.6 Sol Взялся делать мод для Kingdom Come: Deliverance II. Сначала пошёл с Opus 4.8. И целый день мы решали абсолютно тривиальную задачу. Причём «мы» — это я тыкал агента носом в очевидные участки кода, подсказывал, что анализировать и куда вообще копать. В какой-то момент возник закономерный вопрос: а кто тут, блин, агент? Claude стал каким-то амор

🔥84custom 53958487821202335143

7 Jul 2026, 18:36 UTC449 views8 reactionsread 7 August 2026
Photo

Почему ты вечно не укладываешься в сроки — и при чём тут чувство времени. «Сколько нужно?» — «Ну, дня два». Через неделю задача готова где-то на две трети, ты сидишь и не понимаешь, как опять так вышло. Дело не в том, что ты ленивый или тупишь. Просто ты понятия не имеешь, сколько реальной работы влезает в час твоего времени. Оцениваешь на глазок. А глазок врёт, причём всегда в одну сторону — в оптимизм. ⸻ Помодо

5custom 53958487821202335143

28 Jun 2026, 15:23 UTC455 views14 reactions1 Starread 7 August 2026
Photo

Всё! Доделал, наконец-то 🎉 Тот самый инструмент для прокачки LinkedIn SSI — готов. В прошлом посте говорил: буду пилить и показывать. Допилил. И очень доволен, как вышло. Зовут Beacon. Один запуск — и бот сам делает всю рутину: заходит на профили рекрутёров, растит сеть, лайкает и комментирует (текст под пост генерит LLM), кидает идеи для твоих постов. Принцип pull > push — не спамить инбокс, а прокачать профиль та

🔥7custom 539584878212023351452

23 Jun 2026, 10:00 UTC460 views13 reactionsread 7 August 2026
Photo

Думаю автоматизировать LinkedIn Точнее — прокачку SSI. Это внутренний индекс LinkedIn: насколько ты «живой» на платформе — ведёшь профиль, проявляешь активность, растишь сеть, попадаешь в чужие ленты. Чем выше SSI, тем чаще тебя показывают рекрутёрам и тем теплее заходят твои отклики. Штука, которую почти все игнорят. А она реально двигает выдачу. Проблема в том, что качается он руками и тупой рутиной: каждый день

custom 539584878212023351413

22 Jun 2026, 13:55 UTC376 views12 reactionsread 7 August 2026
Photo

Как же приятно читать такую обратную связь!) Сразу чувствую, что привношу какую-то пользу

8custom 53958487821202335144

22 Jun 2026, 11:43 UTC780 views15 reactionsread 7 August 2026
Photo

Я полгода пилил Job Radar. Сегодня — релиз. Началось с простого: я ненавижу искать работу. Не саму работу — а рутину вокруг неё. Открыть hh, пролистать сотни вакансий, на каждую написать сопроводительное, отправить, забыть, повторить. По 2–4 часа в день на тупую механику, которую делает человек только потому, что её некому делегировать. Я собрал AI-ассистента, который ищет работу за тебя. Что он делает. Каждый ден

🔥11custom 53958487821202335144

12 Jun 2026, 12:46 UTC517 views11 reactionsread 7 August 2026
Photo

226 откликов. Два оффера. Девушка из нашего закрытого сообщества пару месяцев гоняет Job Radar. React, обычный профиль, без нетворкинга и знакомых CTO. За это время через радар ушло 226 откликов. Это 3-4 отклика каждый день, два месяца подряд, без выходных. Руками так не делает никто, все сдуваются на второй неделе. Результат: два оффера. 250к и 340к. Второй собес по вакансии за 340, кстати, прошёл за 10 минут. Д

custom 53958487821202335147👍21🔥1

1 Jun 2026, 13:46 UTC535 views7 reactionsread 7 August 2026
Photo

🤖 Замкнул круг — агент сам ревьюит и сам исправляет В прошлом посте рассказал про связку SDD + TDD. Логичное продолжение — feedback loop через MR. Раньше после пуша надо было самому ждать ревью, читать замечания, чинить, пушить, ждать снова. Теперь это крутится без меня. Как работает: 1. Пушу feature-ветку → автоматом создаётся MR. 2. GitLab CI триггерит AI-ревьюера → агент читает diff и пишет ревью (~8-10 минут

custom 53958487821202335144👍3

31 May 2026, 11:51 UTC474 views8 reactionsread 7 August 2026
Photo

🎯 Объединил две методологии — баги от агента почти ушли Главная боль работы с ИИ-агентом — правдоподобная хрень, которая собирается, проходит «ну, кажется работает», а в проде взрывается. Поменял подход — и колоссально снизил эту шляпу. Подход — связка Spec Driven Development + Test Driven Development. Раньше они работали по отдельности и каждая давала что-то своё. Я их объединил в один сквозной воркфлоу под работу

4custom 53958487821202335143🔥1

28 May 2026, 17:21 UTC413 views8 reactionsread 7 August 2026

Opus 4.8 вышел🫥 Пошёл тестить!

4custom 53958487821202335143🔥1

22 May 2026, 20:20 UTC577 views9 reactionsread 7 August 2026

Job Radar восстановил! Но доступен он пока только для уже зарегистрированных участников, новые пользователи пока доступ получить не смогут (до тех пор, пока я не восстановлю модуль подписок и оплат)

🔥5custom 53958487821202335144

22 May 2026, 18:15 UTC583 views9 reactionsread 7 August 2026

Профессионалы из https://ufo.hosting/ сегодня похерили безвозвратно мой сервер, на котором находились все мои проекты, все базы данных, бэкапов не осталось (только несколько устаревших, которые я вручную делал). Не допускайте моих ошибок: 1. Не пользуйтесь этим хостером (пусть подумают над тем, как управлять своей инфраструктурой) 2. РЕГУЛЯРНО делайте бэкапы! Я вот расслабился и потерял контроль над этим. Сервисы б

custom 53958487821202335146😱21

Showing the 12 most recent of 20 posts we hold for @boiling_point_kanev. 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.

Citation-graph rank

Citation-graph rank — 1,395,116 of 1,549,376entries 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.

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

Named by 1 registered channel — 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.

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

“boiling point | Kanev Space” (@boiling_point_kanev), 1,302 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/boiling_point_kanev.

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.