3 measurements spanning 14 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 166–167 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
21 Aug 2026, 15:16
166
-1
8 Aug 2026, 15:47
167
no change
7 Aug 2026, 09:05
167
first reading
Engagement
19 posts held, back to 6 June 2025 — 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 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 19 posts for this entry, the most recent from 3 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
25s
Average length
25s
Measured directly from 1 video 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
217 reactions across 17 posts, in 10 distinct kinds. The most used accounts for 42.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
92
42.4%
⚡
52
24.0%
🔥
25
11.5%
🦄
12
5.53%
🫡
10
4.61%
🙏
9
4.15%
👍
8
3.69%
😈
7
3.23%
👎
1
0.461%
🤓
1
0.461%
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 17 of the 19 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 217 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 6 June 2025 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
46
across the posts below
Posts paid on
10
of 18 we hold a reading for · 56%
Most on one post
22
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @krenels. 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 19 most recent posts we hold for this entry, published 6 June 2025 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.
Сегодня выйдет первый эпизод подкаста Agentic Coffee Bros.
Время поменялось, coding agent-ы стали инструментов разработчиков. Появился spec-driven подход. Стало возможным переписать огромный продукт на Rust (как сделали Bun https://bun.com/blog/bun-in-rust) за 10 дней против года.
При этом, есть 2 проблемы
— Не понятно, как измерить ценность от решений. Вокруг куча хайпа: постоянно выходит новая китайская модель, к…
Про “being okay” и модель обучения
Я никогда не был “самым быстрым” — ни в разработке, ни в предпринимательстве. “Самым быстрый" — больше всего выкатить фич за спринт, самый высокий time to market.
Надо было уметь много деливерить со сравнительно низкой вдумчивостью — у меня плохо получалось в такое: я начинал копать в детали и тонкости.
10 лет назад я комплексовал от этого. Мне казалось, что я не имею advantage …
#books
Случайно узнал, что у Yogi Berra есть книга про команду и жизнь.
Йоги Берра — один из людей, о которых я узнал через Талеба.
В моей голове Йоги глубоко засел как мастер и мудрец.
Йоги Берра получил титул Most Valuable Player 3жды. Таких ребят всего 4 в истории бейсболла. Стал тренером 1965 году.
Йоги сказал знаменитое “It ain’t over till it’s over” — и предполагаю, что это был источник для Талебовского вд…
Размышляю последнюю неделю об одном из принципов, которым живу: invest in learning infrastructure.
Хотя размышления пока недописаны — жизнь продолжает праймить меня на эту тему: сегодня случайно встретил понятие “autodidacts”.
Autos я знаю — это “сам”. “didacts” оказалось “учить”.
Те, кто обучаются сами. Удивително красиво звучит.
Хотя никогда не слышал про автодидактов — Я знаком с понятием “self taught”, которое…
#playbook
Снепшот принципов, которые уточнились или родились за этот год:
— break the fucking ice level 2 = не останавливайся на черновике, итерируй и улучшай. Оказалось, что это проблема для ребят, кто освоил подход “черновика”. Иначе: drop the ball. Обойти drop the ball — это break the fucking ice level 2
— “как самурай взмахивать мечом на горе фудзи каждый день целый год” — про дисциплину и то, что удивительно …
#books #mindset
Cтратегия — не выбор, а дизайн
Когда смотришь назад на успешную историю — OpenAI / Salesforce / <успешный стартап Х> — всегда видишь “иллюзия выбора”.
Кажется, что перед командой стояло “три пути” — и она просто взяла лучшую из возможных.
Salesforce: self-hosted CRM дорогие и тяжелые? Будем продавать CRM в 1990 по модели подписки.
OpenAI: страшно за AI? Будем привлекать cutting-edge AI таланты в …
#strategy
Следи за руками
TL;DR:
Не путай громкие слова, цитатки, вижен - со стратегией. Крутые результаты дает не тупо «positive thinking» — нужна конкретика: «Fix it, close it or sell it» и «Будь #1 или #2, иначе выходи из рынка». Эти политики имеют основания и помогают принимать решения «на местах». А не только красиво звучат.
Сегодня размышлял о том, как фаундеры черпают вдохновение и подходы из всяких баек. К…
Про Kaiju No. 8, Кимино Кафку и то, как аниме может изменить вас
Я тут опубликовал историю в Инстаграм про кино и аниме. Слава сподвиг вылить мысли на бумагу глубже: показать, какие элементы историй и как со мной резонируют. Ниже я рассказал историю Кимино Кафка — его прообразы — и то, как они со мной резонируют. Возможно этот пост сподвигнет вас переоценить влияние аниме и кино on one’s own charater.
Мне так хотел…
#MetaMindset
TL;DR Моя сильная сторона — deep thinking: смотрю вперед, вижу сайд-эффекты и отфильтровываю байасы. Минус — глубина замедляет. Баланс дают «pit-crew» партнеры и команда — люди, которые умеют строить операционку, не выключая мозг.
Умение глубоко думать — мой unique value proposition. Глубоко — я вижу и короткий, и длинный горизонт. Учитываю сайд эффекты. Умею быть менее biased, чем другие. Знаю природу…
❤7⚡5🙏5
Showing the 12 most recent of 19 posts we hold for @krenels. 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.
Forward network
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.
Mentions
Named by 4 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.
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
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@krenels 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.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@wedogtm named in 1 post, 9 August 2026 – 9 August 2026
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 21 August 2026 — this
entry's latest reading, not the date you are reading this.
“Krenel is building” (@krenels), 166 subscribers as measured 21 August 2026. Telegram Register, tgregister.com/channel/krenels.
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.
