Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 22 September 2026 and assigned it the closest of 31 fixed categories, at 43% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
6 measurements spanning 49 days, net +2. 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 365–371 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
25 Sept 2026, 08:00
370
+2
28 Aug 2026, 09:54
368
+1
22 Aug 2026, 01:38
367
+1
15 Aug 2026, 16:26
366
-2
8 Aug 2026, 06:20
368
no change
7 Aug 2026, 09:02
368
first reading
Engagement
19 posts held, back to 26 April 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 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 15 May 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
55s
Average length
55s
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
125 reactions across 18 posts, in 9 distinct kinds. The most used accounts for 33.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
42
33.6%
🔥
30
24.0%
🏆
26
20.8%
👍
12
9.60%
💯
6
4.80%
⚡
5
4.00%
❤🔥
2
1.60%
👎
1
0.8%
🤝
1
0.8%
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 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 125 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 26 April 2026 to 15 May 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
4
across the posts below
Posts paid on
2
of 19 we hold a reading for · 11%
Most on one post
3
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @ycguy. 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 26 April 2026 to 15 May 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.
I used to study a lot, and thought I was smart. I was wrong.
Two definitions changed my life:
1) Learning = same condition, different behavior.
2) Intelligence = speed of behavior change.
So if ya wanna be smart, ya gotta learn. If u wanna learn, u gotta change.
(c) Alex Hormozi
things that aren't doing the thing
Preparing to do the thing isn't doing the thing.
Scheduling time to do the thing isn't doing the thing.
Making a to-do list for the thing isn't doing the thing.
Telling people you're going to do the thing isn't doing the thing.
Messaging friends who may or may not be doing the thing isn't doing the thing.
Writing a banger tweet about how you're going to do the thing isn't doing…
My life was changed by four sentences in four books
Last week someone asked why I prefer books. My immediate answer was that I love their quiet, non-commercial nature. No ads. No hype. Just quiet wisdom with deep rewards for a focused mind.
But today I realized something more profound: Each of my biggest life-changing moments came from a single sentence deep inside a book.
#1 : Island by Aldous Huxley
This is a …
What taste actually is
Bourdieu called taste cultural capital: the internalized standards that let you recognize quality, make judgment calls, know which rules to break and when. Taste is knowing when the violation serves the work better than the rule does. It's shaped by exposure, education, and social context. It's both personal and collective. And it's generative, it doesn't just reflect a worldview, it creates o…
Я уверен — если передо мной появится сам господь бог, я спрошу у него что-то вроде: «В чем смысл жизни?», а он ответит: «Выращивай рис». А потом мы будем неловко молчать.
Есть такая концепция, я называю ее «спираль развития» — находясь на разном уровне спирали, ты не можешь увидеть картину целиком и понять, что действительно важно.
Когда начинающие предприниматели присылают мне вопросы, типа: «Как зарегистрировать …
О фаундерах
А теперь на ту же тему — про инвестиции — но уже из личного опыта.
Чем больше я занимаюсь инвестициями, тем боле прихожу к простой идее: почти ничего, кроме фаундера, не имеет значения. Идея, рынок, команда и технология — глубоко вторичны. Самые плохие инвестиции — это инвестиции в "классную идею" на "модном рынке". При этом, лучшие фаундеры работают почти исключительно над самыми интересными идеями на …
Автор пишет:
In college I took a class on what it means to be human. We spent weeks eliminating the obvious answers: intelligence, tool use, language. Now AI is working on all three.
Не знаю, очевидно ли вам, как и автору, почему intelligence, tool use и language не делают человека человеком, но мне было не очевидно.
Вот что claude пишет про все три:
сначала мой TL;DR
Интеллект — вороны, осьминоги и шимпанзе прох…
Организация — не имеет ни таланта, ни инфраструктуры данных, ни желания перестраивать процессы. Все в этой цепочке действуют рационально в рамках своих стимулов. Результат — рынок, где продавать AI радикально проще, чем получать от него эффект.
YC, кстати, это уже поняли. В их последних requests for startups фокус сместился: им интересны компании, которые не продают инструмент, а продают результат. Не "вот вам AI-пл…
🏆8
Showing the 12 most recent of 19 posts we hold for @ycguy. 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
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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Golden Borodutch @golden_borodutch · 65,429 Telegram ranks this channel #13 of 68 here — alongside 67 others — read 29 August 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 25 September 2026 — this
entry's latest reading, not the date you are reading this.
“you can, guy” (@ycguy), 370 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/ycguy.
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.