Мои мысли про стартапы и продукты.
Байрам Аннаков, фаундер and CEO onsa.ai - автоматизация B2B продаж
Мой сайт: https://empatika.com
Мой YouTube: https://www.youtube.com/BaykaAnnakov
Мой LinkedIn: https://linkedin.com/in/bayramannakov
Created
29 April 2017 — measured — cross-checked against a third-party dataset (ext.tg_channel)
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 10 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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 the other topics.
Growth
62 measurements spanning 98 days, net -185. 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 15,289–15,568 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)
Subscribers
Change
12 Nov 2026, 11:15
15,340
-5
10 Nov 2026, 07:50
15,345
+3
8 Nov 2026, 22:57
15,342
-8
7 Nov 2026, 14:19
15,350
+4
6 Nov 2026, 11:09
15,346
+16
5 Nov 2026, 10:48
15,330
-1
2 Nov 2026, 09:35
15,331
-6
1 Nov 2026, 10:20
15,337
-4
31 Oct 2026, 08:06
15,341
+1
30 Oct 2026, 09:28
15,340
+5
29 Oct 2026, 09:59
15,335
-3
28 Oct 2026, 05:40
15,338
+13
27 Oct 2026, 08:25
15,325
+4
26 Oct 2026, 10:49
15,321
-1
25 Oct 2026, 10:10
15,322
+1
24 Oct 2026, 08:49
15,321
-3
23 Oct 2026, 10:05
15,324
-4
22 Oct 2026, 06:40
15,328
+2
20 Oct 2026, 20:55
15,326
-1
19 Oct 2026, 21:41
15,327
first reading
Engagement
60 posts held, back to 3 July 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 79 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
18.4%
avg views ÷ 15,340 subscribers
Avg views / post
2,830
19 posts measured
Reaction rate
0.839%
reactions ÷ views · ER floor
Posts in window
19
of 60 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
Window
Rolling 30 days · latest post in window 12 November 2026
Posts held
60 (3 July 2026 – 12 November 2026)
Views total
53,750
Reactions total
451
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
15 Nov 2026, 07:25 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
Photos
≈576
Videos
≈76
Links
≈1,030
Lifetime counters from Telegram’s own channel header, read 15 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
40s
Average length
40s
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
2,046 reactions across 59 posts, in 31 distinct kinds. The most used accounts for 34.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
712
34.8%
🔥
526
25.7%
👍
261
12.8%
🤣
146
7.14%
😁
143
6.99%
💯
51
2.49%
👏
44
2.15%
😍
37
1.81%
🎉
28
1.37%
🤝
28
1.37%
🙏
26
1.27%
🤔
7
0.342%
❤🔥
6
0.293%
🥴
6
0.293%
✍
3
0.147%
🤓
3
0.147%
🥰
3
0.147%
💅
2
0.098%
🤷♀
2
0.098%
⚡
1
0.049%
11 further kinds
11
0.538%
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 60 of the 60 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 2,220 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 60 most recent posts we hold, published 3 July 2026 to 12 November 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
30
across the posts below
Posts paid on
8
of 60 we hold a reading for · 13%
Most on one post
20
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @ProductsAndStartups. 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 60 most recent posts we hold for this entry, published 3 July 2026 to 12 November 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
Telegram’s own ‘edited’ marker: 11 of 19 posts held from the last 30 days (57.9%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
За что клиент будет платить, когда код почти бесплатный?
Этим вопросом я закончил пост про изобилие кода. В прошлую пятницу покрутили его на AI Natives. Допустим, клиент может собрать приемлемый аналог. За что он будет платить нам снова?
3 ключевые идеи, которые мы вынесли - спасибо Анжелике, Мише и дружбану за плодотворный брейнсторм!
1) Формула внимания
Клиент покупает, а не вайбкодит, пока
Стоимость внимания …
Что ещё делает швейцар? Или что мы упускаем, когда автоматизируем работу
Представьте, что у вас отель. После глубокого анализа по оптимизации расходов консультанты предлагают вам автоматизацию: зачем платить швейцару за то, что дверь умеет делать сама? Ставите автоматическую дверь, увольняете швейцара - профит!
На следующий день к отелю подходят трое. Один тащит два чемодана, второй останавливается у вас каждый мес…
пришла пора новой переклички: уже год прошел :)
Знакомимся? Пишите в комментариях несколько слов о себе, почему вы здесь и ссылку на свой LinkedIn/Телеграм канал
Вот мой: https://www.linkedin.com/in/bayramannakov
Зовут меня Байрам. Люблю технологии и обучение. И добрых Людей! Пытаюсь популяризировать предпринимательство и инструменты, помогающие в этом нелегком деле
Ваш ход?
Зачем просить LLM менять веса другой модели?
В твиттере нашумела работа про Weight-Space Programming: LLM читает и меняет веса других нейросетей, а маленькие сети может писать с нуля.
Откуда столько энтузиазма? В демо авторов Astra исправляет зацикливание Qwen, изменяя небольшую часть весов. CTO Legora показывает, как Fable пишет веса маленькой сети для проверки юридических ссылок. Ну и, разумеется, без сингулярнос…
На следующей неделе буду в Тбилиси: есть идейка в четверг 12го собраться в каком-нибудь пабе и развиртуализироваться/встретиться со старыми знакомыми
Кто в деле - добавляйтесь в группу, там решим что и где: https://t.me/+JTacDrNziDYzNDk6
AI сделает компании меньше... или больше?
У DeepMind вышла интересная работа про то, как AI изменит размер компаний. Авторы разделяют две способности:
1) компетенция - насколько хорошо агент выполняет задачу индивидуально
2) координация - насколько хорошо агенты работают вместе
Более сильный агент позволяет делать больше прежней командой; улучшение координации может сделать выгодной более крупную организацию.
Но з…
Запись встречи - enjoy! youtube.com/watch?v=CKicV_syHMM&feature=youtu.be
Главы:
00:00 Приветствие и что изменилось у участников
05:04 Январь → октябрь: что изменилось в моей работе
08:06 Новые навыки: чистая среда, followthrough и персонализация
14:09 Правила, которые появились после ошибок
20:11 Карта задач: где я использую AI
25:42 Петля: контекст → попытка → проверка → исправление
26:42 Навыки и подключенные инст…
AI и свобода ПЕРЕДУМАТЬ
Прочитал мини-эссе Джеффри Катценберга про AI и творчество. Понравилась мысль, что спор «использовать AI или нет» завёл нас не туда: полезнее обсуждать условия, на которых мы будем его использовать.
Интересный у него состоялся разговор с LLM о разнице между reasoning и creating:
Reasoning and creating are two distinct cognitive modes, though they also work together. Reasoning is fundamental…
Одиночество фаундера 2.0?
Как-то писал здесь про одиночество руководителя. Кажется, у этой темы появляется новая версия: если всё больше работы можно сделать с агентами, как меняется само ощущение от работы?
В недавнем разговоре у Лекса Фридмана Анкур Мойтра сформулировал интересное чувство:
So I feel very excited, but maybe more intellectually lonely than I felt before.
Он радуется новым возможностям AI, но пере…
Как понять, что агент умеет делать продукт?
В первом посте про изобилие кода мы приняли рабочую гипотезу:
AI сможет выполнять значительную часть задач по разработке продуктов с приемлемым качеством, стоимостью и супервизией.
Как выяснить, какую часть этой работы уже можно отдавать агентам?
Окей, мы с вами знаем, что писать код они могут. Но при этом всем нам очевидно, что создать продукт это не только про написать…
В январе я рассказывал, как юзаю Claude Code —> в пятницу сделаем апдейт
Обсудим в пятницу: https://luma.com/i1i4k9qq
🔥25❤11👍2😁2👏1🤓1
Showing the 12 most recent of 60 posts we hold for @ProductsAndStartups. 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 18 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.
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.
Продакты не нужны @betternotworse · 28,392 Telegram ranks this channel #3 of 96 here — alongside 95 others — read 9 September 2026
Вправо Вверх 📈 Михаил Табунов @bossofyourboss · 27,263 Telegram ranks this channel #4 of 95 here — alongside 94 others — read 10 September 2026
e/acc @cryptoEssay · 63,674 Telegram ranks this channel #4 of 96 here — alongside 95 others — read 21 August 2026
No Flame No Game @proproduct · 38,597 Telegram ranks this channel #8 of 96 here — alongside 95 others — read 31 August 2026
GPT/ChatGPT/AI Central Александра Горного @aioftheday · 44,704 Telegram ranks this channel #8 of 97 here — alongside 96 others — read 29 August 2026
Evening Prophet @eveningprophet · 19,102 Telegram ranks this channel #9 of 94 here — alongside 93 others — read 5 October 2026
GoPractice! @gopractice · 29,379 Telegram ranks this channel #9 of 97 here — alongside 96 others — read 9 September 2026
Tech Crunch @techcrunchru · 16,293 Telegram ranks this channel #10 of 95 here — alongside 94 others — read 5 October 2026
Максим Спиридонов @mspiridonov · 69,976 Telegram ranks this channel #10 of 98 here — alongside 97 others — read 21 August 2026
Игорь Кузнецов о темных паттернах @brainshare · 21,709 Telegram ranks this channel #12 of 93 here — alongside 92 others — read 22 September 2026
Стартап дня. Александр Горный. @startupoftheday · 62,522 Telegram ranks this channel #13 of 97 here — alongside 96 others — read 22 August 2026
kyrillic @kyrillic · 61,215 Telegram ranks this channel #13 of 96 here — alongside 95 others — read 22 August 2026
Matskevich - brains, love and robots @Matskevich · 24,970 Telegram ranks this channel #14 of 98 here — alongside 97 others — read 14 September 2026
Ваня Замесин @zamesin · 50,070 Telegram ranks this channel #14 of 97 here — alongside 96 others — read 25 August 2026
Product Management & AI @ruspm · 25,007 Telegram ranks this channel #16 of 97 here — alongside 96 others — read 14 September 2026
TechSparks @techsparks · 46,744 Telegram ranks this channel #16 of 97 here — alongside 96 others — read 27 August 2026
Индекс дятла @dindex · 22,206 Telegram ranks this channel #20 of 98 here — alongside 97 others — read 21 September 2026
Epic Growth — рост продуктов @epicgrowth · 26,033 Telegram ranks this channel #21 of 97 here — alongside 96 others — read 12 September 2026
Daily Reminder @justakindreminder · 36,347 Telegram ranks this channel #21 of 98 here — alongside 97 others — read 1 September 2026
Rinat Aliev | Channel @telega_Rinata · 20,537 Telegram ranks this channel #23 of 97 here — alongside 96 others — read 4 October 2026
запуск завтра @ctodaily · 33,692 Telegram ranks this channel #23 of 96 here — alongside 95 others — read 4 September 2026
Тёмная сторона / Темнографика @temno · 79,121 Telegram ranks this channel #23 of 99 here — alongside 98 others — read 18 August 2026
Малоизвестное интересное @theworldisnoteasy · 74,331 Telegram ranks this channel #24 of 94 here — alongside 93 others — read 19 August 2026
Карьера в топ от Анны Знаменской @annaznamenskaya · 29,995 Telegram ranks this channel #25 of 98 here — alongside 97 others — read 6 September 2026
This channel appears in 66 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cross-platform identity — Wikidata
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
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 12 November 2026 — this
entry's latest reading, not the date you are reading this.
“EDU” (@ProductsAndStartups), 15,340 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/ProductsAndStartups.
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.