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Никита | AI & Startups

@nikita_ai_web3

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

352subscribers

+0 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1002323452414
TypeChannel
Username@nikita_ai_web3
Description22 года. Строю продукты на AI, делаю MVP за 3–7 дней, ищу первых клиентов и выручку. Здесь: — как быстро проверять идеи — как делать рабочие прототипы без команды — реальные кейсы — разборы новых AI-инструментов Для связи @AtikinNT
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live13 August 2026
Measurements held2
On Telegramt.me/nikita_ai_web3

Growth

3526 Aug 2026, 05:38 — 352 subscribers6 Aug 2026, 21:17 — 352 subscribers6 Aug 2026, 05:386 Aug 2026, 21:17
2 measurements taken within a single day. 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 351–353 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
6 Aug 2026, 21:17352no change
6 Aug 2026, 05:38352first reading

Engagement

15 posts held, back to 10 July 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
37.7%
avg views ÷ 352 subscribers
Avg views / post
133
14 posts measured
Reaction rate
5.92%
reactions ÷ views · ER floor
Posts in window
14
of 15 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 3 August 2026
Posts held15 (10 July 20263 August 2026)
Views total1,857
Reactions total110
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Aug 2026, 21:17 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
483
Videos
31
Links
203

Lifetime counters from Telegram’s own channel header, read 6 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

125 reactions across 15 posts, in 10 distinct kinds. The most used accounts for 43.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥5443.2%
😁1713.6%
1512.0%
👍1411.2%
🦄108.00%
👀54.00%
🤔43.20%
32.40%
😱21.60%
👾10.8%

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 15 of the 15 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 125reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 10 July 2026 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.

Recent posts

3 Aug 2026, 22:24 UTC63 views8 reactionsread 6 August 2026
Photo

Обновление FondBond.tech 🔥 Теперь доступно подключение через 💙 Зачем это было нужно? Всё упирается в цифры. Мы видели целую группу пользователей, которые не смогли пройти этап воронки по подтверждению почты. Поэтому было принято решение сделать быстрый и удобный вход через ВК. Собственно, по нашему законодательству у нас остался только ВК да Яндекс) А те, у кого уже есть личный кабинет, могут просто привязать акка

🔥6👍1🦄1

2 Aug 2026, 09:49 UTC93 views6 reactionsread 6 August 2026

😶 Как же тяжело править другие навалябкоженные проекты... Если начинать проекты с помощью AI, не учитывая, что AI должен быстро и просто в них разбираться, получается просто ужас. Коротко о нагоревшем: 🔴файлы по 4 тыс. строк на JS или TS 🔴просто море мёртвого кода 🔴отсутствие документации или, что ещё хуже, наличие устаревшей документации 🔴100500 зависимостей библиотек, которые можно было заменить одним open-source

3🔥3

31 Jul 2026, 19:52 UTC111 views4 reactionsread 6 August 2026
Photo

Может, кто-то не в курсе, но сегодня DeepSeek всех опять удивил. Компания выпустила Flash-модель, которая находится на одном уровне с GLM 5.2, Gemini Flash 3.6 и Kimi K3 (low). На Reddit уже ждут релиза от MiniMax 😮 #ai

😁2😱2

31 Jul 2026, 18:10 UTC108 views5 reactionsread 6 August 2026

Услышал интересную мысль про будущее AI 🤔 Отмотаем на 100 лет назад, к буму автоматизации в производстве. В отчёте 100 Years of U.S. Consumer Spending есть классный пример с одеждой. Раньше платье стоило ~20% от месячной зарплаты, и на него реально копили Пришли заводы и цена упала до ~1,2%. И знаете что? Тратить на одежду стали больше. Цена снизилась, выбор вырос, ценность одной вещи упала - люди просто стали пок

🤔4🔥1

29 Jul 2026, 19:29 UTC133 views11 reactionsread 6 August 2026
Photo

Хочу поделиться готовыми MCP для Яндекс Метрики и Яндекс Вебмастера ⚡️ Недавно (вчера) мы в ФондБонд упёрлись в тупик. Было непонятно, за что хвататься в первую очередь: 🔵пилить новые фичи? 🔵менять дизайн? 🔵запускать рекламу? 🔵делать рассылку? В какой-то момент мы осознали, что просто гадаем на кофейной гуще ☕️. Нужно было срочно опираться на цифры, начал разбираться. И тут меня озарило: Мне банально лень ковырять

🔥73👍1

27 Jul 2026, 20:44 UTC138 views6 reactionsread 6 August 2026
Photo

Мне сильно не нравилось, что у нас был нейрослоп на сайте 😶 И вот вчера вечером я нашёл скилл, который это фиксит. Называется /hallmark (ссылка на сайт). А результат можете увидеть на скринах 🖼 На самом деле очень удивился, насколько круто может получиться, если даже немного убрать ИИ-паттерны. А ещё из интересного у этого навыка есть: 🔵режим аудита на нейрослоп 🔵режим правок 🔵режим полного редизайна Всем советую

🔥6

27 Jul 2026, 18:37 UTC147 views12 reactionsread 6 August 2026
File

Это чистая правда ребят, без рофла 🔩 #startup

😁7🔥3🦄2

27 Jul 2026, 07:09 UTC150 views9 reactionsread 6 August 2026
File

Федеральный закон от 26.07.2026 № 243-ФЗ "О поддержке развития технологий искусственного интеллекта в Российской Федерации" 🔗Ссылка

👀52👍2

26 Jul 2026, 09:21 UTC159 views11 reactionsread 6 August 2026
Photo

Большой апдейт в FondBond.tech 🚀 Сильно улучшил алгоритм ребалансировки портфеля. Что изменилось: 🔵Конкретные рекомендации: теперь алгоритм точечно предлагает, какие именно неоптимальные позиции продать, а какие — купить. Раньше это было просто сравнение с «лучшим» портфелем на данных. 🔵Обновлённый UI/UX: сделал интерфейс понятнее и нагляднее для пользователей. Следующий этап — гибкая настройка подборок и возможнос

🔥6👍32

24 Jul 2026, 20:11 UTC142 views5 reactionsread 6 August 2026
Photo

Реально Kimi K3 хуже Fable 5 всего на 0,44 % и дешевле в ~3 раза 🙂 ссылка на пруф #ai

3🔥2

24 Jul 2026, 20:01 UTC135 views6 reactionsread 6 August 2026

Затестил Kimi K3 на алгоритме оптимизации облигаций на FondBond.tech Это зверь! Круто разобрал алгоритм по деталям и выделил недоработанные места... Очень глубоко думает по шагам, разбирает суть алгоритма и продуктовые User Story сразу. Не надо ничего добавлять в плане инструкций или промптов. Хотя мб у меня просто промпты изначально хорошие 😎 Вышла она относительно недавно, и это open source Fable 5 по всем бенчам

🔥3👍2👾1

23 Jul 2026, 18:57 UTC163 views6 reactionsread 6 August 2026
Photo

Пока вникал в то, что пропустил за последние две недели, наткнулся на интересный дашборд от OpenRouter Это статистика использования моделей по языкам. Решил сравнить три из них: 🔵Русский 🔵Немецкий 🔵Арабский Сравнивать с английским (США) или китайским вообще неинтересно, там и так всё предсказуемо. Выводы очевидны: везде лидируют китайские open-source модели. Только в арабском сегменте еще как-то держатся решения о

🔥6

Showing the 12 most recent of 15 posts we hold for @nikita_ai_web3. 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.

Citation-graph rank

Citation-graph rank — 294,520 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

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 2 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.

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

“Никита | AI & Startups” (@nikita_ai_web3), 352 subscribers as measured 6 August 2026. Telegram Register, tgregister.com/channel/nikita_ai_web3.

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.