Когда истратил все недельные лимиты на ИИ-агентов уже в понедельник #Humor @MikeBlazerX 🚀Схемы — в MikeBlazerPRO.com / @MikeBlazerPRO
😭5👨💻2👎1🤬1
Signed Mike Blazer

Channel
@MikeBlazerX
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts recorded as deleted · Citations · Telegram's recommendations · Cite this entry
8,959subscribers
+94 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001616788541 |
|---|---|
| Type | Channel |
| Username | @MikeBlazerX |
| Description | Все прелести SEO: — результаты экспериментов — секреты продвижения — свежие идеи — SEO-фишки — кейсы — топы без ссылок Платный PRO-канал: https://t.me/MikeBlazerX/5841 ... Автор: @MikeBlazer Рекламу не продаю! |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 5 November 2026 |
| Measurements held | 22 |
| Confirmed unchanged | 1 time, most recently 5 November 2026 |
| On Telegram | t.me/MikeBlazerX |
Technology — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 79% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Nov 2026, 12:17 | 8,959 | +2 |
| 2 Nov 2026, 10:55 | 8,957 | +4 |
| 30 Oct 2026, 03:09 | 8,953 | +14 |
| 24 Oct 2026, 15:40 | 8,939 | -10 |
| 21 Oct 2026, 11:16 | 8,949 | +12 |
| 14 Oct 2026, 23:19 | 8,937 | +16 |
| 11 Oct 2026, 23:42 | 8,921 | +17 |
| 4 Oct 2026, 23:37 | 8,904 | -3 |
| 26 Sept 2026, 00:18 | 8,907 | -10 |
| 17 Sept 2026, 10:00 | 8,917 | +15 |
| 13 Sept 2026, 16:39 | 8,902 | -4 |
| 9 Sept 2026, 14:59 | 8,906 | -2 |
| 4 Sept 2026, 03:59 | 8,908 | +10 |
| 31 Aug 2026, 12:04 | 8,898 | -16 |
| 28 Aug 2026, 06:44 | 8,914 | +19 |
| 25 Aug 2026, 16:43 | 8,895 | +8 |
| 19 Aug 2026, 00:36 | 8,887 | +8 |
| 16 Aug 2026, 01:48 | 8,879 | +7 |
| 12 Aug 2026, 10:36 | 8,872 | -2 |
| 9 Aug 2026, 16:02 | 8,874 | first reading |
105 posts held, back to 29 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 39 pages of Telegram’s post history, 20 posts per page.
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. It is computed over the 24 of 31 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 November 2026 |
|---|---|
| Posts held | 105 (29 July 2026 – 6 November 2026) |
| Views total | 33,487 |
| Reactions total | 96 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Nov 2026, 22:37 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.
Lifetime counters from Telegram’s own channel header, read 6 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.
Measured directly from 5 videos 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.
434 reactions across 77 posts, in 26 distinct kinds. The most used accounts for 28.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 😁 | 125 | 28.8% | |
| ❤ | 103 | 23.7% | |
| 👍 | 55 | 12.7% | |
| 🤣 | 55 | 12.7% | |
| ✍ | 25 | 5.76% | |
| 🔥 | 13 | 3.00% | |
| 🌚 | 8 | 1.84% | |
| 👎 | 8 | 1.84% | |
| ⚡ | 7 | 1.61% | |
| 😭 | 5 | 1.15% | |
| 🤔 | 5 | 1.15% | |
| 🤬 | 4 | 0.922% | |
| 👨💻 | 3 | 0.691% | |
| 💯 | 3 | 0.691% | |
| 🕊 | 3 | 0.691% | |
| 👌 | 2 | 0.461% | |
| 🆒 | 1 | 0.23% | |
| 🏆 | 1 | 0.23% | |
| 👻 | 1 | 0.23% | |
| 💘 | 1 | 0.23% | |
| 6 further kinds | 6 | 1.38% |
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 87 of the 105 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 470 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 105 most recent posts we hold, published 29 July 2026 to 6 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @MikeBlazerX. 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 105 most recent posts we hold for this entry, published 29 July 2026 to 6 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.
Telegram’s own ‘edited’ marker: 0 of 31 posts held from the last 30 days (0%) 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).
Когда истратил все недельные лимиты на ИИ-агентов уже в понедельник #Humor @MikeBlazerX 🚀Схемы — в MikeBlazerPRO.com / @MikeBlazerPRO
😭5👨💻2👎1🤬1
Signed Mike Blazer
Гугл просто обожает контент IBM. Это, пожалуй, самый впечатляющий перформанс библиотеки контента в B2B, который я когда-либо видел, отмечает Гаэтано Нино ДиНарди. Их директория контента /think/topics/ — это абсолютная машина. Уверен, что идейным вдохновителем этой операции был Брайан Кейси, но это точно была командная работа. Конечно, у них есть преимущество бренда и авторитета IBM, но их контент действительно п…
❤3👎2
Signed Mike Blazer
✅ Теперь в Google Search Console можно посмотреть полный Fetch & Render. Я написал бесплатный букмарклет, который пересобирает всю страницу из отрендеренного Гуглом HTML прямо на вкладке "Скриншот" в URL Inspection, рассказывает Натцир. Скриншот в URL Inspection обрывается примерно на 1,750 px, а у просканированной страницы (той версии, которая уходит в индекс) скриншота вообще нет. Букмарклет показывает страницу…
❤5
Signed Mike Blazer
PRO-совет: заблочить фейковых Googlebot, Applebot и GPTBot можно одним правилом в Cloudflare. Cloudflare уже знает, какие боты реальные. Условный "Googlebot" со случайного VPS не проходит проверку и отлетает в блок. Вот само правило (кастомное WAF-правило, действие Block или Managed Challenge): https://gist.github.com/venelinkochev/69f48afca9817be60ca61f45bdd0c49d Сначала я запустил его как Managed Challenge на…
❤3
Signed Mike Blazer
1. Свежий сайт с минимальным трастом, который собирает приличный объем трафика, делится Иан. DriveInsAmerica.com Директория автокинотеатров, запущенная в январе этого года. Хватит забивать на директории! #Directories #CaseStudies 2. Очень простой и довольно свежий сайт, который собирает сумасшедший объем ежемесячных визитов. Это сайт для сравнения роста. howheight.com: зарегистрирован в марте 2026 года, сейча…
❤1
Signed Mike Blazer
Неоправданно странный SEO-совет: читайте документацию по микроразметке с конца. Обычно мы сначала собираем страницу, а потом решаем, какие типы и свойства Schema описывают её содержимое, отмечает Уоррен Хэнс. Но документация также отлично подсвечивает, чего на странице не хватает. Много лет назад мы работали над медицинским сайтом, где контент писали не врачи, но врачи его проверяли. Изучение документации Schema…
Signed Mike Blazer
Ultimate Migration запущен, пишет Келли С. The Structured Data Company рады объявить о запуске нашего нового проекта — The Ultimate Migration Tool. Если вы когда-нибудь переносили сайт, то знаете, какая это боль — доказывать, успешен ли переезд. Экспорт данных из Google Search Console, возня с табличками и попытки понять: трафик реально восстановился или просто слетели формулы. Поэтому я создала инструмент, кото…
Signed Mike Blazer
Слепой тест ИИ-гуманизаторов фиксирует от 18 до 120 искажений смысла — тулзы переписывают бизнес-обязательства Базовый промпт "rewrite this to sound human" сообщил клиенту, что его возврат на £45 уже прошел — хотя в оригинале было "we're refunding". Тулзы для гуманизации текста выдумывают факты, добавляют или выкидывают обязательства, и в клиентских коммуникациях это несет юридические риски. Еще два провала из те…
Signed Mike Blazer
🚀 На 98% меньше переданных данных по сравнению с Brotli. Всего 50 байт для загрузки CSS-ресурса. Я безумно горжусь этим результатом, которого добился, экспериментируя с новой фичей в браузерах на базе Chromium — use-as-dictionary, которую предложил Гилберто Кокки, делится Джорджо Пеллегрино. Поскольку CSS — это часто критический ресурс, блокирующий рендер, уменьшение его веса может серьезно повлиять на производите…
Signed Mike Blazer
Скриншот ниже относится к метрике «originalContentScore» из слива Content Warehouse API, и речь в нем о сигналах человеческих усилий. Сгенерированные ИИ сайты сейчас доминируют на стороне создания контента, а инициированные ИИ сессии доминируют на стороне его потребления. Гугл будет всё больше и больше опираться на человеческие усилия и оригинальный контент, чтобы отделять источники друг от друга. Внутри сигналов…
❤2
Signed Mike Blazer
Идеальный переезд домена обвалил индексацию на 98% — данные вскрывают скрытый триггер проверки качества Хобби-блог переехал на новый домен строго по учебнику, но в итоге 98% урлов не проиндексировались в отчете Page Indexing. Чек-лист чист: запрос на смену адреса в GSC отправлен, редиректы сопоставлены, внутренняя перелинковка обновлена, новый домен доступен для сканирования, свежий сайтмап сгенерирован. При дета…
✍1
Signed Mike Blazer
Инженерный блог Perplexity раскрывает первый срез — как Photon фильтрует страницы для цитирования Инженерный пост Perplexity о Photon (их перестроенном движке извлечения и ранжирования) зафиксировал падение задержки p99 примерно с 800 мс до 65 мс. Однако главная ценность текста — логика отбора страниц до того, как модель начнет писать ответ. Каждый шард индекса извлекает кандидатов, проводит первичное ранжирование…
Signed Mike Blazer
Showing the 12 most recent of 105 posts we hold for @MikeBlazerX. 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.
We recorded 1 post on @MikeBlazerX as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
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.
Named by 14 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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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.
This channel appears in 10 seed channels' Telegram-generated recommendation lists in total, of which the 9 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 5 November 2026 — this entry's latest reading, not the date you are reading this.
“Mike Blazer” (@MikeBlazerX), 8,959 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/MikeBlazerX.
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.