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Channel

Agentic AI Channel

@AgentiicAI

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

342subscribers

+28 since we began measuring on 4 September 2026

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

Register entry

Telegram ID-1003868654318
TypeChannel
Username@AgentiicAI
CreatedBetween 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded4 September 2026
Last confirmed live13 September 2026
Measurements held4
Confirmed unchanged1 time, most recently 13 September 2026
On Telegramt.me/AgentiicAI

Growth

3143423284 September 2026 — 314 subscribers4 September 2026 — 314 subscribers5 September 2026 — 318 subscribers13 September 2026 — 342 subscribers4 September 202613 September 2026
4 measurements spanning 10 days, net +28. 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 310–346 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Sept 2026, 15:37342+24
5 Sept 2026, 18:20318+4
4 Sept 2026, 01:22314no change
4 Sept 2026, 00:47314first reading

Engagement

17 posts held, back to 10 August 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 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
98.3%
avg views ÷ 342 subscribers
Avg views / post
336
6 posts measured
Reaction rate
3.62%
reactions ÷ views · ER floor
Posts in window
6
of 17 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 1 September 2026
Posts held17 (10 August 20261 September 2026)
Views total2,018
Reactions total73
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken4 Sept 2026, 01:22 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.

Reaction mix

302 reactions across 16 posts, in 4 distinct kinds. The most used accounts for 90.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
27290.1%
👍175.63%
🙏103.31%
👏30.993%

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 16 of the 17 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 302 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 17 most recent posts we hold, published 10 August 2026 to 1 September 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

1 Sept 2026, 19:13 UTC195 views8 reactionsread 4 September 2026

سلام به امیررضا و بقیه دوستان ما غرفه داریم تو سالن 31A (طبقه همکف سالن میلاد)، پلاک ۴۸ اگه تشریف آوردید خوشحال میشم در خدمتتون باشم.

5👏3

Signed Ebrahim Mousavi

1 Sept 2026, 19:05 UTC201 views7 reactionsread 4 September 2026

دوستان من فردا ( چهارشنبه ) میرم نمایشگاه الکامپ. اگر کسی از دوستان در نمایشگاه بود و تمایل داشت همدیگه رو ببینیم و صحبت کنیم، خوش حال می شم از صحبت و آشنایی با شما. بهم پیام بدید اگر تشریف اوردید. @Alef_BEH_1

7

30 Aug 2026, 02:32 UTC392 views21 reactionsread 4 September 2026
Photo

جلسه ۶ از دوره Agentic AI تحت عنوان دیزاین پترن ها و سیستم های حافظه ، منتشر شد. در این جلسه به مبحث طراحی سیستم های حافظه یا Memory برای Agent ها و Chatbot ها می پردازیم. در این جلسه کدنویسی نداریم و کدها روی اسلایدها موشکافی شده اند. بسیار بسیار مبحث مهمی هست و پیش نیاز درک حافظه، دیتابیس های برداری مانند Qdrant و Pinecone هست. تا این جلسه هنوز وارد Agentic AI به اون معنا نشدیم و مبانی و پایه ها رو ساختیم. جلسه

21

29 Aug 2026, 17:51 UTC417 views19 reactionsread 4 September 2026
Photo

جلسه ۵ از دوره Agentic AI منتشر شد. در این جلسه دو دیتابیس بسیار مهم شامل Qdrant و Pinecone رو مورد بررسی عمیق قرار می دهیم، این جلسه شامل مباحث تئوری و اجرای کدهای مربوطه هست. در جلسه بعدی با توجه به تسلط نسبی بر جلسات گذشته، وارد مبحث Memory و دیزاین پترن های حافظه خواهیم شد. لینک جلسه وکتور دیتابیس: https://youtu.be/nuCNGVX8wpQ

16🙏3

26 Aug 2026, 09:20 UTC298 views9 reactionsread 4 September 2026
Forwarded from @djangolearn_irPhoto

تخصص و مهارتت رو الان بساز طرح جدید مکتبخونه با نام "ایران ماهر" فرصتی تازه در اختیار علاقه مندان به یادگیری گذاشت تا بتونیم در کنار هم یک مهارت جدید بیاموزیم و به ارتقای جمعی کمک کنیم. منم مثل همیشه دوره هایی که حس کردم می تونه به این موضوع کمک کنه رو توی این طرح قرار دادم تا دوستان بتونن نهایت استفاده رو از این طرح داشته باشن. به دوره های زیر می تونین با استفاده از راهنمای درج شده دسترسی داشته باشید: - جنگو مقد

9

26 Aug 2026, 09:20 UTC515 views9 reactionsread 4 September 2026

از دوره های تدریس شده توسط مهندس بیگدلی، دوره Fast API برای AI Engineering بسیار بسیار مفید هست، برای تهیه دوره در طرح همدلی مکتب خونه به صورت رایگان کافی ست که دوره رو به سبد خرید اضافه کنید و تیک دسترسی کامل رو بردارید و خرید رو بر اساس اطلاعات گفته شده در این لینک تکمیل کنید. https://mktb.me/xmzu/

🙏63

24 Aug 2026, 13:04 UTC384 views21 reactionsread 4 September 2026

دوستان از اون جایی که دیتابیس PostgreSQL و همین طور مبحث نوشتن Query های SQL یک پیش نیاز جدی هست، در صورت تمایل می تونید از ویدئو ۷ ساعته دکتر فزونی در یوتیوب استفاده کنید و با این دیتابیس آشنا بشید. این دیتابیس جزو سرفصل های ما نیست، ولی یک AI Engineer حتما و حتما باید با دیتابیس و کوئری نوشتن آشنایی مطلوبی داشته باشه. در آینده و وقتی که بخوایم یک LongTerm Memory برای Agent ها طراحی کنیم، بهش نیاز پیدا می کنیم. http

21

23 Aug 2026, 17:48 UTC340 views28 reactionsread 4 September 2026

اگر عمر و فرصتی باقی بود، بعد از این که AI Agent ها و RAG رو در سطح مطلوبی یاد گرفتیم، به کمک کد نویسی با هوش مصنوعی یک نرم افزار واقعی در حوزه Finance رو به صورت کامل ( بک اند و فرانت) رو به طور کامل در طی چندین جلسه پیاده سازی می کنیم، تا ببینیم با کمک AI می تونیم نرم افزارهای کاملا کاربردی و حرفه ای بسازیم.

24👍4

23 Aug 2026, 17:46 UTC349 views19 reactionsread 4 September 2026

در ادامه دوره بسیار با API های مدل های مختلف کار خواهیم کرد. تا جای ممکن باید سعی کنیم هزینه های توسعه رو پایین نگه داریم تا پروژه های متعدد رو پیاده کنیم.

18👍1

23 Aug 2026, 17:43 UTC358 viewsread 4 September 2026

https://agentrouter.org/register?aff=Q2c4 از این لینک هم می تونید معادل 125 تا 175 دلار کردیت ( اعتبار) API Key بگیرید برای استفاده از model های هوش مصنوعی ، کاملا رایگان . فقط این که بهتر هست با اکانت گیت هاب در این سایت Log in کنید.

22 Aug 2026, 11:52 UTC982 views23 reactionsread 4 September 2026
Photo

سلام دوستان جلسه ۴ ، به طور کامل به مبحث Embedding اختصاص داره. خودمم تعجب می کنم که ۲ ساعت درباره Embedding صحبت کردم هم تئوری داشتیم و هم کد نویسی. البته رویکرد ما این جا یک رویکرد عملی و استفاده از امبدینگ برای حل مسائل مهندسی هست. اگر مایل بودید درباره امبدینگ بیشتر یاد بگیرید و مدل های امبدینگ رو آموزش بدید، باید برید سراغ کورس های NLP و دیپ لرنینگ. فایل ها هم بعد از اتمام یکی دو جلسه آینده در اختیارتون قرار می

22🙏1

21 Aug 2026, 19:45 UTC352 views39 reactionsread 4 September 2026

دوستتان سلام، قسمت Embedding هم رکورد شد. ۲ ساعت و ۱۰ دقیقه راجع به امبدینگ صحبت کردیم و پیاده سازی هم داشتیم. فقط به خاطر مشکلات اینترنت خیلی کند آپلود می شد که آپلود ویدئو موکول شد به تایمی که سرعت اینترنت و کیفیت vpn بهتر باشه. جلسه بعدی راجع به ۲ تا دیتابیس برداری Qdrant و Pinecone هست که در محصولات واقعی و تجاری به وفور استفاده می شن. تا جای ممکن باید سعی کنیم سریع بریم جلو و مباحث رو هم عمیق و هم تا جای ممکن

34👍5

Showing the 12 most recent of 17 posts we hold for @AgentiicAI. 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.

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.

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 13 September 2026 — this entry's latest reading, not the date you are reading this.

“Agentic AI Channel” (@AgentiicAI), 342 subscribers as measured 13 September 2026. Telegram Register, tgregister.com/channel/AgentiicAI.

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.