4 measurements spanning 6 days, net +34. 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 5,974–6,018 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
12 Aug 2026, 19:03
6,013
+14
9 Aug 2026, 16:24
5,999
+20
6 Aug 2026, 11:15
5,979
no change
6 Aug 2026, 11:07
5,979
first reading
Engagement
17 posts held, back to 21 May 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 9 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
29.8%
avg views ÷ 6,013 subscribers
Avg views / post
1,790
2 posts measured
Reaction rate
1.23%
reactions ÷ views · ER floor
Posts in window
2
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
Window
Rolling 30 days · latest post in window 2 August 2026
Posts held
17 (21 May 2026 – 2 August 2026)
Views total
3,580
Reactions total
44
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 03:38 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
Video runtime
17m 52s
Average length
2m 14s
Measured directly from 8 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.
Reaction mix
345 reactions across 17 posts, in 18 distinct kinds. The most used accounts for 62.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
216
62.6%
👍
47
13.6%
🤯
18
5.22%
🆒
13
3.77%
🔥
13
3.77%
👏
10
2.90%
😢
6
1.74%
🌚
5
1.45%
🐳
3
0.87%
😱
3
0.87%
👌
2
0.58%
👾
2
0.58%
😐
2
0.58%
⚡
1
0.29%
👀
1
0.29%
💔
1
0.29%
😍
1
0.29%
🤝
1
0.29%
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 17 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 345reactions 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 21 May 2026 to 2 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.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 17 we hold a reading for · 6%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @Design_Stuffs. 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 17 most recent posts we hold for this entry, published 21 May 2026 to 2 August 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.
اگه برای طراحی رابط کاربری دنبال پسزمینههای مینیمال و حرفهای هستید، این ابزار رو از دست ندید.
وبسایت Nucleo یه ابزار رایگان، ساده اما کاربردی برای پترنهای SVG هست.
توی چند ثانیه برای هیروسکشن، لندینگپیج، داشبورد یا صفحههای خالی، پترنهای متنوع بسازید.
میتونید چند پترن رو با هم ترکیب کنید، رنگ و شفافیتشون رو تغییر بدید، همون لحظه نتیجه رو ببینید و در نهایت خروجی SVG آماده بگیرید و مستقیم داخل پروژه استفاده …
✨ اگر در حوزه Product، Design یا AI فعالیت میکنید، این رویداد رو از دست ندید.
از ۳ تا ۷ آگوست، Product School، رویداد آنلاین و رایگان AI Builder Week 2026 رو برگزار میکنه؛
مجموعهای از ورکشاپهای عملی درباره ساخت محصولات مبتنی بر هوش مصنوعی.
توی این رویداد، بیشتر از ۱۰ ورکشاپ عملی برگزار میشه که بهجای صرفا حرف زدن درباره AI، روی ساختن محصول با AI تمرکز دارن.
چیزی که به نظرم این رویداد رو ارزشمندتر میکنه، حضور مدی…
بزرگترین مشکل بعضی از سرویسهای آنلاین ایرانی، نداشتن تعهد به مشتری
هر روز از تحول دیجیتال، اعتماد به سرویسهای ابری و مهاجرت کسبوکارها به ابزارهای آنلاین صحبت میکنیم.
اما یک سؤال اساسی وجود داره:
اگر فردا این سرویس از کار بیفته، چه کسی پاسخگوی مشتریه؟
متأسفانه وینساین فقط یک مثال از این ماجراست.
سرویسی که ما و بسیاری از کسبوکارها، قراردادها و اسناد مهم خودشون رو بهش سپردیم، اما مدتهاست که کاربران از نبود پ…
نسخه جدیدی از ChatGPT برای تغییر تجربه استفاده از AI معرفی شد!
حالا Chat، Work و Codex کنار هم قرار گرفتن تا از تحقیق و برنامهریزی تا ساخت فایل و توسعه نرمافزار، همه داخل یک محیط انجام بشه.
مدلهای جدید GPT-5.6 هم برای کارهای پیچیده، برنامهریزی و خروجیهای آمادهتر طراحی شدن.
به نظرم نکته مهمتر خود Work نیست.
اپنایآی داره مرز بین ابزارهای مختلف رو از بین میبره. همونطور که فیگما با Motion فاصله بین Design …
🔄 با آپدیت جدید ChatGPT روی ویسمدلهاش حالا میتونیم مکالمه بسیار انسانیتری رو تجربه کنیم! بدون مکث و به صورت همزمان 🔥
🔗 جزییات بیشتر
این قابلیت، الان برای تمام کاربران ChatGPT در دسترس هست.
#Ai
🟡 @Design_Stuffs
اگه صاحب کسب و کار هستین و دغدغه جذب و استخدام دارین و روزانه زمان زیادی رو صرف بررسی رزومهها میکنین تا بتونین نیروهایی که مناسب پوزیشن مدنظرتون هستن رو پیدا کنین:
«ورکمارکر» میتونه بهتون کمک کنه تا با معیارهایی که خودتون از پیش تعریف کردین،
رزومههای دریافتی رو براتون به طور اتوماتیک بررسی و تحلیل کنه و درنهایت با صرف زمان کمتر و با دقت بیشتر، بهترین و مناسبتترین کاندیداها رو برای اون موقعیت شغلی پیدا کنین …
🧑💻 با قابلیت جدید Code on the Figma Canvas حالا میشه مستقیم داخل Canvas فیگما با کد کار کرد.
دیگه کد فقط یه خروجی بیرونی نیست؛ تبدیل شده به یه لایه واقعی از طراحی، درست کنار UI و کامپوننتها.
یعنی بهجای اینکه “طراحی → کد” داشته باشیم، کمکم داریم میریم سمت یه حالت ترکیبی:
“طراحی + کد” روی یک بوم مشترک.
نکته مهم اینه که این کدها فقط برای نمایش نیستن؛ میشه باهاشون تعامل ساخت، رفتار تعریف کرد و حتی بخشهایی از تجرب…
🔄 این ابزار جدید Figma Weave که معرفی شد هم به نظرم جالب اومد.
مهمترین ویژگی اینه که Weave فقط یک ابزار ساده برای گرفتن خروجی از AI نیست. اینجا میشه چند مدل مختلف AI رو کنار هم قرار داد و یک Workflow کامل ساخت؛ جایی که هر مدل یک بخش از فرآیند رو انجام میده.
مثلاً یک مدل محتوا تولید کنه، یکی تصویر بسازه، یکی خروجی رو ویرایش کنه و همه اینها داخل یک فضای واحد به هم متصل باشن.
چیزی که جالبه اینه که فیگما دیگه AI رو …
🙂 موشن به فیگما اضافه شد.
یکی از مهمترین فیچرها و ابزارهای معرفی شده در کانفیگ ۲۰۲۶ فیگما موشن بود.
تا امروز برای ساخت انیمیشن و طراحی تعاملات پیشرفته، معمولاً باید بین چند ابزار مختلف جابهجا میشدیم. حالا فیگما این فاصله رو کمتر کرده و امکان ساخت Motion رو مستقیم داخل همون فضای طراحی آورده.
مهمترین ویژگی اینه که حالا میشه با استفاده از Timeline، حرکت عناصر، ترنزیشنها و جزئیات انیمیشن رو با کنترل خیلی دقیقتری ط…
📣 فریمر ۳ معرفی شد.
طراحی سایت، یه قدم بزرگ به سمت هوشمندتر شدن برداشته.
مهمترین تغییرش اضافه شدن Agents هست. دستیارهایی که مستقیم روی Canvas کار میکنن و میتونن لندینگ بسازن، محتوای CMS بنویسن، کامپوننت ایجاد کنن یا ایرادهای سایت رو برطرف کنن، در حالی که کنترل اصلی همچنان دست طراحه.
قابلیت Branching هم اضافه شده تا بتونی بدون دست زدن به نسخه اصلی سایت، ایدههای جدید رو جدا تست کنی و فقط تغییرات موفق رو برگردونی.…
📱 توی این ویدیو، قابلیتهای مدل جدید Claude Fable 5 در زمینه طراحی Interface و Front-End بررسی شده.
تستهای جالبی روی این مدل انجام میشه تا ببینیم چقدر در درک مفاهیم بصری و پیادهسازی کدها پیشرفت کرده.
⬇️ موارد بسیار جذابِ بررسیشده در ویدیو:
・طراحی لندینگپیجهای مدرن با انیمیشنهای Scroll-based
・بازسازی طرحهای پیچیده وب، صرفاً از روی اسکرینشات یا آدرس سایت
・استفاده از ایجنتهای کمکی برای کار با فیگما
・مدرن…
چه تمیز و زیبا :))
Reframing a photo after it’s been taken with Spatial Reframing ✨ The new iOS 27 Apple Intelligence feature demo (Beta)
#WWDC #iOS27
🐦 Ben Geskin
#Tools #Ai
🟡 @Design_Stuffs
🤯18🔥4❤3😱3🐳1👍1
Showing the 12 most recent of 17 posts we hold for @Design_Stuffs. 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 — 637,118 of 1,160,990entries 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 12 August 2026 — this
entry's latest reading, not the date you are reading this.
“Design Stuff” (@Design_Stuffs), 6,013 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/Design_Stuffs.
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.
