Telegram RegisterThe public register of Telegram
Telegram profile photo for Pan

Channel

Pan

@PanSystem

On this record: Growth · Engagement · What this channel posts · Posts · Handles named that no longer answer · Cite this entry

22,764subscribers

-1,521 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002465296934
TypeChannel
Username@PanSystem
DescriptionPayments Acceleration Network
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live22 August 2026
Measurements held15
Confirmed unchanged1 time, most recently 22 August 2026
On Telegramt.me/PanSystem

Growth

22,76424,28523,524.57 August 2026 — 24,285 subscribers7 August 2026 — 24,285 subscribers8 August 2026 — 24,099 subscribers9 August 2026 — 24,062 subscribers10 August 2026 — 23,924 subscribers11 August 2026 — 23,745 subscribers12 August 2026 — 23,568 subscribers14 August 2026 — 23,497 subscribers15 August 2026 — 23,299 subscribers16 August 2026 — 23,156 subscribers17 August 2026 — 23,040 subscribers18 August 2026 — 22,991 subscribers19 August 2026 — 22,835 subscribers20 August 2026 — 22,837 subscribers22 August 2026 — 22,764 subscribers7 August 202622 August 2026
15 measurements spanning 15 days, net -1,521. 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 22,536–24,513 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
22 Aug 2026, 04:0822,764-73
20 Aug 2026, 17:4722,837+2
19 Aug 2026, 21:1422,835-156
18 Aug 2026, 18:4222,991-49
17 Aug 2026, 21:3523,040-116
16 Aug 2026, 21:0623,156-143
15 Aug 2026, 15:2823,299-198
14 Aug 2026, 01:0823,497-71
12 Aug 2026, 18:3423,568-177
11 Aug 2026, 19:1123,745-179
10 Aug 2026, 19:2223,924-138
9 Aug 2026, 19:5324,062-37
8 Aug 2026, 21:0824,099-186
7 Aug 2026, 14:4524,285no change
7 Aug 2026, 14:3424,285first reading

Engagement

29 posts held, back to 7 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 34 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
0.079%
avg views ÷ 22,764 subscribers
Avg views / post
18.0
18 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
18
of 29 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 20 August 2026
Posts held29 (7 July 202620 August 2026)
Views total324
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken22 Aug 2026, 20:38 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

Links
330

Lifetime counters from Telegram’s own channel header, read 22 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.

Recent posts

20 Aug 2026, 15:16 UTC6 viewsread 22 August 2026

Agent compute is not one big bill. It is hundreds of small executions that become visible only after they add up. https://t.co/tRbmilJYPy — PAN (@Pan_Ecosystem) Aug 20, 2026

Signed IFTTT

18 Aug 2026, 19:41 UTC10 viewsread 22 August 2026

14,000 designs. 9 binders. 3 sub-nanomolar. The agent didn't win because it was smart. It won because the loop was closed: design → wet-lab validate → feed back. Autonomous execution only pays off when there's a checkpoint at the end. https://t.co/zyvvLjIMdN — PAN (@Pan_Ecosystem) Aug 18, 2026

Signed IFTTT

18 Aug 2026, 15:11 UTC10 viewsread 22 August 2026

A wallet is not an approval system. If an agent can spend, you need to define: what it can buy, how much it can spend, and when a human must approve. https://t.co/sdhiFPaKlh — PAN (@Pan_Ecosystem) Aug 18, 2026

Signed IFTTT

16 Aug 2026, 18:26 UTC15 viewsread 22 August 2026

Open models do not just create more builders. They create more agent attempts. More experiments. More tool calls. More failed runs. More inference demand. More need to verify what actually happened. The open-source wave expands the execution market, not just the model market. https://t.co/Sg0KVkPqk7 — PAN (@Pan_Ecosystem) Aug 16, 2026

Signed IFTTT

14 Aug 2026, 13:26 UTC19 viewsread 22 August 2026

Agents need receipts. Not screenshots. Not vague logs. A real one should show: intent → compute → verification → payment → result. PAN is building that execution record. https://t.co/i2DVVPjjDD — PAN (@Pan_Ecosystem) Aug 14, 2026

Signed IFTTT

13 Aug 2026, 13:11 UTC20 viewsread 22 August 2026

Training compute is easy to spot. Big clusters. Big budgets. Big announcements. Agent compute will be harder to see. Small jobs. Always running. Spread across tools, apps, and users. Paid for one action at a time. The biggest compute market may be the one nobody sees. https://t.co/rI6uYqRSgb — PAN (@Pan_Ecosystem) Aug 13, 2026

Signed IFTTT

11 Aug 2026, 16:36 UTC17 viewsread 22 August 2026

Training compute is easy to recognize. Big clusters. Big budgets. Big announcements. Agent compute will be harder to see. Small jobs. Always running. Spread across tools, apps, and users. Paid for one action at a time. That market may be much larger than it looks. — PAN (@Pan_Ecosystem) Aug 11, 2026

Signed IFTTT

10 Aug 2026, 13:21 UTC16 viewsread 22 August 2026

Official Announcement Thrilled to partner with @XAgent_official the zero-code platform empowering anyone to Speak to Build custom AI Agents. As the Demand Layer for AI Compute PAN will explore seamless compute access agent-to-agent payments and scalable infrastructure for the https://t.co/mYgOtdDTjz — PAN (@Pan_Ecosystem) Aug 10, 2026

Signed IFTTT

9 Aug 2026, 16:26 UTC16 viewsread 22 August 2026

We’re not trying to make smarter agents. We’re trying to make agent execution something you can actually verify and settle. Intent, compute, payment, result. PAN sits in that loop. — PAN (@Pan_Ecosystem) Aug 9, 2026

Signed IFTTT

7 Aug 2026, 13:16 UTC16 viewsread 22 August 2026

I don’t think the next AI compute wave will look like the last one. Training was big clusters and big headlines. Agents feel different. Smaller jobs. Running constantly. Happening in more places. Messier, but probably much bigger than people expect. https://t.co/5NJBwZaBZV — PAN (@Pan_Ecosystem) Aug 7, 2026

Signed IFTTT

6 Aug 2026, 13:16 UTC18 viewsread 22 August 2026

Once agents start paying for tools and compute, settlement stops being optional. Someone has to prove what was requested, what ran, and who paid. That’s the part we’re building around. https://t.co/cGrVzXVv2s — PAN (@Pan_Ecosystem) Aug 6, 2026

Signed IFTTT

4 Aug 2026, 14:46 UTC19 viewsread 22 August 2026

One question keeps showing up for us at PAN: if agents are going to work all day, where does that work actually run? Not the model. Not the demo. The execution behind it. https://t.co/8tr8Jp4WOU — PAN (@Pan_Ecosystem) Aug 4, 2026

Signed IFTTT

Showing the 12 most recent of 29 posts we hold for @PanSystem. 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.

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

“Pan” (@PanSystem), 22,764 subscribers as measured 22 August 2026. Telegram Register, tgregister.com/channel/PanSystem.

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.