Telegram RegisterThe public register of Telegram

Channel

AI Lab

@AISystemAgentLab

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

5,207subscribers

-74 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1003308303690
TypeChannel
Username@AISystemAgentLab
DescriptionPractical AI workflows, agents and automation systems for people, founders and businesses. No hype. Just useful systems. Buy ads: https://telega.io/c/AISystemAgentLab ADS: CITYTRAVEL (Flight tickets) https://shp.pub/7c3sd1?erid=2SDnjeJxX1C
CreatedBetween 1 November 2025 and 28 February 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live10 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 10 August 2026
On Telegramt.me/AISystemAgentLab

Growth

5,2075,2815,2447 August 2026 — 5,281 subscribers7 August 2026 — 5,274 subscribers10 August 2026 — 5,207 subscribers7 August 202610 August 2026
3 measurements spanning 4 days, net -74. 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 5,196–5,292 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
10 Aug 2026, 15:315,207-67
7 Aug 2026, 11:155,274-7
7 Aug 2026, 01:165,281first reading

Engagement

25 posts held, back to 19 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 8 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
6.28%
avg views ÷ 5,207 subscribers
Avg views / post
327
25 posts measured
Reaction rate
0.443%
reactions ÷ views · ER floor
Posts in window
25
of 25 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. It is computed over the 21 of 25 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 11 August 2026
Posts held25 (19 July 202611 August 2026)
Views total8,175
Reactions total32
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 04:37 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.

What this channel posts

Photos
138
Videos
10
Links
79

Lifetime counters from Telegram’s own channel header, read 12 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

32 reactions across 19 posts, in 3 distinct kinds. The most used accounts for 40.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍1340.6%
1031.3%
🔥928.1%

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 21 of the 25 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 32reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 25 most recent posts we hold, published 19 July 2026 to 11 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

11 Aug 2026, 06:48 UTC119 viewsread 12 August 2026
Photo

Your inbox is not a writing problem. It is a decision queue. Most people ask AI to reply to emails. Too early. First, make it choose the action. 4 lanes: REPLY NOW - a real next step, and you own it. AI drafts; you send. DELEGATE - create a clean handoff for the right owner. WAIT - another person, date or missing detail comes first. Set a follow-up trigger. ARCHIVE - no action. Keep it searchable, not attention-hu

Signed BotAdminAIWorkflowLab

10 Aug 2026, 09:33 UTC168 views0 reactionsread 12 August 2026
Photo

Stop looking for one perfect AI. Build a 3-lane AI task router instead. The useful question is not "Which model is best?" It is: "Which model should handle this job?" FAST LANE Summaries, extraction, rewrites, inbox drafts, first-pass research. Use a fast, low-cost model. DEEP LANE Strategy, product specs, hard reasoning, coding and reviews. Use your strongest model. CREATIVE LANE Hooks, campaign angles, scripts

Signed BotAdminAIWorkflowLab

8 Aug 2026, 14:24 UTC220 views1 reactionsread 12 August 2026
Photo

New here, or lost in the feed? 10 AI Lab practical materials worth saving: FULL PDF GUIDES 1. First AI Telegram bot - https://t.me/AISystemAgentLab/106 2. Personal Task Bot with Memory - https://t.me/AISystemAgentLab/119 3. OpenClaw Practical Guide - https://t.me/AISystemAgentLab/122 4. AI Customer Reply Assistant - https://t.me/AISystemAgentLab/173 PRACTICAL STARTERS 5. Market Research Tracker - https://t.me/AISy

🔥1

Signed BotAdminAIWorkflowLab

8 Aug 2026, 05:53 UTC216 viewsread 12 August 2026
Photo

Scope creep rarely arrives as a big demand. It usually sounds like: "While you're there, can we also add this?" Use AI as a Scope Creep Detector before you say yes. Keep one approved scope note: outcome | deliverables | timeline | exclusions | assumptions Then use this prompt: "Compare this new request with the approved project brief. Categorize every element as: within scope, clarification needed, new work, or r

Signed BotAdminAIWorkflowLab

7 Aug 2026, 06:59 UTC230 viewsread 12 August 2026
Photo

Your best marketing language is probably already in your inbox. Build an AI Proof Vault: a library of real, checkable customer evidence for sales, landing pages, content and case studies. For every useful signal, save: verbatim quote | source | outcome claimed | context | proof status | possible use Prompt: "Extract only explicit customer claims and verbatim quotes from these messages. Return: exact quote, source,

Signed BotAdminAIWorkflowLab

6 Aug 2026, 07:23 UTC232 views3 reactionsread 12 August 2026
Photo

Do not let AI "clean" a spreadsheet in one click. First make it explain what it wants to change. AI Spreadsheet Cleanup: 1. Work on a copy. Keep raw data untouched. 2. Ask for a read-only Data Health Report: types, blanks, duplicate candidates, inconsistent labels, suspicious values and uncertain cases. 3. Request a Cleanup Plan: every transformation, why it matters, affected rows and possible loss. 4. Apply only

2👍1

Signed BotAdminAIWorkflowLab

5 Aug 2026, 08:25 UTC237 views1 reactionsread 12 August 2026
Photo

Most people test AI tools the wrong way. They ask: "What can this do?" Ask: "Can this improve one real job this week?" Use an AI Experiment Card: 1. Job - exact repeat to improve 2. Baseline - current time and quality 3. Real sample - five actual examples 4. AI setup - one tool, one prompt 5. Review - accuracy, usefulness, tone, time saved 6. Decision - scale, improve, or leave it alone Prompt: "Turn this idea i

🔥1

Signed BotAdminAIWorkflowLab

4 Aug 2026, 07:28 UTC270 views0 reactionsread 12 August 2026
Photo

Do not automate a task just because AI can do it. First find the friction worth removing. Try an AI Friction Log for five workdays. Every time work slows down, record: trigger | friction | frequency | minutes lost | current workaround | error risk Do not solve anything yet. Collect evidence. Then ask AI: "Cluster repeated problems and rank them by frequency x time lost x error risk. For the top 3, recommend: eli

Signed BotAdminAIWorkflowLab

3 Aug 2026, 13:37 UTC288 views1 reactionsread 12 August 2026
Photo

Most work does not get stuck because you forgot a task. It gets stuck because you forgot who has the next move. Build an AI Waiting List. Track anything you cannot move forward alone: client approval, teammate's file, vendor quote, promised intro, manager's decision. Use six fields: item | waiting on | why it matters | last touch | due date | next move Weekly prompt: "Review this waiting list. Flag overdue items

🔥1

Signed BotAdminAIWorkflowLab

2 Aug 2026, 07:09 UTC319 views1 reactionsread 12 August 2026
Photo

Your network does not need more DMs. It needs better memory. AI Relationship Radar Important people can disappear behind urgent work: a client you promised to update, a former colleague who needs an intro, a mentor you meant to thank. Build one private table: person | context | last exchange | open loop | next helpful action | next review date Then run a 15-minute weekly AI review: "Identify promised follow-ups,

👍1

Signed BotAdminAIWorkflowLab

1 Aug 2026, 05:05 UTC325 views1 reactionsread 12 August 2026
Photo

Do not use AI to win a hard conversation. Use it to prepare for one. Before a feedback talk, client reset, salary conversation or cofounder disagreement, ask AI to separate what happened from the story you are telling yourself. 1. Paste a redacted situation: your goal, relationship, facts, what you need and the outcome that is not acceptable. 2. Prompt: "Act as a neutral conversation-prep coach. Separate: facts,

👍1

Signed BotAdminAIWorkflowLab

31 Jul 2026, 19:34 UTC308 views1 reactionsread 12 August 2026
Photo

Your AI is not always hallucinating. Sometimes it is faithfully repeating an old document. Pricing sheets, FAQs, sales decks and SOPs quietly expire. Then an AI assistant gives a confident answer that was correct six months ago. Run a Knowledge Decay Audit. 1. Start with pricing, policies, product availability, customer FAQs, sales materials and operational instructions. 2. Prompt: "Audit these documents for kn

1

Signed BotAdminAIWorkflowLab

Showing the 12 most recent of 25 posts we hold for @AISystemAgentLab. 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 — 460,576 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.

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

“AI Lab” (@AISystemAgentLab), 5,207 subscribers as measured 10 August 2026. Telegram Register, tgregister.com/channel/AISystemAgentLab.

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.