Starting a Session From My Phone Sometimes I am on the road and I need to start a new session from my phone. I can of course connect to the computer through AnyDesk, squint at the screen on my phone, press the "new" button and so on. But that is such a pain. I am thinking maybe it is better to make a Telegram bot that can create a new session itself. I just say: "on this machine, raise a session, start a session"…

Channel
Palo Alto Ai Research Lab \ OpenClaw Hermes N8N Claude GPT etc
@PaloAltoAi
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
164,325subscribers
-2,747 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
Register entry
| Telegram ID | -1001704501466 |
|---|---|
| Type | Channel |
| Username | @PaloAltoAi |
| Description | ⚡️Practical AI automation hub for entrepreneurs. Guides, workflows, and real examples to help you save time, automate business tasks, build faster with OpenClaw, n8n, Claude & GPT, and turn AI into measurable productivity gains. |
| 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 | 17 August 2026 |
| Measurements held | 12 |
| Confirmed unchanged | 1 time, most recently 17 August 2026 |
| On Telegram | t.me/PaloAltoAi |
Topic
Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 100% 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 why it has no browse page of its own yet.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Aug 2026, 20:13 | 164,325 | -316 |
| 16 Aug 2026, 15:14 | 164,641 | -373 |
| 14 Aug 2026, 20:48 | 165,014 | -246 |
| 13 Aug 2026, 13:57 | 165,260 | -180 |
| 12 Aug 2026, 14:18 | 165,440 | -238 |
| 11 Aug 2026, 14:02 | 165,678 | -314 |
| 10 Aug 2026, 13:16 | 165,992 | -240 |
| 9 Aug 2026, 14:16 | 166,232 | -192 |
| 8 Aug 2026, 13:39 | 166,424 | -221 |
| 7 Aug 2026, 16:06 | 166,645 | -279 |
| 6 Aug 2026, 12:42 | 166,924 | -148 |
| 6 Aug 2026, 01:32 | 167,072 | first reading |
Engagement
93 posts held, back to 16 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 27 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.065%
- avg views ÷ 164,325 subscribers
- Avg views / post
- 106
- 90 posts measured
- Reaction rate
- 0.929%
- reactions ÷ views · ER floor
- Posts in window
- 90
- of 93 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 37 of 90 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 17 August 2026 |
|---|---|
| Posts held | 93 (16 July 2026 – 17 August 2026) |
| Views total | 9,581 |
| Reactions total | 47 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 17 Aug 2026, 21:53 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
- ≈805
- Videos
- ≈11
- Links
- ≈1,070
Lifetime counters from Telegram’s own channel header, read 17 August 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.
Reaction mix
34 reactions across 26 posts, in 2 distinct kinds. The most used accounts for 85.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 29 | 85.3% | |
| ❤ | 5 | 14.7% |
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 40 of the 93 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 61reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 93 most recent posts we hold, published 16 July 2026 to 17 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
My Machines Do Not Know How to Say Goodbye Today I was turning on remote access across every session in the fleet. I wanted to see any of them from my phone and keep working inside any of them. My hub sent back the list of nodes the order never reached. Two of my own laptops were on it. The work laptop had not spoken to the fleet in 71 hours. The MacBook, 32. Their heartbeat file had not been updated in nineteen d…
95 Automations, 4 Do Everything Today's insight was about my automations again. I counted my automations in n8n. There are 95. In the last 30 days, 11 ran at least once. Fifty-seven never ran at all. And 99.8% of all runs come from four of the 95. The two most loaded are the alarm-clock and the watchdog: one wakes a machine when a message for it arrives in the work chat, the other checks the machine is still ali…
👍1
The smart zone is shorter than your context window — and your startup files eat it first I started digging into harnesses. Listened to a talk by an engineer on the GigaChat team about how the industry got to today's agents. Strong speaker, real respect for both the delivery and the expertise. His history and his estimates below are his, not ours. Four years, start to finish: Late 2022 — a clean chat. One prompt, o…
Leaving Traces in Every Language I am right now doing deep research on stores, marketplaces and collections of skills for Claude Code, LLMs and other vendors. Particular emphasis on non-English platforms. I am taking the top world languages, starting with the ones most ordinary and most important for us: Chinese, Japanese, Korean, English, Spanish and other popular languages. In short, I need to study every place…
Should You Knock on a Door That Never Opens? I am currently researching skill marketplaces, or some catalogue of skills, and I want to publish all our Claude skills there. I want to point my Claude at it, tell it there are skills there and that it can take them for itself too. I am studying skills for Claude, Codex, Gemini, Grok and so on. I have already taken a few steps. My 101 skills can be installed by anyone…
Looking for the Top 10 Problems Across 300 Sessions Another thing I am doing: analysing all my sessions from the last month — 100, 200, 300 sessions. Particular attention to sessions where I was building something, retro sessions, sessions from all my computers. The task: find the top 10 problems worth fixing. Meaning, find the problems that show up often and that may be stopping my project from working properly. …
👍1
A Fingerprint in Everything You Open-Source Morning thoughts. I am producing a lot of content, skills and so on right now. Everything I make, I open-source. But to understand later whether anyone actually uses my products, it would be good to have some kind of traction signal. To know: right, someone is using my product, even if they modified it a little. So I am thinking about embedding a kind of altered finger…
👍1
The Failure Was Saving Today's failure is the inverse kind. I overdid it. I spent the whole week optimising tokens. Looking at where and how to save, sitting on Opus, actually counting every session. And I was pleased: consumption was down, the resources in Claude Code would last until Saturday. Well, yes. A day before the limits reset, Fable is 95% unspent. The smartest of the models I pay for stood idle for a w…
👍1
Lost Sessions Get a Lightweight Retro I keep accumulating orphaned sessions. I sit down with an agent, get absorbed in the work, close the window, and that is it. The result is written down nowhere, what we built is not recorded, a week later I do not remember it and the agent remembers even less. If a session closes with a retro, there is a breakdown: what we did, what we keep, where it goes. If it does not, there…
👍1
One Ultracode Session Eats the Whole Window I tried burning Fable tokens through effort on ultracode. When you set effort to ultracode, it is not just fun, it is better than Goethe's Faust. The most important thing is that the request be specific, as all-encompassing as possible. So those guys who advise giving Claude as much context as possible, meaning dictating a long, long message where everything is thought …
👍1
Every Peer Exports Its Own LLMs Since the Claudes on different machines can each be tied to their own accounts, every other peer's Claude account may be its own. The same applies to ChatGPT, Grok, Gemini and other LLMs. Therefore we export all dialogues from Claude AI, ChatGPT, Gemini, Grok and the rest locally on each peer. All of it goes into the Vault for future reindexing. I need to think about how to organi…
👍1
Showing the 12 most recent of 93 posts we hold for @PaloAltoAi. 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 — 147,670 of 1,480,975entries 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.
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 17 August 2026 — this entry's latest reading, not the date you are reading this.
“Palo Alto Ai Research Lab \ OpenClaw Hermes N8N Claude GPT etc” (@PaloAltoAi), 164,325 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/PaloAltoAi.
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.