Applicable not only to research but also to other aspects of a professional career that require analysis to improve processes
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Channel
@on_my_road
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry
477subscribers
-2 since we began measuring on 10 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001634069157 |
|---|---|
| Type | Channel |
| Username | @on_my_road |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/on_my_road |
Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 21 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 15:19 | 477 | -1 |
| 31 Aug 2026, 18:43 | 478 | -1 |
| 10 Aug 2026, 10:20 | 479 | no change |
| 10 Aug 2026, 08:46 | 479 | first reading |
14 posts held, back to 13 May 2025 — the 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 14 posts for this entry, the most recent from 28 December 2025. An engagement rate over an empty window would be a number about nothing.
Measured directly from 1 video 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.
444 reactions across 14 posts, in 14 distinct kinds. The most used accounts for 34.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 155 | 34.9% | |
| 👍 | 124 | 27.9% | |
| 🔥 | 99 | 22.3% | |
| 🏆 | 20 | 4.50% | |
| ❤🔥 | 10 | 2.25% | |
| 💯 | 9 | 2.03% | |
| ✍ | 6 | 1.35% | |
| 🎉 | 6 | 1.35% | |
| 🤯 | 6 | 1.35% | |
| 🍾 | 3 | 0.676% | |
| 🤔 | 2 | 0.45% | |
| 🤩 | 2 | 0.45% | |
| 👀 | 1 | 0.225% | |
| 🤝 | 1 | 0.225% |
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 14 of the 14 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 444 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 14 most recent posts we hold, published 13 May 2025 to 28 December 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @on_my_road. 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 14 most recent posts we hold for this entry, published 13 May 2025 to 28 December 2025. 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.
Applicable not only to research but also to other aspects of a professional career that require analysis to improve processes
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Ilmiy maqola yozish siri: Shokli modeli Nima uchun ba'zi olimlar juda ko'p maqola chop etadi, boshqalari esa kam? 1957-yilda Nobel mukofoti sovrindori Uilyam Shokli ajoyib tadqiqot o'tkazadi. U Bell laboratoriyasida ishlagan davrda barcha xodimlarning ilmiy samaradorligini o'rganadi va qiziq natijani topadi: samaradorlik logarifmik-normal taqsimlanganini ko'radi. Ya'ni, ko'pchilik olimlar kam maqola yozadi, faqat oz…
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The Era of Agentic Commerce The next big thing in AI will likely be AI agents that buy products and book services for you with minimal human involvement. Some projections suggest that AI agents could orchestrate up to $5 trillion in global spending by 2030. We’re moving from “Click-to-Buy” to “Intent-to-Execute” where you don’t browse or compare, you simply tell an agent what you want, and it gets it done. For the …
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The Hidden Power of B2B Telecommunications🌐 One of the best parts of working in consulting is getting exposure to industries you’d never imagine working in and discovering how they actually operate. Last summer I was deep in the utilities sector, learning how they quietly power the AI revolution. This time, I found myself exploring the fascinating world of telecommunications. At first, most people think of the usu…
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Quick life update: 🏙 Moved to Dallas 🤠 🏛 Starting a new job!
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In my last post, I wrote about how AlphaFold used AI to crack the decades-long puzzle of protein folding, earning its creators a Nobel Prize and transforming biology. But the story doesn’t stop there. Just a few weeks ago, OpenAI revealed its own move into biology with a model built for longevity science. Instead of predicting protein shapes like AlphaFold, this model actually designs new proteins. Working with Ret…
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We all know different use cases of ubiquitous AI such as writing emails, making TikTok clips, or automating call centers. But AI is starting to do something far bigger: it’s changing the way we do science. Take the protein-folding problem. For half a century, scientists struggled to predict how a simple chain of amino acids twists itself into the 3D shapes that power life. The challenge was so complex that many thou…
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Why the Healthcare Industry Is Massively Underrated A lot of people don’t realize just how huge healthcare industry is. It isn’t just hospitals and insurance, it’s a vast ecosystem that touches almost every part of life and the economy. Here are some statistics in case you missed: -In the U.S. alone, healthcare spending exceeds $4.5 trillion a year and accounts for about 18% of U.S. GDP, making it one of the larges…
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Over and over again, I see people not realizing they are becoming victims of the sunk cost fallacy and getting stuck in things, deals, products, and relationships that no longer make them happy and that they would be much better off leaving behind. The sunk cost fallacy happens when we keep committing resources to something simply because we’ve already invested, even if the best choice is to walk away. It quietly dr…
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mind blowing power of compounding and investing in passive index founds
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This experiment is a powerful reminder that we must actively cultivate the ability to learn and adapt even when we haven't directly experienced something before. This is the essence of "range" building a mental "Swiss Army knife" of reasoning tools that apply broadly, not just narrowly within one field. Modern life "requires range, making connections across far-flung domains and ideas". On a final note, this really …
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During my break between now and starting my job in September, I picked up some books. One of them, "Range: Why Generalists Triumph in a Specialized World" by David Epstein, is a massive global hit, challenging our ideas about careers, education, and success. What truly surprised me was seeing Uzbekistan mentioned right there in its pages! Epstein's book champions the idea that having a broad range of experiences an…
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Showing the 12 most recent of 14 posts we hold for @on_my_road. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“On the Road” (@on_my_road), 477 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/on_my_road.
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.