Technology — 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 16 September 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
15 measurements spanning 61 days, net -50. 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 2,165–2,230 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
6 Oct 2026, 06:37
2,172
-7
29 Sept 2026, 13:19
2,179
-2
16 Sept 2026, 03:38
2,181
-5
12 Sept 2026, 01:57
2,186
-2
7 Sept 2026, 15:16
2,188
-10
2 Sept 2026, 18:16
2,198
-2
30 Aug 2026, 08:12
2,200
-1
27 Aug 2026, 10:39
2,201
-3
24 Aug 2026, 12:07
2,204
-8
20 Aug 2026, 20:23
2,212
-3
17 Aug 2026, 10:24
2,215
+1
14 Aug 2026, 01:47
2,214
-4
10 Aug 2026, 15:22
2,218
-4
7 Aug 2026, 10:37
2,222
no change
6 Aug 2026, 16:13
2,222
first reading
Engagement
21 posts held, back to 28 June 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 2 pages 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 21 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
91 reactions across 20 posts, in 13 distinct kinds. The most used accounts for 34.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
31
34.1%
🔥
27
29.7%
👍
11
12.1%
✍
6
6.59%
🆒
4
4.40%
👀
3
3.30%
🤔
3
3.30%
👏
1
1.10%
👾
1
1.10%
😁
1
1.10%
😎
1
1.10%
🤩
1
1.10%
🥰
1
1.10%
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 20 of the 21 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 91 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 28 June 2026 to 7 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
14
across the posts below
Posts paid on
11
of 21 we hold a reading for · 52%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @the_dev_signal. 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 21 most recent posts we hold for this entry, published 28 June 2026 to 7 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.
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Exploring the Advancements of GPT-5.6: A Game-Changer in AI
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Revolutionizing Tokenization: Meet GigaToken for Lightning-Fast Language Models
GigaToken introduces a groundbreaking approach to language model tokenization, achieving speeds approximately 1000 times faster than traditional methods. This innovation is poised to significantly enhance the efficiency of AI applications and research in natural language processing.
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Obsidian-TUI: Your Obsidian Vault in the Terminal
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Unveiling PGSimCity: A Deep Dive into PostgreSQL's Inner Workings
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Google Backs OpenWeight Models: A Shift in AI Dynamics
Google's endorsement of OpenWeight models signifies a major shift in the AI landscape, positioning itself against Anthropic and other tech giants. This could lead to increased collaboration and innovation in the development of open AI technologies.
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Speed Up Your Neovim Experience with This Navigation Plugin
A developer showcases a newly created plugin that enhances visual line navigation in Neovim, promising to streamline the coding process. This tool could significantly boost productivity for Neovim users looking for efficient navigation solutions.
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From Rust to Zig: Insights on Our Code Rewrite Journey
This article offers an in-depth look at the process of rewriting a codebase from Rust to Zig, discussing the challenges and benefits encountered along the way. Such real-world experiences provide valuable lessons for software engineers considering similar transitions in their projects.
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Meet LM Studio Bionic: Your New AI Agent for Open Models
LM Studio Bionic emerges as a powerful AI agent designed specifically for managing and deploying open models, providing developers with a robust tool for enhancing productivity in AI projects. Its capabilities promise to streamline workflows and foster innovation in the AI landscape.
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Why Rust is the Future: Insights from Linux's Shift Away from C
Greg Kroah-Hartman highlights the growing trend of Linux transitioning from C to Rust, emphasizing Rust's advantages in safety and developer satisfaction. This shift could reshape the landscape of system programming, making it more accessible and efficient for developers.
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Claude Code vs. OpenCode: A Token Showdown
In a comparative analysis, Claude Code sends a staggering 33k tokens before even reading the prompt, while OpenCode limits this to 7k. This difference highlights the varying approaches to processing user input in language models and their implications for efficiency.
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❤2🔥1
Showing the 12 most recent of 21 posts we hold for @the_dev_signal. 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.
Mentions
Named by 1 registered channel — 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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
🤖 Coding News ⚡️ @CodingNews · 22,996 Telegram ranks this channel #7 of 68 here — alongside 67 others — read 19 September 2026
Learn Programming تعلم البرمجة @SuDevelopers · 27,001 Telegram ranks this channel #34 of 60 here — alongside 59 others — read 11 September 2026
ኦርቶዶክስ ተዋሕዶ ጥያቄና መልስ @orthotew · 25,120 Telegram ranks this channel #67 of 69 here — alongside 68 others — read 14 September 2026
LEARN WITH KAVYA @learn_with_kavya · 26,738 Telegram ranks this channel #67 of 70 here — alongside 69 others — read 11 September 2026
This channel appears in 4 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 6 October 2026 — this
entry's latest reading, not the date you are reading this.
“Dev Signal” (@the_dev_signal), 2,172 subscribers as measured 6 October 2026. Telegram Register, tgregister.com/channel/the_dev_signal.
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.