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Channel

404 KIDS SEE GHOSTS (生产力之王版

@isaiahsystem

On this record: Topic · Growth · Engagement · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry

13,563subscribers

-12 since we began measuring on 6 August 2026

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

Register entry

Telegram ID-1001407174982
TypeChannel
Username@isaiahsystem
CreatedBetween 1 April 2019 and 30 November 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live26 September 2026
Measurements held32
Confirmed unchanged1 time, most recently 26 September 2026
On Telegramt.me/isaiahsystem

Topic

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 11 September 2026 and assigned it the closest of 31 fixed categories, at 69% 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

13,53913,57513,5576 August 2026 — 13,575 subscribers7 August 2026 — 13,573 subscribers8 August 2026 — 13,569 subscribers9 August 2026 — 13,568 subscribers10 August 2026 — 13,569 subscribers11 August 2026 — 13,562 subscribers12 August 2026 — 13,561 subscribers13 August 2026 — 13,565 subscribers14 August 2026 — 13,559 subscribers16 August 2026 — 13,555 subscribers18 August 2026 — 13,551 subscribers19 August 2026 — 13,549 subscribers20 August 2026 — 13,548 subscribers21 August 2026 — 13,553 subscribers22 August 2026 — 13,548 subscribers24 August 2026 — 13,550 subscribers25 August 2026 — 13,545 subscribers26 August 2026 — 13,539 subscribers27 August 2026 — 13,543 subscribers28 August 2026 — 13,545 subscribers31 August 2026 — 13,543 subscribers1 September 2026 — 13,545 subscribers2 September 2026 — 13,541 subscribers3 September 2026 — 13,544 subscribers5 September 2026 — 13,541 subscribers9 September 2026 — 13,551 subscribers11 September 2026 — 13,539 subscribers13 September 2026 — 13,542 subscribers15 September 2026 — 13,540 subscribers17 September 2026 — 13,568 subscribers19 September 2026 — 13,573 subscribers26 September 2026 — 13,563 subscribers13,5636 August 202626 September 2026
32 measurements spanning 51 days, net -12. 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 13,534–13,580 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)SubscribersChange
26 Sept 2026, 11:3913,563-10
19 Sept 2026, 13:3813,573+5
17 Sept 2026, 02:3813,568+28
15 Sept 2026, 01:5813,540-2
13 Sept 2026, 12:5613,542+3
11 Sept 2026, 18:2113,539-12
9 Sept 2026, 02:5713,551+10
5 Sept 2026, 17:2013,541-3
3 Sept 2026, 17:2113,544+3
2 Sept 2026, 07:0713,541-4
1 Sept 2026, 04:4513,545+2
31 Aug 2026, 02:1313,543-2
28 Aug 2026, 23:5213,545+2
27 Aug 2026, 20:2813,543+4
26 Aug 2026, 17:2613,539-6
25 Aug 2026, 14:4513,545-5
24 Aug 2026, 11:4813,550+2
22 Aug 2026, 21:3513,548-5
21 Aug 2026, 12:5913,553+5
20 Aug 2026, 12:1313,548first reading

Engagement

39 posts held, back to 16 May 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 50 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
7.17%
avg views ÷ 13,563 subscribers
Avg views / post
973
7 posts measured
Reaction rate
0.617%
reactions ÷ views · ER floor
Posts in window
7
of 39 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 2 September 2026
Posts held39 (16 May 2026 – 2 September 2026)
Views total6,811
Reactions total42
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken2 Sept 2026, 20:08 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.

Reaction mix

275 reactions across 37 posts, in 10 distinct kinds. The most used accounts for 35.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤9835.6%
👍6624.0%
💅3713.5%
🔥279.82%
❤‍🔥196.91%
🆒103.64%
🙉103.64%
🎉41.45%
👏20.727%
🗿20.727%

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 37 of the 39 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 275 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 39 most recent posts we hold, published 16 May 2026 to 2 September 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

2 Sept 2026, 11:01 UTC438 views5 reactionsread 2 September 2026

Tools for Science丨那些面向科研的知识生产协议 最近在深度研究和实践 Discourse Graphs,又发现了不少类似模型和开放科学架构。它们基于 QUE(Question, Claim, Evidence)结构进行知识处理和生产,无论写作、研究以及创意生产,或科学发现、人文研究,都大有裨益。 Discourse Graphs: 它把问题(Question)、主张(Claim)、证据(Evidence)和项目(Project)组织成可查询的论证图谱,让主张可以查看内容回答、由什么支撑或反对,都能被溯源检查。研究成为可以持续修正、生长,共同维护的知识图谱。目前 Roam Research 和 Obsidian 都有官方插件。 https://discoursegraphs.com/ MIRA: 另一种开放的科研数据结构与互操协议,它让主张、证据、研究方案等知识单元带着来源和作者信息,在不同工具之间流通,共享…

👍4❤1

Signed 志筑仁美

1 Sept 2026, 12:49 UTC787 views6 reactionsread 2 September 2026
Photo

给每一分钟一份工作丨Nautilus Log 的时间管理哲学 https://mp.weixin.qq.com/s/zo7f_2aj0XSwarOUHe_JzQ 如何感知时间?[[Nautilus Log]] 完整内容已经写成文章发布在公众号,欢迎阅读。#Original

❤‍🔥2🆒2❤1👏1

Signed 志筑仁美

31 Aug 2026, 10:48 UTC≈1,020 views4 reactionsread 2 September 2026
Photo

目前最前沿武器,Inner loop: Multica,Outer loop: Raft。 #Agents

❤4

Signed 志筑仁美

31 Aug 2026, 10:24 UTC996 views3 reactionsread 2 September 2026
Photo

[[Nautilus Log]] Google Calendar 同步功能 https://github.com/404KSG/roam-nautilus-log [[Nautilus Log]] 现在可以设置里一键连接 Google Calendar,直接拉取排期事件和任务。普通点击同步,Roam 中的本地修改和子 Block 会被保留,Option + 点击可强制刷新。全程只读,不会修改 Google Calendar。 目前 Roam Depot 审核中,使用 404KSG+roam-nautilus-log+1441 测试。 相关链接 1 Nautilus Log丨我目前最满意的时间管理工具 2 [[Nautilus Log]] 的魔法 #RoamResearch

❤3

Signed 志筑仁美

30 Aug 2026, 11:12 UTC≈1,100 views7 reactionsread 2 September 2026
Photo

我给 Roam Research 换了套 Linear 皮肤 https://github.com/404KSG/morden-roam-css 这套 Modern Roam Theme 主题,算是我使用 Roam Research 7 年沉淀和优化的结果,超官皮级别的皮肤,如同使用全新的软件。它由 Linear 的视觉逻辑重构整个工作区:左侧栏与主界面背景完全交融,右侧栏以卡片形式嵌进主界面,整体阶梯架构但不失主次感,写作区、左右侧栏组成完全现代化的 Xanadu 工作台。 目前整套主题已经达到 Roam 应有的完整度、一致性和可兼容性。30 多个 CSS 模块和 3 个 JavaScript helpers,除了整体布局,还优化了很多功能细节:左侧栏引用数字、前进/后退按钮、Bullet 呼吸效果、Zettels 标签、引用与大纲 Hover 轨道、引用框圆角细节和各种文本优化。 颜值还是第一生产力,常用常新。 #R…

👍6❤1

Signed 志筑仁美

29 Aug 2026, 13:48 UTC≈1,250 views14 reactionsread 2 September 2026
Photo

日志工作流真是目前最好的 Agents 协同工作方式,尤其借助大纲软件。大纲纵深就是 Subagents 纵深,大纲并列就是多 Agents Runtime 并发,Block 引用日志都可追本溯源、亦可蒸馏回归,无情分发,无情飞轮。真正的建造游戏内核。#mood

👍13❤1

Signed 志筑仁美

29 Aug 2026, 12:56 UTC≈1,220 views3 reactionsread 2 September 2026

Grok Bot Guides https://x.ai/bot/guides SpaceXAI 最近整理了一套 Grok Bot 使用指南,展示如何使用 Grok Bot 高效协同工作。Grok Bot 现在价值也很明显,自带云电脑的 Agent 个人助手,原生浏览器的跨应用接力,拥有记忆和完整 Context 的 Agents 协作能力。Grok Bot 还支持启动 Cursor Cloud Agents,云上加云。需要注意,Grok Bot 云电脑会在空闲时时冻结的,不完全是官方宣传的 24h 在线,可以接 Macmini 常驻。 目前也有 local first 的开源版本: OpenMausBot,X Premium+ 以及 Cursor Pro 也能订阅使用。Grok Bot 作为 X 内容抓取、处理和总结也非常友好。进阶的 Agents 互动范式。 #Agents

❤2❤‍🔥1

Signed 志筑仁美

28 Aug 2026, 07:51 UTC≈1,280 views7 reactionsread 2 September 2026
Photo

把 Matt Pocock Skills 拆成两支 Agent 小队 https://github.com/mattpocock/skills Matt Pocock 的 mattpocock-skills 一直是我 All in 的一套 Agent 工程插件。仓库目前接近 24 万 Stars,也被 Claude Code 官方 Marketplace 收录。现在它已经成了我给各类 Agents 和 Multica 扩展工程能力的主要 skills 来源。 我用 Skillshare 跟踪上游并同步到 Agents,Multica 里,我很早就把它们拆成 Matt Engineering Ops 和 Matt Writing Studio 两支小队。工程线分成 Discovery、Planner、Engineer、Reviewer 这类学习爆破组,比如重点 skills grill-with-docs 和 wayfinde…

❤7

Signed 志筑仁美

27 Aug 2026, 11:22 UTC≈1,260 views4 reactionsread 2 September 2026

设计感受 我很开心 [[Nautilus Log]] 插件获得了一些朋友的私信喜欢/ Star,以及 Obsidan 移植复刻。Nautilus 的概念非常好,我认为应该是目前时间管理实践最强的模型。 我设计插件或者 UI 最常用的提示词是:请你使用 Linear 设计风格...如果 Linear 公司遇到这个 issue,它会怎么优化?如何设计?提示词很有效,基本符合预期。这也是我之前提到关键提示词的作用。比如我在设计 Roam UI 时被提醒:Linear 提出,不要抢夺不该获得的注意力(Don’t compete for attention you haven’t earned),所以有了 Roam 侧边栏卡片聚焦阴影和被主界面包裹而非独立。设计 [[Nautilus Log]] 时,提醒:轻量而非简陋(Building at the early stage),所以各种交互元素虽然挺多,但是可以堆叠淡化。以及 Line…

❤3👍1

Signed 志筑仁美

27 Aug 2026, 10:00 UTC≈1,180 views12 reactionsread 2 September 2026

写作的坏结局 我发现 AI 用于写作生产已经走向了坏结局。AI 写作现在仅作为一次性 Hype 诱饵,用于劣质信息和注意力交换,在废墟上建造废墟,几乎没有复用价值。这和我最初设想的 AI 写作完全相悖。 我认为有效的 AI 写作或者知识生成应该重新审视 Zettelkasten/ Discourse Graph, Roam Ontology 这类知识组织和交互概念,这是现在真正需要重视的建造哲学。AI 可以广泛参与到写作中,前提是 AI 的写作 Vibe 和人的思考氛围必须契合,共同参与生产过程,而不是 AI 在写作过程提前作品化、独立化,这让知识生产变得黑箱、低效率,无迹可循。可悲的写作。 相关链接 1. Zettelkasten: https://zettelkasten.de/ 2. Discourse Graph: https://discoursegraphs.com/ 3. Roam Ontology: htt…

❤7🗿2🆒2👍1

Signed 志筑仁美

26 Aug 2026, 12:51 UTC≈1,260 views7 reactionsread 2 September 2026
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#memories

🆒6❤1

Signed 志筑仁美

26 Aug 2026, 12:30 UTC≈1,270 views4 reactionsread 2 September 2026
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预设提示词面板 最近越来越发现有些提示词口述重复率越来越高,很多关键句子会让 AI 的输出带来质的变化,这也是为啥很多优秀 Skills 有效或者质变部分就是那 1-2 句提示词。 比如我经常复用的口述约束词,使用 Luna Max 模型子代理来并行处理;将可复用的知识和案例写入 Wiki 这些。前者可以内置为系统提示词,但是会显得不够灵活,后者我也尝试过做成 MCP 让它自主调用,但是会让输出过于笨重和缓慢。这些都是一句话的事情,作为可以随时粘贴的 Snippet 刚好合适。 我主要对比了 Keyborard Maestro 和 Raycast,最后用 Raycast 做的本地 Prompt Launcher:快捷键直接打开面板,可以随时直接粘贴、也可以叠加 Modifier 填充文本,挺方便。(也比较推荐输入法预设模板) #Tools #Prompt

🎉4

Signed 志筑仁美

Showing the 12 most recent of 39 posts we hold for @isaiahsystem. 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.

Posts edited after publishing

@isaiahsystem edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
26 August 2026
Most recent edit
28 August 2026

Forward network

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.

Mentions

Named by 9 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.

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 26 September 2026 — this entry's latest reading, not the date you are reading this.

“404 KIDS SEE GHOSTS (生产力之王版” (@isaiahsystem), 13,563 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/isaiahsystem.

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.