Forward Deployed Engineer(FDE,前线部署工程师) 是深入客户业务现场、系统诊断复杂问题,并基于公司核心AI技术平台进行定制开发、系统集成与快速迭代,最终交付可量化业务价值的高阶AI技术专家岗位。
Signed qilai

Channel
@aiziyuanbiji
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
2,442subscribers
+346 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002682021171 |
|---|---|
| Type | Channel |
| Username | @aiziyuanbiji |
| Created | Between 1 March 2025 and 31 July 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 15 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/aiziyuanbiji |
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 15 September 2026 and assigned it the closest of 31 fixed categories, at 98% 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 |
|---|---|---|
| 17 Sept 2026, 00:01 | 2,442 | +35 |
| 13 Sept 2026, 07:59 | 2,407 | -3 |
| 9 Sept 2026, 20:40 | 2,410 | -9 |
| 4 Sept 2026, 15:57 | 2,419 | +30 |
| 1 Sept 2026, 04:28 | 2,389 | +13 |
| 29 Aug 2026, 05:33 | 2,376 | +20 |
| 26 Aug 2026, 08:14 | 2,356 | +29 |
| 23 Aug 2026, 12:45 | 2,327 | +50 |
| 19 Aug 2026, 17:55 | 2,277 | +26 |
| 16 Aug 2026, 19:58 | 2,251 | +55 |
| 13 Aug 2026, 05:14 | 2,196 | +46 |
| 9 Aug 2026, 23:36 | 2,150 | +47 |
| 7 Aug 2026, 08:30 | 2,103 | +7 |
| 6 Aug 2026, 20:01 | 2,096 | no change |
| 6 Aug 2026, 19:51 | 2,096 | first reading |
18 posts held, back to 1 August 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 18 posts for this entry, the most recent from 6 August 2026. An engagement rate over an empty window would be a number about nothing.
3 reactions across 3 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 3 | 100.0% |
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 3 of the 18 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 3 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 1 August 2026 to 6 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.
Forward Deployed Engineer(FDE,前线部署工程师) 是深入客户业务现场、系统诊断复杂问题,并基于公司核心AI技术平台进行定制开发、系统集成与快速迭代,最终交付可量化业务价值的高阶AI技术专家岗位。
Signed qilai
今天一个做投资的朋友跟我说了个事儿,挺触动我的。他说他现在看AI项目,基本上只看一个指标——客户续费率。 技术再牛、团队背景再强、故事讲得再好,续费率低于60%的,一律不投。他说AI项目最大的坑,不是东西做不出来,而是客户用了一次就再也不用了。 他之前就踩过这个坑。投了一个特别炫的AI营销工具,团队是MIT出来的,半年就签了50个客户,看着势头很好。结果三个月续费率一拉出来,只有30%。赶紧去问客户为什么不续,客户说工具确实不错,但是用起来太复杂了,光为了跑这个系统就得专门配三个人。 这事让我琢磨了很久。我们给企业做AI,卖的根本不是功能演示那种一次性的东西,卖的是人家能真正用起来、一直用下去的能力。交付那天不是终点,是续费周期的第一天。
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Channel name was changed to «AI资源笔记»
买东西这事儿,我有个习惯,还挺好用的: 有严格行业标准的东西,尽量找陌生人买。 非标的东西,尽量找熟人,或者之前合作过的人。 拿苹果手机举例吧, 它就是那种高度标准化的产品,每一台出厂都一样,坏了厂家也给保。 所以没必要为了便宜一点就找熟人,只要渠道能保证是正品就行。 但非标的东西就不一样了, 小到理发、私人裁缝,大到软件定制开发, 这种服务因人而异,出来的效果差别很大。 这种我一般都找合作过的熟人,心里更有底。
Signed qilai
很多所谓的产品,骨子里其实就是SEO产品。 举个例子:你的iPhone本地数据从来没备份过,结果一不小心刷机了,想恢复数据——按理说,这根本做不到。但你去淘宝搜“iPhone数据恢复”,会跳出一堆店铺,都说自己能做,收费也不贵,两百块,远程操作。 他们怎么干呢?先让你找台电脑,再给你装个ToDesk之类的远程控制软件,然后装模作样地在电脑上翻一翻,看看你有没有云备份或者本地备份。最后告诉你,恢复不了的话,退一半钱。 说白了,他们真正想赚的就是这一百块。而且万一碰到个小白,其实本地本来就有备份呢?那这一百块就白捡了。 所以你看,这个所谓的“数据恢复”产品,本质上就是个话术产品,唯一的核心竞争力,就是保证你在淘宝搜的时候,它能排在前头。 我讲这个,不是想吐槽这些人的生意有多low。因为说到底,现在流行的Vibe Coding产品,不也是同一个路数吗😂 当“解决问题”的成本高于“假装解决问题”的流量成本时,所有的产品都会进…
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省Token这8条规则,说白了就一句话:别让你的AI编程Agent像个实习生一样什么都自己重写,要像干了十年的老油条那样写代码。 直接上干货: 1. 不保留向后兼容。过时的东西直接删,别加兼容层、别写迁移脚本、别留降级方案。 2. 选当下能满足需求的最简单实现。不要提前做抽象,也别画蛇添足加配置层。 3. 系统要分层搭建,先跑通一个最小的端到端版本,再逐步往上加功能。绝对不要因为未来可能出现的复杂度,就把已经跑起来的东西拆掉。 4. 组件保持模块化,注意关注点分离。 5. 优先用成熟且有人维护的库。没有明确的理由,别自己重新造轮子。 6. 先翻翻项目里已经有的依赖能做什么,再考虑要不要加新包或自己写。别一上来就默认库里没有。 7. 架构决策要往长远了做。不接受“先这样,以后再换”的临时方案。 8. 先看成熟产品是怎么解决同一个问题的,用已经被验证的模式,别从零发明。 就这8条,丢进你项目根目录的AGENTS.md文件里,C…
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昨晚刷到一个挺有意思的网站,想分享给想找副业或创业灵感的朋友。 网址是:http://starterstory.com 它收录了 2962 多个已经真实赚到钱的项目,类型很杂——有 AI 工具、SaaS、插件、电商、内容网站,还有一人公司。相当于把海外已经跑通的小生意,直接拆开给你看。 比如某个项目月入几万美元,它会告诉你: - 怎么开始的 - 启动成本大概多少 - 第一批用户从哪来(靠 SEO 还是社交媒体) - 用了哪些工具把产品做出来 而且你可以按收入、成本、项目类型、团队人数来筛选。比如专门找: - 一个人能做的 AI 项目 - 低成本启动的 SaaS - 或者已经做到月入 1 万美元的小工具 我觉得它最有价值的地方,不是让你照抄别人的产品,而是帮你发现“已经有人愿意付钱”的需求。 看到一个海外项目之后,你可以顺着想: - 这个需求能不能换到别的行业? - 能不能搬到中文市场? - 能不能用 AI 把原本复杂…
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跟你分享一个真实情况:用 Claude 写推文,坚持发一个月,确实有人能做到月入 1-2 万。 但大部分人用 AI 写内容,其实还在“瞎问”的阶段。 最常见的做法就是一上来就甩一句:“帮我写个爆款推文。” 这相当于把方向、用户、痛点、转化,全部扔给 AI 去猜。猜中了算运气,猜不中你就得一遍遍改,越改越没底。 真正有效的做法,是把问题拆开问。每天花 30 分钟就够,流程其实很简单。 第一步,先选定一个领域,持续发。别今天聊 AI 工具,明天讲副业赚钱,后天又谈个人成长,那样 AI 都搞不清你的定位。固定一个方向,比如 AI 副业、职场成长、内容变现、工具推荐或个人效率。在一个领域发久了,AI 才能慢慢帮你积累风格和用户画像。 第二步,每天定一个具体主题。主题越小越好,别写“AI 赚钱”这种空泛的,可以写“普通人怎么用 Claude 找到第一单服务”“不会写文案的人怎么用 AI 发第一条成交帖”,或者“为什么你问 AI…
❤1
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一、先看准了再动 金价涨跌,说白了就是市场情绪的温度计。金价跌,说明大家信心足,可以大胆出手;金价涨,说明都在避险,这时候得捂紧口袋。 做生意一定要顺势而为,别跟大环境对着干。 门槛低的生意,看着好进,其实最难做,因为谁都能来抢一口。 大钱往往集中在那三五年里爆发,有了就有了,没有就是没有,别指望细水长流慢慢熬成富翁。 二、别用忙掩饰懒 卖点越聚焦越好,垂直深耕的人最赚钱,什么都会一点的人,反而哪个都做不深。 每天就干两件事:白天想好怎么打,晚上复盘哪里差。 整天忙得脚不沾地的人,大多发不了财。财富是对认知的补偿,不是对苦劳的奖赏。 真正会赚钱的人,只盯着最重要的事干,剩下的能外包就外包,能砍掉就砍掉。 三、搞定生意,先搞懂人性 卖东西不一定要便宜,但要让人觉得占了便宜,这里头有个度,得拿捏好。 没有白收的礼物,也没有白吃的饭局,人情往来都有它的价码。 想让别人帮你,先让别人从你这儿赚到钱,这是最朴素也最管用的道理。 …
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以前,投资人最爱问创业者:“如果腾讯抄你,你的壁垒是什么?” 这话现在听着挺冒犯的,但当时那意思其实是——你至少还值得腾讯专门拉个项目组来对付你。 到了2026年,问题变成了: “把你产品截图扔给AI,用Vibe Coding复刻一个要多久?你的护城河又是什么?” 现在你的对手可能只需要一个周末,外加几十美元的Token。 过去创业,是想办法让大厂觉得不值得抄。那现在呢? 说白了,不管是腾讯还是AI,本质都是当下效率的判官,在检验你做的事情到底有没有真实的效率价值。 创业归根到底,就是解决社会效率的问题,同时去满足那些还没被满足的需求。 换个角度想:既然成本都这么低了,你干嘛还要融资? 如果连资本都不再是运营的门槛,那这个生意就压根没有门槛。接下来会卷成什么样,想都不敢想。 具体拆开,事情分两种。 一种是搓完用完就丢的东西——出个bug也没啥灾难性后果,软件体量小、代码少,对界面和体验要求也不高。这类确实没什么商业价值了…
Signed qilai
Boris 说,Anthropic 内部平均有 90% 的代码已经是 Claude Code 写的了,而他自己从去年 11 月起就是 100%。 更有意思的是后面那段话。他说,前端、后端、产品设计这种传统的分工方式已经过时了,因为现在人人都能写代码。他们团队实际上分化成了五种新的角色: - 原型师:抓住第一个想法,飞快地试错。 - 构建者:把原型做成能推向市场的产品。 - 维护者:软件跑到一定规模之后,负责守住它。 - 扩展者:把已经跑通的产品放大十倍、一百倍。 - 收尾人:打磨产品和代码,把那些毛刺都处理掉。 他还提到,扩展者这类人现在在 Anthropic 特别抢手。
Signed qilai
现在全世界大部分模型都进入了DeepSeek斩杀区 能力差、价格贵的只能等着被斩杀了🫡
Signed qilai
Showing the 12 most recent of 18 posts we hold for @aiziyuanbiji. 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.
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.
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 September 2026 — this entry's latest reading, not the date you are reading this.
“AI资源笔记” (@aiziyuanbiji), 2,442 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/aiziyuanbiji.
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.