Liiiiam

水过CV论文，目前从事后端开发，对Agent很感兴趣。
摸鱼时喜欢看理财内容🤔
- Agent first

[一起发财 @yiqifacai]

如果你有一笔2年不太用的钱，我会建议你买入内存股，如果你有一笔5年不太用的钱，会建议你买入CPO股，如果有一笔10年不太用的钱，我会建议你买入特斯拉，如果是一笔20年不太用的钱，留给下一代，建议你买点spaceX。
读 《大胆前行：太空数据中心的构想》有感。
emm... 二十年后再发财，终不似少年游。

[Liiiiam @zlin9i]

@kenw_2 嗐，看完只觉得生理不适

[Liiiiam @zlin9i]

先转后看

[Xudong Han @Xudong07452910]

这篇论文让我感觉，我们对「AI 会取代程序员」这件事的讨论方向可能全错了。

核心观点：AI Agent 的出现不是让软件工程师工作效率更高，而是让「把决策逻辑永久编码进软件」这件事本身变得越来越不必要。

作者说的是一个更根本的范式变化：传统软件工程的本质是，人类把判断逻辑「固化」成代码——if-else、状态机、算法，这些都是把人类决策「提前写死」的方式。但在以 LLM 为核心推理引擎的 Agent 系统里，代码变成了「临时生成、用完即扔的工具」，每次任务，Agent 动态生成需要的代码，执行完就不需要了。决策不再被预先编码，而是在运行时由 LLM 推理循环动态产生。这不是增量改进，而是软件生产范式的结构性替换。

我觉得这个观点里最值得注意的细节是：这不只是生产力工具的升级，而是「软件」这个概念本身的角色在变。以前代码是「系统的中心」，Agent 框架是外壳。现在 LLM 推理循环是中心，代码变成了外壳里的临时辅助。如果这个趋势持续，软件工程的核心能力可能不再是「写出好代码」，而是「设计出可靠的推理约束边界」。

以前我们关注写出可维护的代码，以后可能更要关注设计出可靠的推理边界。

https://t.co/28rZe5qvBP

[Liiiiam @zlin9i]

@Jesii_ca_M 🇩🇪

[Liiiiam @zlin9i]

@beardomination 🦜一直这样癫癫的

[Liiiiam @zlin9i]

@0427SMtieshou 我第一次看到这个段子时，还是一个法国人发的

[Liiiiam @zlin9i]

@liujiayi1111 好乖

[Liiiiam @zlin9i]

@ooeli_eth 还是好看的

[Liiiiam @zlin9i]

我至今都不知道为啥🤦🏻‍♂️

[Liiiiam @zlin9i]

@aleabitoreddit 女股神！

[Liiiiam @zlin9i]

@ritu_twts pycharm

[Liiiiam @zlin9i]

@lxfater 额贼，好吓人

[ثامر الغالي @alghali]

يوتيوب تعلن عن اتاحة نقل جميع مباريات كأس العالم 2026 على قناة FOXOne في اليوتيوب

التعليق سيكون باللغة الانجليزية .. احفظ الرابط عندك قد تحتاجه اذا هنق اشتراكك 😅

[Matt Van Horn @mvanhorn]

https://t.co/95lFnAyw0e

[Andrew Ng @AndrewYNg]

One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations.

The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below.

The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs.

However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality.

Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on.

What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities.

[Original text: The Batch newsletter]

[Liiiiam @zlin9i]

嗯🤔

[xIA @xiathis]

En vez de 2 horas de Netflix esta noche, mira esta clase magistral de 40 min del fundador de una empresa china de IA valorada en más de $20B

La explicación más clara que he visto sobre enjambres de agentes y sistemas de IA a gran escala.

[Liiiiam @zlin9i]

@imvihv 公司挺有用的

[Liiiiam @zlin9i]

@siantgirl 那你适合去潮汕找👀

[Liiiiam @zlin9i]

@wangray 广东的眉眼真好看啊