Randalloop

All about Sneakers, I sell and buy shoes, sz9.5. Also a big fan of Supreme

[Randalloop @them1stwalker]

legit check 🤔

[nash_su - e/acc @nash_su]

llm_wiki 竟然被 Google 制定为知识标准：OKF v0.1

当然我说的是 karpathy 的那个 llm_wiki 方法论，现在被 Google 起草了一个 0.1 版本的 OKF 开放知识格式标准。

我的那个 llm_wiki 项目看来要跟这个赶紧做个兼容，现在 11k star 了，得加紧更新

项目地址：https://t.co/Xkd9oTNcIj

Google OKF 标准相关文档：
https://t.co/Sd6yvl61wT

[Shann³ @shannholmberg]

what is agent looping

for the last two years we prompted agents one task at a time. that is starting to change

instead of asking an agent to build the landing page and then driving every step yourself, you set up a loop that handles discovery, planning, the work, checking, and iterating until the goal is met

looping is a setup you build. almost any agent harness can run it, it just depends on how you wire it up

at its simplest, looping is one agent working on itself:

> researches
> drafts
> checks the draft against a goal
> fixes what is weak
> runs that cycle again until the work clears the requirements

you are not prompting each step anymore. the agent repeats the cycle for you

the bigger version is a fleet looping. you give an orchestrator agent a goal, it breaks the goal into pieces, hands each piece to a specialist agent, and those specialists hand smaller jobs to their own subagents

the whole tree keeps looping through discovery, planning, execution, and verification until the goal is met

one agent looping is like a person redoing their own draft. a fleet looping is a whole team running a project end-to-end

you create a goal, and the system runs the loop until it finishes within the reqs you set

open and closed looping:

OPEN LOOPING is exploratory. it still has conditions and a goal, but you give the agent or the fleet a wide space to move in. it can try different paths, discover things, build something you did not fully spec out

this is the exciting end, it is what Peter and others are doing, and tbh it is where I want to spend more time

the catch is cost, an open loop with real room to explore burns an insane amount of tokens. for the 90 percent of people without an unlimited budget it is not runnable yet, and pointed at projects with a loose standard it turns into a slop machine

CLOSED LOOPING is bounded. a human designs the end-to-end path first:

> clear goal
> defined steps
> an eval at each step
> a point where it stops or hands back to you (and feeds back performance data)

the agents still loop, but inside framework you built. it gets better every run because each pass feeds the next, and it runs on a normal budget because the path is tight.

for most marketing work, closed is the one that pays off today.

> the orchestrator owns the goal
> the specialists own the steps
> the subagents do the narrow work
> an eval gate make sure its not slop

[小互 @xiaohu]

https://t.co/uYh4KNpDqs

[Smartpig @Smartpigai]

Andrej Karpathy 用 2 小时演示了他日常如何使用 AI

本质就是把 AI 当成能执行任务的同事，用自然语言直接沟通。

流程很简单：一句话说明任务 → AI 执行 → 看结果再用一句话微调。

真正的差别在于，你是否把这种能力升级成一个能在你不在线时也持续运行的系统。

[Leon7ang @Leon7ang]

@zhangxiaojubtc 来了～主包 https://t.co/danmVFdGKB 我用的他的懒人配置

[Gagan Ghotra @gaganghotra_]

🚨 JUST IN - Google published a long piece about "Optimizing your website for generative AI features on Google Search" 👀

A lot in it https://t.co/22t75EtwUH

🧵

[花叔 @AlchainHust]

别吵了！我给你们开源了一个skill，随意转换md和HTML
👇
https://t.co/yYQIcwAF3Z

[阿哲Phil @Formulasearch]

https://t.co/Ou7xl0QJDk

[Sac @Saccc_c]

泡泡玛特可以给我打钱了

用Codex + HyperFrames 为泡泡玛特做了一个宣传片

顶级的IP + 顶级的视觉设计 = 顶级的营销

各位老板请享用

[Sac @Saccc_c]

https://t.co/7bPLnuZH0V

[Kyrie @KyrieCheungYep]

https://t.co/ItwwW5tiAr

[Warp @warpdotdev]

The Warp team uses a lot of Skills to speed up our workflow, so we open-sourced them.

> npx skills add warpdotdev/oz-skills

Includes Skills for SEO and accessibility auditing, documentation writing, DevOps tasks like terraform configuration, and more.

[Vincent Josse @vince_jos]

Today, we’re releasing Claude Code for SEO.

It does an SEO agency's work by finding relevant backlinks for your website, researching keyword opportunities and publishing SEO-friendly articles to your website.

Now live on ProductHunt: https://t.co/TaNxEigqlo

[Mario Tomic @mariotomich]

Just 8 minutes of walking increased creative output by 60%.

Stuck on a problem? Go for a walk.

[看不懂的SOL @DtDt666]

兄弟们！炸场硬核干货来了！

亲手打造特斯拉 Autopilot、OpenAI 联合创始人 Andrej Karpathy，这套大模型实操教程，

里面全是他本人日常工作生活里，用大模型的全套真实玩法：从靠模型做深度思考、搞硬核科研，到文件上传处理、Python 解释器实操、Claude Artifacts 高阶用法，全给你拆得明明白白，半点儿私货都没留。

没有半句空泛的理论，没有半点没用的跑分测评，全是能直接抄作业的落地干货。

整整 2 个小时，大神一步一步带着你，走完他自己日常用 LLM 的完整工作流。

而是这 2 个小时里的东西，会悄无声息地改变你整个职业生涯的工作逻辑和效率上限。

别打开抖音刷剧了，先把这个内容收藏好👇

[姚金刚 @yaojingang]

两周前，开源了第一个系统：GEOFlow
到今天，已经有1k Star了
作为一个非常细分场景里的开源系统，这个反馈其实挺超预期的
这个系统的功能复杂度还挺大的，集成了：CLI、Skill、爬虫、API、GEO工作流、自动化、AI友好度优化，乃至接下来的数据分析与多端发布…

前几天和几位同行专家聚餐交流，一位CEO说，他的小龙虾扫描到了一个叫GEOFlow的项目，还下载下来部署了一遍
我说：这个系统，我写的
那一刻还挺有意思

[Peter Pang @intuitiveml]

https://t.co/oWr2pTk4Hu

[Berryxia.AI @berryxia]

Stanford 这堂 2 小时 AI 系统构建课，直接把 Claude 所有教程和 Prompting Thread 秒了！

强烈推荐：
“比你刷过的所有 Claude 教程都实用 10 倍”

里面讲的不是 prompt 技巧，而是 Stanford 真正教工程师如何从零构建可靠 AI 系统的完整方法论。

周末就刷这一个，绝对是你这周最有生产力的事！

我已经将其翻译为中英 文双语视频直接戳这里👇

[ShingLok @xShingLok]

@steipete I built this to fix it: https://t.co/K9K5DX8Dr3 🦞