How I combined the best of @poteto's pstack and @kunchenguid's Firstmate into a single runtime. Instead of letting their routers fight as separate authorities, I kept Firstmate as the outer loop for fleet orchestration and injected pstack's engineering discipline directly into the workers runtime. >Firstmate is a fleet commander (horizontal scale across Git worktrees). >pstack is an elite micro-manager (strict engineering habits and verification). Here is how I merged them into an optimized hybrid runtime: * Conditional Briefs: Worker prompts load plays just-in-time. Zero bloated prompt dumps. * Required-Read Habits: Smallest logical change, subtract code before adding, and analyze blast radius. * Context Discipline: Only map how the system is built when the change crosses into another part of it. If you skip that, write one line saying why. * Verification: "Done" requires real artifact proof (running live shell commands or generating local app verifiers). * Scaffold Isolation: Worktree checks prevent role hijack across ship, scout, and supervisor agents. I stripped out the Cursor UI dependencies for my local machine's CLI stack and skipped the expensive multi-frontier review loops. Firstmate handles the fleet isolation. The injected runtime handles the code discipline. The goal is lean, fast and deterministic. Just wired this up today, so I will be seeing how this works on my projects. html artifact- Repo links: pstack: Firstmate:

Today is a very historical moment for AI video generation You can now generate AI video faster than you can watch it Before it'd take let's say 2-5 minutes to generate 15 seconds of video @fal made a post-trained Minimax H3 variant called Max which is 50x faster than the

Okay I built it! 🍰 Infinite Slop An infinite and interactive AI generated live stream of slop that goes on forever and ever Anything that you write in the chat is generated next and AI will try to connect it to the previous video so there's an actual sequence and story line Idea by @marcantoinefon and @rehan_shei's original stream so I made it It'd be very expensive to run this so @fal very generously sponsors this They also fine-tuned the model that makes this possible for the first time, making Minimax H3 50x faster and as "Max" and it can now generate videos faster than you can watch them, very cool! Let me know what you think!!!! 😊

Introducing /skill-doctor v1 Skill doctor is a skill that improves your skills: - Crawls your past CC, Codex, or Warp convos - Scores them for efficiency and code quality - Proposes diffs to your skills that you'd actually merge (STE-100 approved) 🔖

make money with grok bot in 6 weeks (FULL GUIDE)

Can try it here for free

long live the kino-fork

More important than ever

poteto poteto poteto how do you use pstack with strict corporate guardrails like not being able to do privileged commands with sudo or reading from the macOS keychain?

在代码里发 HTML 邮件是个老大难，网页上调得好好的样式，到 Outlook 里表格散架、按钮错位，各家邮箱兼容性还不一样。 emailmd 把这活简化成写 Markdown，渲染出各家邮箱都认的 HTML，Gmail、Outlook、苹果邮件这些客户端都能正常显示。 图表是亮点，柱状图、进度条、KPI 卡片、评分星星，6 种数据元素各写一个列表就能生成。 底层是拿表格和文字符号画的，邮箱屏蔽远程图片时照样显示，纯文本版里还会自动重排，不会塌成一串数字。 GitHub： 命令行、React 组件、MCP 服务三种用法都有，接上 MCP 还能让 AI 帮着渲染邮件、检查影响送达的问题。 做产品要发注册确认、订阅通知这类邮件的，省得再跟几百行 table 布局较劲。

I got early access to this @bot feature and it was fun to play with! Here are some fun bots of mine to get you started: @illo_skill bot to easily help you get fun illustrations with basically zero setup: Spotify DJ bot: Credit Card Max bot -- help you figure out credit card benefits and perks maximization strategies. This will get much better if they eventually get @Plaid integration like ChatGPT finances:

How to Build a One-Person Media Company With Hermes Bots

You are right to push back

独立开发者做完产品上线，SEO 从哪下手不知道，商业审计工具的订阅费又不便宜。 claude-seo 把整套 SEO 审计做成了 Claude Code 插件，已斩获 15000+ Star！ 25 个子 Skill 加 18 个专家 Agent，技术 SEO、内容质量、结构化标记、AI 搜索优化全覆盖。 全站审计会同时放出最多 15 个 Agent 并行跑，几分钟出一份带优先级的行动清单，附 0 到 100 的打分。 GitHub： 有意思的是每条建议都带一句「怎么验证它没起作用」，不灵能查出来，不是拍脑袋的清单。 现在搜索流量越来越多来自 AI，它专门按 Google 的 AI 优化指南查站点在 AI 搜索里的可引用性。 自己有网站、又不想为 SEO 单独买工具的，装上跑一遍审计就知道差距在哪。

Introducing Opengrok Use any model from any sub ✅ Use local models ✅ Custom controls & flexibility ✅ Model picker ui for convenient swapping ✅ Every model gets its own persistent cloud pc? ✅ (grok/cursor sub required)

its time to improve my skills 👀

@EffectTS_ deserves to have up to date awesome list. The amount of libraries I have discovered while working with Effect is enormous so here is the list you can check and use for your Effect-ts projects:

We built to ship shaders on. Now it's open source. ▪︎ Minimal agent-first WebGPU library ▪︎ Run in the browser or headless Node.js ▪︎ Render in CPU sandboxes and CI tests ▪︎ Create reusable.wgsl modules

My screen recording app is here, it replaced CleanShot X and Screen Studio for me, all in one tiny native app Free to use, get the pro version with 50% off in limited time, no subscription 👉

Y'all should look at @CloudflareDev Computer. Your agent's don't need a container all the time!

有老项目可以想 redesign 的可以试试这个 skills：redesign-existing-projects 大名鼎鼎的 taste skill 的一部分，专门为 redesign 设计，分为三步：Scan - Diagnose - Fix 我在一个项目上简单用了一下，还是不错的，这几天深入用一下看看效果怎么样。

Pi 现在也能直接用 Claude Pro/Max 订阅了。 pi-anthropic-auth 专门补上 Pi 对 Anthropic OAuth 的兼容缺口。它不是重写 provider，而是在 Pi 原生 Anthropic transport 外加一层薄封装： • 保留原生 /login anthropic • 保留完整模型列表 • API Key 请求和其他 provider 完全不受影响 • 只在检测到 sk-ant-oat OAuth token 时启用 • 交互轮次与 compaction 都能覆盖 安装一行： pi install npm:@gotgenes/pi-anthropic-auth 然后照常执行 /login anthropic 即可。目前项目 181 Stars，最新 release 为 v2.0.6。 注意：Pi 0.80.8 及之后版本中，自己运行独立 agent loop 的后台 Agent 是已知例外，需要按项目文档使用 workaround。 如果你想在 Pi 里复用已有 Claude Pro/Max 订阅，这个扩展值得收藏。

oh my pi, meet oh my fleet. OMP is now supported inside Agent Orchestrator. Give every task its own isolated worktree, run multiple OMP sessions in parallel, and track the code, PRs, CI, and reviews from one live board. your favorite harness just got a control plane. @_can1357 x @aoagents

here are some more resources you can send to your agent to improve your UI... - - - - -

Or rewrite history Duck tales ahhh whoo ooohh

currently selling one Microduck every 5 seconds

天崩地裂一般，跑根本来不及，伤亡估计很大啊

Rainmaker just produced ~19M gallons of water in Alaska via next-gen cloud seeding over 3 hours of operations. We are the first company to provably produce precipitation in Alaska. As promised, we’ve linked our white paper and relevant data. In the future, Rainmaker will protect and restore glaciers with man-made snowfall. Immediately, this demonstration shows how Rainmaker will add new water to the Colorado River and Great Salt Lake in the coming months. We turned around this analysis and white paper just a couple days after operating. There are many data sources I want to deepen our understanding of the atmosphere and increase our provable production; we’re building the instruments to collect that data in subsequent operations. But at Rainmaker, we won’t tout LOIs, simulations, or lab tests. What matters is physically measuring that you’ve affected the atmosphere; proving that we’ve produced water. We prefer sharing only the tech that has proven to make more water for farms, industries, and ecosystems in need. Expect a regular cadence of these from us as we build the best atmospheric science lab in the world. Feedback is welcome in the interim. Rainmaker Century. https://www.rainmaker.com/blog/alaska-validation-report

How Quants Use AI to Build Regime-Adaptive Trading Strategies (Complete Guide)