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👀 It’s funny how this same old circus keeps rolling around again and again: during shakeouts, fools panic-sell everything in hopes of striking gold with scam tokens, while smart investors seize the opportunity to buy undervalued and top-tier projects at a discount. In the end, the fools are left empty-handed 🤦‍♂️, while the smart investors grow their 💎 wealth. It’s a pattern as predictable as the sunrise.

Si tuviera que convertirme en ingeniero IA en 90 días, no empezaría con cursos. Construiría proyectos a partir de estos 10 repos de GitHub :

AI 虚拟女友一个月赚4.3万美金！ 我今天看到这个帖子，直接看呆了。 一个21岁的 Austin 大学生，用 AI 造了一个叫 Maya 的 OnlyFans 账号，第一个月就赚了4.3万美元。 问题是——照片里那个女孩，根本不存在。 Maya 22岁，UCF 心理学辍学生，1247个付费订阅者，单月最高一个粉丝就刷了1847美元。 她没有拍视频，没有真人打字，所有消息都是 Claude Code 写的，所有照片是 Flux 生成的，声音是 ElevenLabs 合成的。整个 Maya 只是他 MacBook 里四个 .md 文件。 以前造一个 AI 虚拟网红要花半年甚至一年半，现在只需要4个星期，下一个可能就是一个周末。 作者详细写了 Maya 的四个文件： persona.md 写她完整的人设、背景、喜好； voice.md 锁声音风格； flux.md 固定长相和拍摄风格； brain.md 记录每个订阅者的记忆和互动历史。 Claude Code 每次回复前都会读这四个文件，从不崩人设，也从不忘记粉丝说过什么。 真的很感慨，技术栈已经简单到可怕的地步。 以前的 Aitana López 花了18个月，现在 Maya 4周就跑通了。 这已经不是科幻，而是任何一个有 laptop 的人都能复制的路径——从 OnlyFans 到 Instagram、TikTok、Twitch，随便哪个平台都能套。 AI 让“虚拟人”成本降到了几乎为零，剩下的唯一瓶颈，是你有没有那个 taste 去决定这个虚拟人要成为什么样子。

En 2014, Peter Thiel impartió una clase de 1h sobre cómo crear un monopolio partiendo de 0. Explicó cómo: · Google se convirtió en intocable · PayPal superó a todos · Facebook arraso a la competencia Estas son las 11 lecciones de su clase: 1. Crea valor y, después, captúralo

设计师 @Tanjim38 设计的这些 dashboard 真是太赏心悦目了，简洁清爽，干净利落。 哪怕把原稿直接甩给 AI，都做不出这么极致整洁的页面……

UI/UX Designers, this might be one of the cleanest color palette generators I’ve seen lately. Kigen is a color generator that helps you quickly create beautiful palettes for your UI projects, making it easier to pick colors that actually work well together instead of guessing. Bookmark it for later 💜

Boris Cherny, the creator of Claude Code at Anthropic, just listed 9 patterns that waste 73% of your tokens. in this podcast he breaks down exactly how the model burns tokens before it even reads your prompt: - the 14% you lose to CLAUDE.md before typing a word - the 13% you pay re-reading old chat history - the 11% from hooks you forgot you installed - why most "Claude got dumber" complaints are wrong if you're hitting Max limits more than once a week, you have at least 4 of these. Probably 7. instead of another show tonight, watch this. my own breakdown based on 400+ hours of usage is below, read it after the podcast

现在大家都在做 Agent，但一上复杂业务：架构怎么搭、记忆怎么管、多智能体怎么配合，往往越做越迷糊。 我最近看到一本开源书 Agentic Design Patterns，把智能体设计模式从入门讲到企业级，脉络清晰、拆解到位。 全书 21 章 + 7 个附录，按难度分四大部分；每章配套 Jupyter Notebook，边读边跑，理论和代码紧贴在一起。 GitHub：github.com/evoiz/Agentic-… 前半段打底：提示链、路由、并行、反思、工具调用、多智能体协作等核心模式，一次讲透“怎么设计”。 后半段落地：记忆管理、异常恢复、人机协作、安全护栏、性能评估等生产必修课，直接对准“怎么上线”。 附录还补齐框架对比和高级提示技巧，适合查漏补缺、随用随翻。 想把 Agent 从概念学到可落地的系统方法，这本开源书值得收藏，慢慢啃。

Introducing Mesa: the most powerful filesystem ever built, designed specifically for enterprise AI agents. Every team building agents eventually hits the same wall: where do the files live? Not the chat history, the actual artifacts the agent works on. > The contracts your agent redlined > The claim files it updated > The 200-page audit report it edited overnight while you were asleep Today those documents live in a sandbox that dies in 30 minutes, an S3 bucket where concurrent writes clobber each other, or a GitHub repo that was never built to absorb agent-scale traffic. So we built Mesa. The world's first POSIX-compatible filesystem with built-in version control, designed from the ground up for agents. You mount it into your sandbox like any other filesystem. Your agent reads and writes files normally. Behind the scenes every change is versioned, branchable, reviewable, and rollback-able — like a codebase, for any file type. Mesa provides – Branches so agents work in parallel without locking – Durable storage that survives sandbox death – Sparse materialization so massive document sets load instantly – Fine-grained access control per agent – Full history for human review and audit Design partners are running Mesa in production across legal, healthcare, GTM, business ops, and coding agents. Private beta is open: link in the comments

Robert Sapolsky es un neurocientífico de Stanford que demostró que el estrés crónico es el asesino silencioso que los médicos ignoran. Reveló 10 hábitos que haces todos los días y que te quitan años de vida. 1) Repasar conversaciones en tu cabeza

Delete 99.87% of your digital footprint from the internet. Here is a step -by -step guide:

在 GitHub 上挖到一门很实用的开源课：Learn Harness Engineering，专门教你给 AI 编程助手搭一套更可靠的“工作台”。 它把 AI 协作拆成五个关键机制：指令、状态、验证、范围、会话，让每次任务都可追踪、可续接、可验证，不再靠运气出结果。 GitHub：github.com/walkinglabs/le… 官网：walkinglabs.github.io/learn-harness-… 课程结构很清晰：12 节理论 + 6 个实战项目，用同一个桌面应用贯穿推进，边做边演进。 从最基础的对比实验起步，逐步把整套工作环境搭起来；每个项目的产出，直接接到下一个项目继续用，越做越稳。 更贴心的是，它还提供可直接复用的模板文件：拷进自己的项目就能上手，不用完整学完，也能立刻提升 AI 的稳定性和可控性。 如果你已经在用 Claude Code 或 Codex 做真实开发，却总觉得 AI 时好时坏、难以复现，这门课很值得花时间看看。

可以提高审美的网站 dark.design footer.design landingly.co godly.website awwwards.com 提高你的审美，在 AI 时代显得尤为重要 dqxf1izhlm.feishu.cn/wiki/Q851wiIjH…

Goodbye Claude Code subscription fees. Someone just built a proxy that runs Claude Code completely free... and it's wild. You literally plug in a free NVIDIA API key and point Claude Code at localhost. That's it. It handles everything: - Converts Anthropic API calls to NVIDIA NIM format - Unlocks 40 requests/min for free - Supports Kimi K2, GLM 4.7, MiniMax M2, Devstral and more - Streams thinking tokens and tool calls live - Even includes a Telegram bot so you can run Claude Code from your phone No API bill. No rate limit panic. No vendor lock-in. Honestly, this goes beyond router tools like OpenRouter. It doesn't just swap the model... it turns Claude Code into a free agent you can control remotely. The project is open-source on GitHub. It's called free-claude-code.

Вчера Антрпики провели бестплатный воркшоп на FrontendMasters - это взрыв мозга абсолютно свежая инфа по технологи ClaudeCode. Я занимаюсь транскрипцией этого семинара для себя новозможно буду делиться тут новой информацией Для понту и хайпу канеш. Если интересно ставьте лайк

마이크 타이슨이 전성기 시절 최대 500개 수행했다던, ‘타이슨 푸시업’ 이거 진짜 전신 운동입니다. 한번에 하체랑 상체 동시에 조질 수 있습니다.

任何人都应该知道并且收藏的前端设计库大全整理： 设计库 → curations.supply 着陆页 → landing.love SaaS 网站 → saaspo.com AI 移动应用构建器 → sleek.design/?ref=abrahambw 字体 → uncut.wtf 动画 → 60fps.design 移动应用 → mobbin.com/?via=abraham 品牌 → rebrand.gallery 图标 → hugeicons.com/?via=Abraham 设计系统 → component.gallery 网页设计 → curated.design 导航栏 → navbar.gallery CTA 部分 → cta.gallery 用户流程 → pageflows.com SaaS 组件 → saasframe.io 动画（替代） → appmotion.design 着陆页（进阶） → lapa.ninja 极简网页 → minimal.gallery 通用灵感 → godly.website 着陆页组件 → landingfolio.com

If I had to become an AI engineer in 90 days, I would not start with courses. I would build projects from these 10 GitHub repos. 1. LangChain The LLM application framework on almost every AI engineer JD. If you want to build production LLM apps, start here. repo → github.com/langchain-ai/l… 2. LangGraph Stateful agents as graphs. The repo JDs mean when they say "agentic workflows." repo → github.com/langchain-ai/l… 3. LlamaIndex The go-to framework for RAG and document agents. Every "retrieval pipeline" JD points here. repo → github.com/run-llama/llam… 4. CrewAI Multi-agent teams with roles and tasks. Used in production by enterprises across the Fortune 500. repo → github.com/crewAIInc/crew… 5. Qdrant A production vector database written in Rust. JDs name it alongside Pinecone, Chroma, and FAISS. repo → github.com/qdrant/qdrant 6. Ragas The standard framework for evaluating RAG pipelines. Hallucination, faithfulness, relevancy, all measurable. repo → github.com/explodinggradi… 7. Ollama Run open-source LLMs locally in one command. JDs ask for local inference for cost and privacy reasons. repo → github.com/ollama/ollama 8. Awesome MCP Servers Model Context Protocol is the newest skill on JDs. This repo indexes every production MCP server out there. repo → github.com/punkpeye/aweso… 9. Awesome LLM Apps 100+ end-to-end templates for RAG, agents, multi-agent teams, voice agents, and MCP. Real working code. repo → github.com/Shubhamsaboo/a… 10. AI Agents for Beginners Microsoft's free 12-lesson curriculum covering the full AI agent stack. No paywall, no signup. repo → github.com/microsoft/ai-a… AI engineer job descriptions in 2026 keep asking for the same things: RAG, agents, vector databases, evals, MCP. These 10 repos teach all of it. Pick one. Build one project. Push it to GitHub. That's how you start. 100% free. 100% open source.

This 30-min workshop by the creator of Claude Code will teach you more about vibe-coding than 100 YouTube video guides. Bookmark it & give it 30 minutes today. This video will change the way you use Claude forever.