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You want to know what frustrates the hell out of me? Putting your heart, your art, your time, and your own money into building things you believe in… then watching so much of that work disappear into silence. And yeah, some days that shit gets to me. Did I bring books, reading badges, Discord, crypto, and NFTs together into one connected library? 📚 I fucking did. Did it get much attention? Nahh. Did I build an entire browser-based world with its own points economy? A world where you can turn your NFT into a character with a click, rigged, animated, and ready to step into Universe? I did. Much noise about that? Nahh. Am I building RAAP to give NFTs persistent identity, memory, and history? So an asset can carry something meaningful forward when it passes to a buyer or someone in your family? Yes. Because I believe these things can become more than pictures sitting in a wallet. Does that work get the attention I feel it deserves? Nahh. I draw the fucking art. I develop the applications. I write the books. I work through the problems. Six applications that communicate with each other. Two gaming platforms with multiple games. An NFT overlay builder with AI. A stickers and GIFs hub. Do you understand how much work goes into making all of that actually function together? The hours spent fixing something nobody will ever notice, because when it finally works, it’s supposed to feel easy. Then there’s the Discord bot. More than 30 features. A subscription service. An economy tracked on a ledger. Tools to help keep a community engaged when its owner needs to step away and live their damn life. Built it. Still feels like shouting into an empty room sometimes. And Antthony? Our smart ass AI whose dream is to become a stand-up comic? 😂 He lives across our apps. He’ll help you, roast your gameplay, and talk shit when you deserve it. He even has a comedy club inside Universe, where you can sit down with your character and watch his avatar perform. I care enough about this world to give the fucking AI a dream of his own. That’s how deep this goes for me. And I’m still building a marketplace. Still working on an NFT insurance protocol and other projects. Still writing Book 2 for the library. Still preparing two more collections under our umbrella. ☂️ So yeah, I get angry. Because I know what I’m putting into this. I know how much of myself is in every drawing, every feature, every chapter, and every problem I refuse to leave broken. Sometimes I want to scream: what the fuck else do I have to build for people to pay attention? But I also need to correct myself when I say “nobody cares.” Because some of you do. You show up. You read. You play. You test things. You tell me what’s broken and give me a reason to make it better. You matter too damn much for me to erase you just because I’m frustrated with the silence around us. 🖤 I want this to reach more people. Of course I fucking do. I’ve poured too much love into it to pretend otherwise. And I’m going to keep building because I love doing it, and because the people already here deserve to see how far we can take this. More to come in 2027. The plans are in. I’ve got work to do. 🐜

谷歌刚刚放出一门 70 分钟的官方课，手把手教你打造一个7 * 24小时完全自动化的生产级 Agent 。 很多人学 Agent 看了几十个小时零散教程依然搭不出可用的东西，核心是没有搞清玩具 Demo 与工业级架构的边界。 谷歌这门 1 小时课程没有任何水分，只聚焦 5 个真正的工程核心： 1. 从 0 跑通首个 Agent：拆解模型调用、工具绑定与执行环境的基础闭环。 2. 状态持久化（Persistent Memory）：告别单次对话即失忆，构建跨会话的记忆索引与上下文回填。 3. 长时自主循环（Agentic Loops）：摆脱线性问答，让 Agent 具备自我反思、容错重试与多轮状态流转能力。 4. 吃透 MCP 核心架构：彻底理清 Model Context Protocol 与传统 API 的本质区别，学会构建标准化的上下文协议。 5. 多智能体协同系统（Multi-Agent）：把分散的专职 Agent 串联成高协作度的自动化系统。 完全免费。 比市面上价值700刀的课还要干货。 建议收藏，今晚就观看 。🔖

Bring your web game to Snapchat 🎮 Build full-screen, non-camera experiences with familiar web tools. Add Bitmoji, Leaderboards, and Persistent Storage. Publish as a Web Lens and explore Lens+ monetization opportunities. Build now:

AMA @playcambria Pre-TGE + Genesis "We're going for the first nation-scale game economy" @cyberpunk on Cambria Genesis: One persistent MMORPG world with an economy "worth millions of dollars," after ~$1.8M hit last season's prize pool in 10 days @communitybria

Learn Harness Engineering from scratch! This repo is a full learning path around harness engineering, with 14 lectures, 8 projects, reusable templates, and hands-on exercises. The course focuses on the environment around coding agents and how that environment affects whether an agent can reliably work inside a real repository across longer tasks and multiple sessions. It starts with the fundamentals of harness engineering and gradually gets into things like repository structure, persistent state, task boundaries, verification, observability, session handoffs, automated loops, and graph engineering. A harness in this context has five core parts: - Instructions that tell the agent how to work inside the repo - State that persists progress across sessions - Verification through tests, linting, type checks, and full-pipeline runs - Scope controls that keep the agent focused on one task at a time - Session lifecycle so every run starts and ends in a usable state The projects are also connected rather than being isolated examples. You keep working on the same Electron-based knowledge app while gradually improving the harness around it. You start by comparing prompt-only vs. rules-first agents, then build multi-session continuity, runtime feedback, verification, a complete harness, automated maker-checker loops, and eventually represent the workflow as a graph with parallel execution, rollback, and human approval. What I like is that you can actually take parts of the repo and use them directly in your own projects. There are templates for things like "AGENTS. md", "init. sh", feature lists, progress tracking, loop state, maker-checker prompts, and a "harness-creator" skill that can scaffold the basic harness structure for an existing project. The repo also covers the progression from a single agent loop to graph engineering, including when you actually need nodes, shared state, routing, parallelism, and recovery instead of forcing everything into one loop. A solid resource if you're working with coding agents and want to understand the engineering around making them reliable over longer tasks. 100% open source

When Lauren Friedman showed up at Amherst College, she was surprised to discover that almost every single girl in her dorm and on her athletic team was already taking SSRIs. Inside jokes about Zoloft & Lexapro were common on campus, and everyone seemed deeply grateful their persistent anxiety and depression from teenage years was magically disappearing from a pharmaceutical drug. Like her peers, @lololizzle had struggled earlier in life with both anxiety and depression -- so Zoloft seemed like a perfect solution. After all, all of her friends were taking it too, so how bad could it be? Little did she know, SSRIs are causing a silent epidemic among Gen Zers called Post-SSRI Sexual Dysfunction, or PSSD. Like untold tens of thousands of other people just like her, Lauren now has completely lost her libido, sensation in her genitals, and even a sense of emotional connection with the people around her... PERMANENTLY. She says she and others like her were NEVER given informed consent about the risk of developing PSSD, and American doctors will rarely even diagnose the condition at all. Whether it's birth control being thrown in the faces of teenage girls to magically "regulate your hormones" or Zoloft instantly prescribed to "make you happy," one thing is clear--the young women of Generation Z are being poisoned en masse without any understanding of what may happen to them down the line.

OpenAI Dots is insane for building a 24/7 AI company... I mapped the whole OpenAI Dots architecture into one paper: agents, models, tools, memory, delegation, guardrails and the revenue layer. Here are the 10 steps: step 1 → stop treating Dots like a chatbot. each Dot runs in a persistent cloud environment with its own browser, terminal, files, memory and scheduled execution. close the laptop and the workflow keeps moving step 2 → hire by responsibility. give every Dot one clear domain, dedicated sources, a working style, an approval boundary and a trigger. a "general helper" has no role, only undefined context step 3 → make one Dot the orchestrator. you give it the objective, it decomposes the work, delegates to specialized agents, checks their outputs and merges everything into one deliverable step 4 → stop being the courier between agents. with isolated delegation, each worker gets only the context and tools it needs, executes in its own environment, then returns a structured result to the orchestrator step 5 → connect the real business stack: cloud browser sessions, Slack, Microsoft Teams, Google Workspace, internal dashboards and APIs. a Dot without tools is still just a conversational layer step 6 → put the company on a clock. recurring routines and event triggers turn one-off tasks into persistent operations. research, monitoring, reporting and pipeline checks can run while nobody is online step 7 → automate the reversible, gate the irreversible. let agents read, research, analyze and draft autonomously, but require human approval before messages send, money moves, records change or production code ships step 8 → route intelligence by cost. keep the strongest model on orchestration, conflict resolution and final audits, and let cheaper high-context models handle background research, classification and repetitive execution step 9 → give the company shared memory. project specs, approved claims, pricing, decisions and requirements live in one persistent workspace, so every agent works from the same source of truth instead of rebuilding context from old chats step 10 → connect the loop to revenue. research finds the signal, outreach creates the opportunity, execution moves the work forward, analytics measures the result and monitoring discovers the next action AI stops being something you open when you need an answer. It becomes an operating layer that keeps economically useful work moving after you log off. Copy the complete OpenAI Dots architecture blueprint, then read the full roadmap below ↓

Most #cyclist# are squeezing training in around life, not the other way around. It's about stealing snippets when you can. Even just 30mins a day adds up over a few months. #persistent# training pays off 💪

Introducing Projects, a new way of working in Cursor. Rather than creating a chat for every task, you work with a coordinator agent in a single, persistent thread. Like @bot, your agent is always on, proactively manages work with subagents, and improves over time.

LATEST: 🇰🇷 The Bank of Korea raised its benchmark rate by 25 basis points to 3.00% for the second straight meeting, citing inflation above target and persistent financial stability risks.