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Anthropic just published an engineering guide on how to build always-on agents. The biggest misconception: an always-on agent does NOT run 24/7. It sleeps almost all day, wakes up for short runs, saves state, and goes back to sleep. The 5 core pieces I distilled: 1. Event Inbox Put a database table between webhooks and your agent. Acknowledge webhooks fast, run only one active worker per user so runs never collide, and batch rapid messages together. 2. Timers Keep timers in a separate table from the inbox. Split them into one-off follow-ups and recurring schedules. A background poller drops due timers into the inbox. 3. Lean Memory + Dreaming Only store what cannot be looked up again: user instructions, user notes, past messages, and task progress. Load a small index at wakeup, not every file. Run periodic dreaming passes to clean out stale facts. 4. Unattended Permissions Never put raw API keys inside the agent sandbox — inject them through an outside proxy. Use Deferred Tool Calls to pause risky actions for approval without blocking the worker. 5. Outbox Queue outgoing replies so your agent paces notifications instead of spamming users at 3 AM.

Safety evaluations are critical for understanding whether a model is ready to deploy, which safeguards to build for it, and where to focus training and research. On our Engineering Blog, we offer 10 recommendations for how to design, run and report them.

My first merge ever 👉🏼👈🏼 A year ago I didn’t even know what "PR" meant. Today something I built is part of the Hermes ecosystem, and it’s the first code I’ve ever submitted anywhere. As an engineering dropout, it blows my mind. It might not mean much to the average dev, but for a meat proxy like me, it’s a huge deal. Thank you @Teknium, @witcheer and the @NousResearch team for the Hackathon and for the incredible community you’ve built around your mission. Fuck tyrants. Open source will win 🪽

این مقاله واقعاً دیوانه‌کننده‌ست! پژوهشگرهای چینی مقاله‌ای منتشر کردن با عنوانی که باید تمام سازندگان ایجنت‌های هوش مصنوعی رو به فکر فرو ببره: «پایان Harness Engineering» حرف اصلی مقاله در یک جمله‌ست: شاید دوران طراحی و کدنویسی دستی تمام اجزای اطراف مدل‌های هوش مصنوعی داره به پایان می‌رسه. بذار ساده‌تر بگم: تا امروز ما برای ساخت هر ایجنت، ابزارها، دستورالعمل‌ها، گردش کار و منطق اجرایی رو طراحی می‌کردیم؛ بعد هم همون ساختار رو ماه‌ها استفاده می‌کردیم. اما این مقاله یه ایده متفاوت داره: چرا اجازه ندیم خود سیستم، زیرساختش رو بهتر کنه؟ روش کارش جالبه: ۱. یک مدل کوچیک ۴ میلیارد پارامتری، شکست‌ها و خطاهای سیستم رو بررسی می‌کنه. ۲. برای بهتر شدن عملکرد، ۸ تغییر مختلف پیشنهاد می‌ده. ۳. هر تغییر با مجموعه‌ای از سؤالات و تست‌ها ارزیابی می‌شه. ۴. فقط تغییری باقی می‌مونه که واقعاً نتیجه بهتری گرفته باشه. نکته مهم اینه که مدل اصلی ثابت می‌مونه؛ چیزی که مدام تغییر می‌کنه، هارنس و ساختار اجرایی ایجنته. این ایده به یک مدل یا فریم‌ورک خاص محدود نیست و می‌تونه نگاه ما به ساخت ایجنت‌ها رو تغییر بده. اما بخش مهم‌تر ماجرا: نقش انسان از کدنویسی و دستکاری مداوم سیستم، به طراحی آزمون‌ها و معیارهای موفقیت منتقل می‌شه. یعنی باید دقیق بدونیم از ایجنت چی می‌خوایم و چطور بفهمیم واقعاً بهتر شده یا نه. شاید در آینده مزیت رقابتی ما این نباشه که چقدر خوب برای ایجنت‌ها کد می‌نویسیم؛ بلکه این باشه که چقدر خوب می‌تونیم عملکردشون رو بسنجیم و بهبود بدیم. خلاصه ایده مقاله در یک جمله: قبل از اینکه کد رو بنویسی، امتحانش رو طراحی کن!

Over the past few months, we have restructured MEGA to move in a new direction. We’ve brought together new capabilities and reorganized our teams, a process that has resulted in a 20% reduction in our staff. These are people who helped build MEGA from its earliest days ( building out the chain / wallet, supporting our ecosystem, and telling our wild stories). To everyone who is leaving: I appreciate you. Your work is foundational in what we’re doing next. If you are hiring, please reach out. These are some of the best people we have worked with, and we will gladly make introductions. Our founders, early employees and core engineering team remain committed to MEGA and to the work we started three years ago with MegaETH. We believe cryptography and distributed systems will change how the world produces and accesses purified intelligence. We have a lot to prove, and a lot of work ahead.

I talked my friends who are in Seattle, Washington working in Microsoft. They have been in the office for the last 12 hrs and couldn't find the Root cause of the Outlook issue. They are suspecting that some AI scripts went out of scope and did some patching without any logs and traces. The engineer team that actually coded legacy outlook is not in the Organization and got impacted due recent layoff in the Microsoft. With AI managing almost everything in the Microsoft, so higher management thought of reducing the workforce of Core engineering team. The code of Outlook is so vague that only core engineer (no more in the org) knows about it and earlier they fixed these kinds of issues within 30 mins but now it has been more than 12 hrs and the new team is unable to FIX it.

SpaceX has just unveiled a massive new $50 billion Supercomputing Campus that they want to build in Cochise County, Arizona. All info: • Up to 6 GW across the 9 supercomputing buildings • Construction starts 2027 • Size of each supercomputing building: ~493,000 square feet. • Total supercomputing building space: 4.44 million square feet, excluding support facilities. • SSVEC residential customers are projected to see electricity bill reductions of 10–40%. • Up to 24 GWh of grid-connected battery storage to provide backup power, stabilize the regional electric grid, support local voltage, and absorb fluctuations in electricity demand. Among the largest planned battery installations in the United States. • Additional solar generation in the region is planned to supply renewable electricity during the day and reduce demand on the local grid. • No dedicated on-site power plant or fuel storage yard is planned. • Each supercomputing building will have 10 MW of natural-gas-powered standby generation for critical equipment, operating only during utility outages and periodic testing. • No gas turbines will be installed at the site. • SpaceX plans to fund $3.6 billion in grid infrastructure upgrades, transferred to AEPCO at no cost to its members. • Up to $260 million annually in additional benefits for cooperative members at full buildout, on top of residential bill reductions. • Up to $200 million annually for cooperative members statewide, in addition to SSVEC benefits. • The supercomputers will use dry cooling with a closed-loop water circulation system rather than evaporative cooling. • SpaceX projects zero ongoing industrial water consumption. • The cooling system will be filled initially, with water reused for up to 10 years. • SpaceX estimates annual water usage equivalent to approximately 20–30 Arizona residential homes. • Projected annual water use would be less than 2.5% of a single center-pivot irrigation system's annual consumption. • Permanent jobs: Approximately 1,000. • Construction jobs: Approximately 5,500. • Annual property tax revenue: Up to $103 million in estimated new annual revenue. • Regional economic benefits: SpaceX says its investment will support public education, infrastructure, essential local services, and economic development. • Local suppliers: SpaceX is encouraging suppliers to participate in construction and development of the campus. • Noise mitigation: Equipment will be positioned away from neighboring properties where possible, with setbacks and additional screening to reduce noise. • Nighttime lighting: Outdoor lighting will remain off unless work is underway, with active lights shielded and directed downward. • Dark-sky protection: The campus will comply with Cochise County's dark-sky requirements to limit light pollution. • Nighttime construction: SpaceX says it will seek waivers when nighttime construction lighting is necessary. • Wildlife protection: The campus is being designed with consideration for the region's sandhill crane wintering habitat. This campus's purpose is to build one of the world's most advanced AI supercomputing campuses to train SpaceX's superintelligence models and support scientific and engineering breakthroughs. Learn more:

Jensen Huang is effectively OUT of NVIDIA🚨 Man His wife is 65 years 🇺🇸 They have been married for 41 years. As early microchip designers, she reportedly earned more money She totally left engineering work to raise their two children while Jensen Huang built Nvidia She was one of only three women in a class of 250 electrical-engineering students at Oregon State University when she and Jensen met. Jensen was 17 years when he walked up to the 19 year old Lori (his wife) and asked "Do you want to see my homework?" He promised that if they studied together every Sunday she would get straight A's, turning homework sessions into weekly dates. He also told her he would be a CEO by age 30. A promise he kept when he co-founded Nvidia in 1993. Jensen has repeatedly called meeting her "the most important, single event of Oregon university, and of my life" They married in 1985, the same year she graduated with her electrical-engineering degree. In 2022 the couple gave $50 million to Oregon State University (the campus where they met) to create a major innovation complex named after both of them. Jensen has said he does "zero percent" of his own shopping and that Lori (with their daughter) chooses his clothes, including the signature black leather jacket. He has publicly credited her with being "part of Nvidia every step of the way" and with handling the personal and financial details of their life. It's quite sad what is happening currently and how shattered Lori Huang must be.