AI Agent 现在不缺 Demo，缺的是能真正跑出用户、交易和收入的项目。 @MetisL2 推出了 Metis Rise，一个面向 AI Agent Builder 的月度激励计划，重点支持真正跑在链上的 Agent 应用，包括 x402 支付、ERC-8004 身份、Stablecoin Escrow、链上凭证等方向。 这次他们关注的不是“做没做出一个 Agent”，而是更实际的几件事： • 有没有真实用户 • 有没有真实链上交易 • 能不能完成支付与结算 • 有没有可验证的身份、信誉和交付凭证 • Agent 能不能真正参与经济活动 如果你正在做 AI Agent、Agent Commerce、支付、身份或任务市场相关产品，这个计划值得关注。

This is a good way to understand how early we actually are in AI diffusion right now. The vast majority of people are using AI as a chatbot for simple interactions that approximate next-generation search. This is super useful but dramatically underrepresents the full capability of AI. On the complete other end of the spectrum, agent swarms represent possibly the ultimate form factor of what agents will do inside of our workflows. Math, cyber, bio, materials science, software engineering, finance, and any other field that has valuable tasks that can be executed in parallel where compute can be applied to accelerate work all have this characteristic. Less than a fraction of a fraction of the population uses AI in this way right now, due to a mix of the capabilities of models relative to the user's domain, the cost of doing these types of workflows today, the harnesses available to do this style of AI work, and the availability (or lack thereof) of frontier models to the general public. There will also be a huge amount of change management necessary to get most areas of work -beyond software and AI research- to benefit from this style of agents. Companies need to upgrade their workflows, data needs to integrated and migrated into modern platforms, and companies will need to work through compliance, governance, and security frameworks to pull it off. But this all represents opportunity right now. A lot of this is where the applied layer of AI will really shine in the enterprise because of the domain specificity of this type of work. You can get an early sense of where things are going and the opportunity ahead by seeing through the funnel that Andrej lays out.

Metis 宣布推出全新月度开发者激励计划 Metis Rise: Rise to the Top 🚀 专为能够超越 Demo、产生真实链上交互与服务实际用户的 AI Agent 打造。联合生态及媒体伙伴，共同助力 AI Agent 生态落地。 更多细节即将来袭，Builders 准备好了吗？🔥

Personal agents are the ultimate manifestation of “build something that agents want”. The form factor of a product like Muse is you want to be able to hand off a task to the agent and ensure that it is fully completed end to end. To do this, the agent must be able to successfully operate with your tools or use its own to complete the task. Use your MCP or CLI, easily navigate your site, be able to transact, and more. The new attention you need to compete for is not from the user itself but instead for the agent. This means that the tools that allow agents to order food, handle ecommerce transactions, book flights, work with the local economy, and interact with our data and information best, are the ones that will get used the most. This will ultimately be the biggest opportunity and shakeup in consumer tech since the App Store itself.

Claude Code showed that AI could do real work, not just answer questions. Developers hand Claude a feature, come back to shipped code. That's where much of the industry's serious engineering runs now. Cowork proved knowledge workers could do the same: hand Claude the brief, come back to finished files. Today, chat and Cowork start merging into one Claude. The direction: one Claude that carries context across everything you're working on, wherever you are. Simple enough for everyone to access Claude's full capabilities. I've been using this experience every day for the last few weeks, and it feels awesome. Simpler, faster, and more powerful. We're rolling this out slowly. We'll be fine-tuning the experience as we go to ensure it is fast and reliable. Can't wait to hear what you think.

There’s a massive chasm between the power of AI models and the ultimate workflows that enterprises are trying to automate. This gap is the opportunity for the applied AI layer to fill. You need to connect the intelligence to workflows, often reengineer processes, aggregate the right context and data, allow for the right human in the loop experiences, drive change management, do domain specific evals, manage the security and governance of the data and process, and much more. We’re going to see this layer emerge in every vertical and horizontal category. And ironically, even as models improve at incredible rates, this layer still must exist - and may become even more important and useful. Greater capability enables even more complex tasks to be tackled, amplifying the challenges if you don’t do this well. Was super fun chatting with @sonyatweetybird on all the things going into AI diffusion.

I’m seeing teams at Vercel iterate just as fast on Zig, Go, Rust projects as TypeScript & Python ones. The days of language or runtime choice based on human convenience are over. Agents are the new compilers. They compile intent into fast software.