AFS

The new site is live. Here is how we plan to bring ARC into the community, data spaces and everyday applications, with migrations, new products and builders taking part along the way.

OpenAI's Agents API turns the Codex loop into a hosted API: sessions, compaction, tools, sandboxes, plugins. That layer is real. It is still not a computer with identity, durable state, and an owner who can walk away with it. ARC attaches at the seam they already documented.

Not a pivot from blockchain to AI. The harder claim is simpler: roads and utilities can be built early, but a digital city only comes alive when residents who can work around the clock walk in.

Most people will not manage API keys. They will hire agents. The real question is not which model is smarter, but whose ground the worker stands on when the job is done.

arc skill ships a small catalog of built-in how-to booklets and can drop them into your agent skill folders. That is useful—and incomplete next to gh skill or AFS’s own .skills trees. Here is the plain map, a short how-to, and the open design gap.

Many companies are building compute for agents: sandboxes, VMs, even digital workers. They answer where untrusted code should run. What agents still lack is a machine that can last: identity, state, constrained authority, verifiable history, and the right to leave. We call that machine ARC.

Blocklet 的執行時。它給開發者一個地方來執行以 Blocklet 描述的應用，連同那個 Blocklet 宣告自己需要的資源。

面向真實 LLM 應用的 agent 框架：函數式、可組合、TypeScript 優先。

ARC 是 Blocklet 的 runtime。它讓開發者把應用、執行位置和所需資源分別說清楚：Blocklet 描述應用，ARC 執行它，AFS 表達它要接觸的資源。

AUP（Agentic UI Protocol）先表達應用要呈現什麼、可以做什麼；runtime 再根據裝置能力呈現合適的部分。重點不是複刻同一張螢幕，而是讓同一項應用保留自己的內容和動作。

每個 agent、每個應用、每個行程，看到的都不是全域世界，而是專門為它投影出來的一個小世界。不在這個世界裡的東西，對它來說不是「沒權限」，而是根本不存在。

一項任務的 context 包括相關資料、可用工具和允許的操作。它們被放進清楚的範圍裡，agent 才知道該從哪裡找資訊、能用什麼完成工作。