OpenAI 把整套 Codex Harness 开源了!
除了 CLI,还有 Skill 和运行环境,想学习 Agent 构建的朋友们有福啦!
github.com/openai/codex
LLM Basteltisch retweeted
every ai team ships changes all the time. a new model, a new tool, a prompt edit
each one can fix one bug and quietly break another
the agent harness makes your model useful. the eval harness tells you what broke before a customer does
Google just dropped a 9-page PDF on building agents that run for days - 6 layers to an agent that waits in line, survives a crash and never charges you twice:
the formula: Long-Running Agent = Trigger + Runner + State + Resumable Workflow + Human Gate + Guards
here's how to build your own in 6 layers:
layer 1 → trigger - the model can't set a timer. a scheduler hits a /wake endpoint and the agent runs again
layer 2 → runner - adk web is a dev tool. your server owns the runner, the sessions and the storage
layer 3 → state - session in a real database, preferences under user:, facts in memory. a restart loses nothing
layer 4 → resumable workflow - kill the server mid-queue. it resumes at the same node. finished steps never run twice
layer 5 → human gate - the agent asks for a budget and waits for a yes. the pause survives restarts too
layer 6 → guards - re-check the seat before buying, one idempotency key per order. a retry never charges twice
most agents die when the request ends. this is how you build one that doesn't.
the workflow in layer 4 is a graph. how to design the whole agent system that way is in my article below
LLM Basteltisch retweeted
Anthropic 把 Claude Code 使用的沙箱运行时开源了,叫 sandbox-runtime。
macOS 用系统自带的 Seatbelt,Linux 用 bubblewrap,不需要额外启动完整容器,就能限制 Agent 对文件系统和网络的访问。
而且不只支持 Claude Code,自己的 Agent、MCP Server,甚至普通命令行程序都能用。
但这里有个很现实的问题:
Agent 写代码不只是改文件,还要装依赖、拉文档、访问 API。网络白名单收得太紧,任务可能跑不下去;放得太宽,沙箱的安全价值又会打折扣。
所以 Agent 沙箱真正难的,不只是把权限关起来,而是怎么在安全和可用性之间找到平衡。
开源地址:
github.com/anthropics/sandbo…







