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运行时与基础设施
筛选文章 运行时与基础设施
运行时与基础设施
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GPT-6 Prompt Cache 变成了 Agent 的状态层 GPT-6 增加 cache breakpoint、诊断、预热和可变配置。长跑 Agent 需要主动保持共享前缀稳定,并监控缓存命中率。
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LobsterAI: send tasks by phone, run them on your desktop LobsterAI connects phone messages to a local desktop agent. The phone handles tasks and approvals while the computer works with files, terminals, and browsers.
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LobsterAI:手机发任务,本机 Agent 继续干活 LobsterAI 把手机消息接到本机桌面 Agent。手机负责下任务和确认,本机继续处理文件、终端、浏览器和项目。
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Deploying agent backends with Python Workers GA Python Workers GA supports web frameworks and agent libraries. WebAssembly package compatibility remains the main migration boundary.
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Cloudflare Python Workers GA 后,Agent 后端怎么部署 Python Workers 已进入 GA,FastAPI、Django、Flask 以及 openai、langchain、mcp 可以直接运行在 Workers。真正的迁移边界仍是 WebAssembly 包兼容性。
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Why you cannot just rerun an agent after a crash WorkflowAgent, step boundaries, and idempotency keys explain safe recovery after crashes, timeouts, and human pauses, with a proposed Lora PI Kit adaptation.
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Agent 跑到一半进程挂了,为什么不能直接重跑? 用 WorkflowAgent、Step 边界和幂等键解释 Agent 在崩溃、超时和人工暂停后怎样安全恢复,并给出 Lora PI Kit 的迁移思路。
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Where agent credentials belong: host, vault, and broker Where keys belong when coding agents call GitHub, databases, and cloud APIs, and how vaults and credential brokers define access boundaries.
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Agent 的生产密钥该放哪里?Host Boundary、Vault 与 Broker 解释 Coding Agent 调用 GitHub、数据库和云 API 时,应用密钥、执行器密钥和第三方凭据该放在哪里,以及 Vault 与 Credential Broker 的边界。
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Splash: a local LLM inference stack built for each model Splash combines model packages, kernels, memory planning, and compatible local APIs into a model-specific inference stack for coding agents.
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Splash:把本地 LLM 推理栈按模型重做 Splash 把模型包、Kernel、内存计划和本地兼容 API 组合成按模型定制的推理栈,面向 Coding Agent 的本机模型运行。
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Gemini Live: turnComplete no longer means the task is done Gemini Live Extended Thinking separates conversation turns from background task lifecycles. Clients need interaction_status to track actual completion.