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06:00

5 Questions to Ask Before Choosing an LLM

模型选型五问:开源与闭源、Token 成本、延迟、上下文窗口怎么权衡

Choosing an LLM is not a one-time decision—it must be revisited as models and your app evolve. This guide breaks the choice into five questions: open vs. closed source, cost, latency, performance, and context window. Open models require self-hosting or an API provider like Hugging Face or Groq; closed models are hosted by vendors and priced per token. Latency should be measured with TTFT and TPOT. Benchmarks like Chatbot Arena and Open LLM Leaderboard are useful early indicators, but prone to overfitting—the only real test is running your own evals within your application. Reasoning models such as o1 excel at planning-heavy tasks but cost more and respond slower. Context windows count both input and completion tokens, which is why RAG chunking exists. A practical primer for developers starting model selection.

www.aihero.dev · 8 min · AI Engineering · Context Engineering · Cost Optimization · LLM · Performance
06:00

Cloudflare OS: an open source agent workspace with capability-based governance

Cloudflare OS:让每个员工拥有带权限治理的 Agent 工作台,开源可自部署

Cloudflare has open-sourced Cloudflare OS, the agent workspace it uses internally, to bring AI leverage beyond programmers. A workspace is grounded in company-curated context and skills, and starts each agent with zero access. Resources are exposed as typed bindings, while Gatekeepers—service-specific Workers—hold credentials, enforce policy, and log every observed resource. Sharing a dashboard does not become a way to leak an underlying table, because the platform re-checks the viewer against the observation log. Apps are full-stack Workers with their own SQLite state, and the same server methods are callable by both users and agents. Model routing and spend run through AI Gateway, so admins can set budgets and pick models per task. The code is on GitHub and deployable into a Cloudflare account, with a reference deployment included. Written for engineers working on agent infrastructure, access control, and internal development platforms.

blog.cloudflare.com · 16 min · Agent Infrastructure · AI Agents · Capability Security · Cloudflare · Mcp
06:00

Cloudflare OS: an AI workspace with per-user sandboxed apps

企业级 AI 工作台:每个应用都是可让 AI 改代码的私有沙箱

Cloudflare OS is an open-source AI productivity environment that Cloudflare built for its own workforce. It acts as an operating system for both company operations and AI workloads: instead of fixed document types, every file is a 'Gadget'—a private, sandboxed application that an agent can create, modify, and debug on the user's behalf. A capability-based security layer called Gatekeepers brokers access to external services, logging side effects and letting users approve queued actions in bulk later instead of blocking the agent mid-task. The entire platform runs on Cloudflare Workers and workerd, leveraging Durable Objects, Dynamic Workers, and Facets, and every Gadget has real-time multiplayer collaboration by default. Blueprints let users share the code of an app so others can spawn their own copies. It is early access but substantial, and a valuable reference for engineers exploring agent infrastructure, per-user app sandboxing, and edge-based AI tooling.

github.com · 23 min · Agent Architecture · AI Agents · Cloudflare · LLM · Mcp