Cloudflare Agents turns an agent session into a durable runtime: each agent instance has stable identity, local SQLite, WebSockets, scheduled work, recoverable execution, and tools. It is not just a chat example; it composes Workers, Durable Objects, AI models, Browser, Sandbox, AI Search, and MCP into a deployable agent app.
The Cloudflare AI Stack series covers the infrastructure around AI apps: where models run, how gateway control works, how RAG is built, how agents keep running, how memory is governed, and how browser, sandbox, secrets, data, and observability fit into a product.
Looplane collapses OpenAI-compatible, Responses, Anthropic, Gemini, Workers AI, scripted, and experimental Codex OAuth adapters into one `ModelProvider` contract. The Codex OAuth transport reads SSE but still reduces it inside the adapter into one canonical `ModelTurn`; AgentRunner does not consume token deltas.
Formerly AutoRAG, the managed search primitive: drop files into built-in storage or attach R2 and websites, auto-index with Markdown conversion plus vector and BM25, retrieve with hybrid, RRF, and reranking, and query from Workers via namespace or instance bindings, REST, or MCP.
Upgraded action-maker from hardcoded mock data to live Cloudflare Workers AI generation. The architecture splits into Worker (AI only), Server (data storage), and Frontend (orchestration). Hit two gotchas along the way: Qwen3's thinking block and the Workers AI response format.