Notes on AI, agents, and building things that work.
从 Dots、ChatGPT Space、GPT-6.1 Sol、Ultrafast、Decisions API、Agents API、Codex Cloud、Computer Use 到 Plugin Extensions，本文不只列发布内容，而是用一张完整知识关系图解释 OpenAI 如何把 Chatbot 推向 Digital Employee、Multi-Agent Team 与真正的 Agent Platform。 另加入 Artificial Analysis 的第三方 benchmark snapshot，比较 GPT-6.1 Sol、Astra 与 Luna 的 intelligence / cost trade-off，并延伸到 Model、Reasoning Effort 与 Speed Routing。
Continue readingA dated, evidence-backed comparison of Google Gemini 3.8 Flash, Anthropic Claude Fable 5.1, and OpenAI GPT-5.6 Sol for reasoning, coding, AI agents, speed, cost, context, tool use, and real-world engineering workflows.
Continue readingWhy AI model comparisons should show Low, Medium, High, XHigh and Max effort separately instead of comparing only maximum scores.
Continue readingA practical architecture review of Codex Harness: context engineering, deferred tools, sandboxing, verification loops, compaction, persistent execution, and what these ideas mean for building reliable AI agents.
Continue reading从 Codex Harness 的 Context Construction、Deferred Tools、Sandbox、Goal Loop、Compaction 与 App Server，理解真正的 Agent Engineering。
Continue readingWhy long-context AI needs externalized state, bounded recursion, better harnesses, and evaluator-driven learning—not just bigger context windows.
Continue reading长上下文不是终点。真正的变化，是把 Context 从“全部塞进 Prompt”改造成可查询、可计算、可递归、可验证的外部工作环境。本文拆解 RLM、Prime Agent、Continual Harness、Evaluator、自我改进与安全边界，并给出一套可落地的 Thinking Architecture。
Continue readingA practical role-by-role guide to GPT-5.6 Sol, Terra, and Luna: current API pricing, where each model fits across business functions, and how to design a cost-efficient AI routing and permission architecture.
Continue readingA practical guide to Retrieval-Augmented Generation: how RAG connects language models to external knowledge, improves traceability, and supports reliable AI Agents.
Continue reading2026 年的提示工程不只是改写一句提示词，而是一起设计上下文、工具边界、输出契约、评估和恢复机制。
Continue readingPrompt engineering in 2026 is less about magic wording and more about designing reliable context, tool contracts, output schemas, evals, and feedback loops for AI agents.
Continue readingOpenAI has confirmed Astra as its next major model, but it is not yet a public GPT-6 product. This deep dive separates confirmed facts from speculation, explains Astra’s ten mathematical advances, Lean verification, long-horizon reasoning, safety risks, and its implications for coding agents, MCP, RAG, IDP, and AI-native ERP.
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