The previous two posts covered how events flow from the SDK to the UI. This post focuses on visualizing one specific type of event: tool calls. Tool invocations are the most frequent operations in an Agent application. A typical task might call tools twenty or thirty times—reading files, writing files, executing commands, searching code. If every tool call renders as the same gray block, it's hard
Post 1 covered how AgentBridge converts the SDK's AsyncStream<SDKMessage> into [AgentEvent]. This post looks at what [AgentEvent] becomes — how TimelineView renders 18 event types, handles scroll behavior, and stays smooth when the event count gets large. TimelineView is the main body of the workspace, filling all the space between the sidebar and the input box. Its view hierarchy is shallow: Time
OpenAI revenue is still the number people reach for when they want a leaderboard. But the cleaner frame is different: Anthropic appears to be building a different kind of AI business, one centered on enterprise customers, safety positioning, and less dependence on mass-market fame. That distinction matters because public discussion keeps collapsing three separate things into one scorecard: revenue
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
LLM Foundry: the boring stack that makes an LLM actually useful Most AI projects are built backwards. People start with the model and only later discover they needed a memory system, semantic retrieval, tool use, tests, and a fallback plan for when one provider decides to nap for no visible reason. That is the part I care about now. LLM Foundry is the workshop around an LLM — not the model itsel
🌟 مراجعة كورس Teaching AI Fluency من Anthropic كلنا نتحدث عن الذكاء الاصطناعي، لكن كم منا يعرف كيف يُعلِّمه بشكل صحيح؟ أنهيت للتو كورس Teaching AI Fluency من Anthropic، وكان مختلفاً عن كل ما توقعته. الكورس لا يتحدث عن "كيف تستخدم الذكاء الاصطناعي" بل عن كيف تُصمّم تجارب تعليمية حوله — وهذا فرق جوهري. حلقة التفويض والحرص (Delegation-Diligence Loop): متى تثق بالذكاء الاصطناعي ومتى تتحقق. حلقة