AI 2026: Infrastructure, Agents, and the Next Cloud-Native Shift
2026 AI’s turning point: not models, but infrastructure, agentic runtimes, GPU efficiency, and new organizational forms.
AI Engineering
LLM, AI Native Infra and Agentic AI.
An analysis of Block’s Goose project, why it became one of the first Agentic AI Foundation (AAIF) projects, and what this means for Agentic Runtime and the evolution of AI-Native infrastructure.
How ARK uses cloud-native architecture and declarative runtime to drive engineering adoption of multi-agent systems and shape the Agentic Runtime ecosystem.
Can Open Source Suddenly Disappear? An AI Chat Dev Tool Went 404 Overnight
Lunary, an open-source project in the AI DevTool space, suddenly deleted its GitHub repo, exposing the instability of commercial open source projects.
Agentic AI Foundation and AI Native Standardization
An analysis of the background, strategic urgency, differences and division of labor between Agentic AI Foundation (AAIF) and CNCF/CNAI, and its significance for the AI Native era.
Bun × Anthropic: Runtime Structural Signal
Bun’s acquisition by Anthropic marks the first time a general-purpose language runtime is integrated into a large model engineering system, revealing a structural trend for AI-native runtimes.
Analyzing Ark from architecture, semantics, community activity, and engineering paradigms to reveal its impact on 2026 AI Infra trends and the ArkSphere community.
In-Depth Analysis of Ark: Kubernetes for the AI Era or a New Engineering Paradigm Shift?
Analysis of McKinsey’s Ark project: architecture, CRDs, control plane, design paradigms, production readiness, and implications for ArkSphere and AI infrastructure.
From Using AI to Relying on AI
AI’s real turning point is moving from using AI tools to building AI systems. Why the era of AI engineering hasn’t begun, and the developer opportunity in the next three years.
A practical Antigravity setup guide for developers who want a VS Code-style AI IDE, including marketplace switch, AMP and CodeX installation, and workflow tuning.
NotebookLM Usage Experience and Best Practices
Based on months of deep usage, this article analyzes how NotebookLM helps me learn new technologies, read complex documents, generate teaching outlines, and shares future improvement expectations.
Kimi K2 Thinking: The True Awakening of China's Thinking Model
Kimi K2 Thinking’s open source marks China’s entry into thinking models. This article reviews its technical approach and compares it with Claude and Gemini.