Core Model Overview
A four-layer model (Yin-Yang, Five Elements, Yun, Qi) for understanding AI infrastructure as an evolving organic system
2026/2/10
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The Yin-Yang Layer: Dynamic Balance of System States
Understanding system tensions: expansion vs. constraint, innovation vs. governance, speed vs. stability in AI infrastructure
2026/2/10
articleCard.readMoreFive Elements Layer: Classification and Collaboration of System Roles
Five system roles: data, models, compute, platforms, and hardware—how they interact and balance in AI infrastructure
2026/2/10
articleCard.readMoreThe Yun Layer: Stages and Cycles of System Evolution
System evolution stages: exploration, platform, scale, and rebalancing phases in AI infrastructure growth
2026/2/10
articleCard.readMoreQi Layer: Effective System Flow and Pressure Fields
Effective flow and pressure distribution in systems—data flow, signal propagation, and system health monitoring
2026/2/10
articleCard.readMoreDynamic Relationship Modeling: Five Elements Flow Under Yin-Yang Balance
Integrating Yin-Yang, Five Elements, Yun, and Qi layers to explain complex AI infrastructure system behavior
2026/2/10
articleCard.readMoreEngineering Practice Guide: Architecture Decisions Guided by Theory
Practical principles for applying the Yin-Yang Five Elements Qi model in GPU scheduling, Agent Runtime, and platform governance
2026/2/10
articleCard.readMoreSystem Diagnosis Principles: Criteria for Health Status
Five-dimensional diagnosis framework for AI infrastructure health: element balance, flow smoothness, tension dynamics, stage alignment, and runaway warnings
2026/2/10
articleCard.readMoreConclusion and Outlook
Core value and applications of the Yin-Yang Five Elements Qi-Yun model for AI infrastructure architects
2026/2/10
articleCard.readMoreWhat Is AI-Native Infrastructure?
Core definition, boundaries, and evaluation criteria for AI-native infrastructure, focusing on model behavior, compute scarcity, and uncertainty governance.
2026/1/18
articleCard.readMoreAI-Native Infrastructure One-Page Reference Architecture: Three Planes + One Loop
Three planes (Intent, Execution, Governance) + closed-loop feedback for AI-native infrastructure architecture alignment.
2026/1/18
articleCard.readMoreWhy Start with Compute Governance, Not API Design
Discussing Intent vs Consequence, why compute and cost are the first-order constraints of AI-native infrastructure.
2026/1/18
articleCard.readMoreOperating and Governing AI-Native Infrastructure: Metrics, Budget, Isolation, Sharing, SLO to Cost
Analyzing the closed-loop governance of metrics, budgets, isolation, and sharing in AI-native infrastructure, and explaining how SLO maps to cost and risk.
2026/1/18
articleCard.readMoreOrganization and Culture: How the Operating Model Changes
Redrawing boundaries across platform, infra, ML, and security, and transforming accountability and collaboration in the AI era.
2026/1/18
articleCard.readMoreMigration Roadmap: From Cloud Native to AI Native
An actionable roadmap for AI-native migration, covering bypass pilot, domain isolation, AI-first refactoring, and anti-patterns, with focus on governance loops and organizational contracts.
2026/1/18
articleCard.readMoreGlossary
Bilingual glossary of core AI-native infrastructure terminology for aligning organizational language.
2026/1/18
articleCard.readMoreExecutive Checklist (10 Questions)
Ten critical questions for CEO/CTO to evaluate AI-native infrastructure readiness.
2026/1/18
articleCard.readMoreAI Learning Resources: 44 Curated Collections from Our Cleanup
A curated collection of AI learning resources we removed from the AI Resources list: awesome lists, courses, tutorials, and cookbooks. These educational materials deserve their own spotlight.
2026/2/8
articleCard.readMoreStanding on Giants' Shoulders: The Traditional Infrastructure Powering Modern AI
Before ChatGPT and TensorFlow, there was Hadoop, Kafka, and Kubernetes. This post honors the traditional open source infrastructure that became the foundation of today's AI revolution.
2026/2/8
articleCard.readMoreMy First Month at Dynamia: Why AI Native Infra Is Worth the Investment
Observations from my first month at Dynamia: From cloud native to AI Native Infra, why this direction is worth investing in, and the key issues and opportunities in compute governance.
2026/2/6
articleCard.readMoreThe True Inflection Point of ADD: When Spec Becomes the Core Asset of AI-Era Software
Exploring how Spec becomes the governable core asset in Agent-Driven Development (ADD) and the trend toward control-plane engineering systems.
2026/1/20
articleCard.readMoreAI Voice Dictation Input Methods Are Becoming the New Shortcut Key for the Programming Era
Comparing Miaoyan, Zhipu, and Shandianshuo voice input methods for developers: speed, stability, command capabilities, and cost models.
2026/1/18
articleCard.readMoreFrom Spatial Data to AI Open Source: Technical Standards, Data Sovereignty, and the Global Divide
How technical standards and data sovereignty shape AI open source paths and infrastructure competition in the global AI era.
2026/1/11
articleCard.readMoreJoining Dynamia: Embarking on a New Journey in AI Native Infrastructure
Joining Dynamia as Open Source Ecosystem VP to drive AI-native infrastructure ecosystem development, transforming compute from hardware consumption to core asset.
2026/1/7
articleCard.readMoreRunning Parallel AI Agents on My Mac: Hands-On with Verdent's Standalone App
A hands-on experience with Verdent's standalone Mac app, exploring how parallel AI agents, isolated workspaces, and task-oriented workflows change real-world development.
2026/1/4
articleCard.readMore2025 Annual Review: The Transformation Journey from Cloud Native to AI Native
A look back at the major changes in 2025: shifting from Cloud Native to AI Native Infrastructure, AI tool ecosystem, and major website improvements.
2025/12/31
articleCard.readMoreThe Butterfly Effect After Manus Was Acquired by Meta
Manus's acquisition by Meta sparked polarized opinions. This article explores the butterfly effect in AI applications and key lessons for entrepreneurs on growth strategies.
2025/12/30
articleCard.readMoreAI Infra Open Source in China: Analysis of Beijing and Shanghai's Plans
Beijing and Shanghai's open source plans reveal opportunities and challenges for China's AI infrastructure, balancing technology and governance.
2025/12/25
articleCard.readMoreFrom 2025 Onwards, Software Engineering Shifts from Code-Centric to Runtime and Cost-Centric
In 2025, software engineering shifts from code-centric to runtime and cost governance. AI and Agents move complexity to runtime, compute, and budget layers, reshaping engineering value.
2025/12/24
articleCard.readMoreFrom Cloud Native to AI Native: Why Kubernetes Is the Foundation for Next-Gen AI Agents
Explores why AI Agents need Kubernetes infrastructure and how Agent orchestration, MCP services, and AI gateways enable production-ready AI architectures.
2025/12/24
articleCard.readMoreAI Open Source Landscape: A One-Stop Guide to AI Project Navigation and Scoring System
Comprehensive introduction to the AI Open Source Landscape's positioning, interface, scoring model, and data mechanisms to help developers efficiently discover quality AI projects.
2025/12/23
articleCard.readMoreAI 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.
2025/12/19
articleCard.readMoreWhat I Saw at COSCon'25: The Real State of Open Source in China
From an engineering and organizer's perspective, real changes at COSCon'25: AI as the default backdrop, discussions returning to engineering issues, and Chinese open source entering a long-term phase.
2025/12/18
articleCard.readMoreDecoding Goose: Why It Joined AAIF and What This Means for Agentic Runtime
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.
2025/12/12
articleCard.readMoreARK: Multi-Agent Systems Are Finally Entering the Engineer's World
How ARK uses cloud-native architecture and declarative runtime to drive engineering adoption of multi-agent systems and shape the Agentic Runtime ecosystem.
2025/12/11
articleCard.readMoreCan 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.
2025/12/11
articleCard.readMoreCNCF in the AI Native Era? The Agentic AI Foundation Is Officially Established
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.
2025/12/10
articleCard.readMoreKCD Beijing + vLLM 2026: Kubernetes × AI × LLM Inference, A Community-Driven Tech Event
KCD Beijing + vLLM 2026: Kubernetes × AI × LLM Inference, A Community-Driven Tech Event
2025/12/5
articleCard.readMoreBun Acquired by Anthropic: A Structural Signal for AI-Native Runtimes
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.
2025/12/3
articleCard.readMoreAgentic Runtime Realism: Insights from McKinsey Ark on 2026 Infrastructure Trends
Analyzing Ark from architecture, semantics, community activity, and engineering paradigms to reveal its impact on 2026 AI Infra trends and the ArkSphere community.
2025/12/2
articleCard.readMoreIn-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.
2025/12/2
articleCard.readMoreArkSphere Community Launch
ArkSphere Community launches for developers building AI Infrastructure, runtimes, and agent systems. Focused on open-source, verifiable, and evolvable solutions.
2025/11/30
articleCard.readMoreFrom Using AI to Relying on AI: Why the Era of AI Engineering Has Yet to Begin
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.
2025/11/29
articleCard.readMoreTurning Antigravity Into a VS Code-Style AI IDE
How to configure the extension marketplace, install AMP and CodeX plugins, and adjust editor settings to make Antigravity behave like VS Code for AI development.
2025/11/20
articleCard.readMoreCloudflare November 18 Global Outage: The Dangers of Implicit Assumptions in Modern Infrastructure
An analysis of the Cloudflare global outage on November 18, 2025, exploring implicit assumptions, automated configuration pipelines, and systemic risks in modern infrastructure.
2025/11/19
articleCard.readMoreThe Second Half of Cloud Native: The Era of AI Native Platform Engineering Has Arrived
A decade of cloud native evolution, a look ahead to AI-Native Platform engineering, technical layers, and key changes. KubeCon NA 2025 signals a new era.
2025/11/17
articleCard.readMoreNotebookLM: My Most Recommended AI Tool for Learning and Knowledge Organization
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.
2025/11/17
articleCard.readMoreHelm v4: Paradigm Convergence and Plugin System Rebuild
An analysis of Helm 4's core changes, including Server-Side Apply, WASM plugin system, kstatus status model, reproducible builds, and content hash caching, with a timeline review of Helm's history.
2025/11/14
articleCard.readMoreKimi 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.
2025/11/14
articleCard.readMoreTRAE SOLO vs VS Code: Rethinking Coding Tools from the Perspective of AI Engineering Entities
A comparison of TRAE SOLO and VS Code (Copilot, Agent HQ) via the AI Engineering Entity framework, focusing on automation, collaboration, model transparency, and engineering roles.
2025/11/14
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