My First Month at Dynamia: Why AI Native Infra Is Worth It
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.
AI-Native Infrastructure
Through writing, publishing, and engineering practice, systematically build engineering methodologies for AI-native infrastructure.
What Is AI-Native Infrastructure?
Infrastructure redesigned for AI systems — not retrofitted from cloud-native stacks.
Agent / AI Applications
Agentic Runtime & Context
Inference · Training · Governance
GPU & Accelerated Infrastructure
- NON-DETERMINISM AI workloads are non-deterministic by nature
- AGENT-FIRST Agents, not services, are primary execution unit
- FIRST-CLASS RESOURCES GPU, context, and tokens become first-class resources
- GOVERNANCE > DEPLOY Scheduling and governance matter more than deployment
Core Technology Domains
These directions constitute my ongoing research focus, emphasizing practical engineering abstraction and implementation boundaries.
AI Native Infrastructure
I focus on GPU virtualization, inference, and agent runtime and engineering abstractions, thinking about how to deliver capabilities to production environments stably and efficiently.
Cloud Native
I study Kubernetes’s boundaries and evolution under AI workloads, including resource scheduling, elastic scaling, and multi-tenant governance.
Open Source
I participate in and promote the AI-Native Infrastructure open source ecosystem from an engineer’s perspective, valuing verifiable, evolvable designs and collaboration methods.
Representative Writing
Documenting my research and thinking in AI × cloud native, from engineering practice to architectural abstraction.
A look back at the major changes in 2025: shifting from Cloud Native to AI Native Infrastructure, AI tool ecosystem, and major website improvements.
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.
About Jimmy Song
Jimmy focuses on AI-Native Infrastructure and cloud native application architecture, researching engineering problems such as GPU virtualization, heterogeneous computing scheduling, and system governance. Jimmy currently serves as Open Source Ecosystem VP at Dynamia.ai, and is also a CNCF Ambassador and founder of the Cloud Native Community (China).
