About AI Native Landscape

AI Native Landscape is a curated map of open source projects for the AI Native stack. It focuses on tools, agents, runtimes, platforms, and infrastructure that help developers understand a fast-moving ecosystem through structured classification, bilingual descriptions, and transparent scoring.

What This Site Covers

• Agent systems, MCP, context engineering, RAG, AI runtimes, and AI infrastructure
• Open source projects with verifiable GitHub repositories and baseline metadata
• Long-term curation rather than one-time aggregation

What This Site Does Not Cover

• Closed-source products
• Foundation models by themselves
• Pure academic papers without practical project surfaces

About Jimmy Song

Jimmy Song focuses on research and open source practice in AI-Native Infrastructure and cloud native application architecture.

He is currently Open Source Ecosystem VP at Dynamia.ai, a CNCF Ambassador, and the founder of the Cloud Native Community (China).

His long-term work centers on AI-Native Infrastructure, GPU virtualization, heterogeneous computing scheduling, cloud native architecture evolution, and open source ecosystem collaboration.

AI Native Landscape reflects that same long-term approach to ecosystem curation: structured information, explicit taxonomy, and engineering-verifiable signals instead of trend chasing.

Why This Project Exists

This project exists to help developers quickly understand where a project sits in the AI Native ecosystem, compare adjacent tools, and discover open source projects worth tracking.

Trust and Methodology

• Only verifiable open source repositories hosted on GitHub are included
• Classification and descriptions are maintained in both English and Chinese
• Scoring methodology is public and meant to be understandable
• The directory is continuously maintained instead of dumped as a static list