AI Native Stack

From Semantics to Execution: The complete hierarchy of the Agentic Era.

AI Native Infra is the execution substrate for the Agentic Runtime. We map the ecosystem from abstract semantics down to hardware execution.

1. Agentic Runtime (Semantics)

The abstract definition of how agents think, plan, and act.

Core Semantics

Execution model, state, and workflow definitions.

Execution ModelState ManagementWorkflow DAGSandboxing

Tooling Layer

Model Context Protocol (MCP) and sandbox environments.

MCP ServerMCP ToolsMCP Hub

Reference Implementations

Validating runtime semantics in practice.

McKinsey ARKAutoGPTBabyAGI

2. AI Native Infra (Execution)

The high-performance substrate that powers the runtime.

A. Serving Layer

Inference Engines

High-throughput LLM serving.

Gateway & Routing

Multi-model routing, fallback, and QoS.

LLM GatewayOpenAI-CompatibleInference Router

B. Distributed Compute

Compute Frameworks

Ray, KubeRay, and workflow backends.

RayKubeRaykueuevolcano

Scheduling & Placement

GPU placement, fairness, and binpacking.

GPU SchedulingQuota & FairnessHeterogeneous Cluster

C. Control Plane

Workload Controllers

KServe, Seldon, and autonomous scaling agents.

D. Data Layer

Retrieval Pipelines

RAG pipelines, document ingestion, and transformation.

RAGFlowUnstructuredLlamaIndex

Vector Store

Vector databases and ANN indexing.

E. Observability

LLM Observability

Tracing, evaluation, and telemetry.

OpenLLMetryLangfusearize-phoenix

3. OSS Hub (Supply)

The ecosystem of open source tools and platforms.

Explore the AI OSS Hub

A curated collection of the best open source AI tools.

Browse OSS Hub

4. Roles & Practices

Who builds, operates, and architects these systems?

AgentOps Architect

Design the end-to-end agentic system. Define the runtime semantics and infrastructure requirements.

AI Engineer

Develop agents, workflows, and tools using the runtime primitives.

Platform Engineer

Manage the AI Native Infra, ensuring scalability, reliability, and efficiency.