SandBase Product Update: Sharpening the Agent Infrastructure Layer
A short SandBase product update on agent-first messaging, model registry updates, runtime examples, status visibility, and open-source agent infrastructure assets.
Tag: #agent-infrastructure
Why Production AI Agents Need a Runtime Layer
The agent runtime layer is the production infrastructure between your framework and model. Why it decides durability, isolation, and recovery.
AI Agent Infrastructure Stack 2026
A map of the 2026 AI agent infrastructure stack: inference engines, model gateways, agent frameworks, and dev environments, with the right tool for each layer.
Coder Explained: Secure Environments for Devs and Agents
What Coder is, how it provides governed cloud workspaces for developers and AI agents, and why enterprise agents need this layer.
DeerFlow Explained: ByteDance's SuperAgent Harness
What DeerFlow is, how ByteDance built an open-source SuperAgent harness for multi-hour tasks, and what 'harness' means for agent infrastructure in 2026.
Dify Explained: The Visual Agent Workflow Platform
What Dify is, how its visual workflow builder works for agent development, and where it fits in the agentic AI stack in 2026.
LangChain and LangGraph Explained: The Agent Framework Stack
What LangChain and LangGraph are in 2026, how LangGraph's graph-based agent orchestration works, and when to use them vs newer alternatives.
LiteLLM Explained: The Open-Source Model Gateway for Agents
How LiteLLM works as an open-source proxy for 100+ LLM providers, with routing, cost tracking, and failover for agent stacks in 2026.
Mastra Explained: The TypeScript-First AI Agent Framework
What Mastra is, how the Gatsby team built a TypeScript-native agent framework, and why it matters for JS/TS developers building agents in 2026.
n8n Explained: AI Workflow Automation for Agent Builders
What n8n is, how its 70+ AI nodes enable agent workflows, and when to choose it over Dify or code-first approaches for building AI automation in 2026.
SGLang Explained: The Low-Latency Inference Engine for Agents
How SGLang works, why RadixAttention gives agents faster prefix reuse, and when to choose it over vLLM for production inference in 2026.
vLLM Explained: The Inference Engine Behind Agent Stacks
How vLLM works under the hood, why PagedAttention matters for agent workloads, and where it fits in a production agent infrastructure stack in 2026.
Why Autonomous AI Agents Need Secure Sandboxes
Autonomous AI agents that run code and shell commands need isolation. Why sandboxes are non-negotiable in production, the isolation levels, and how to choose.