Agent OS

Agent OS is the 2026 informal term for the layer of infrastructure — agent runtime, tool registry, state store, tracing, evals — that production agentic systems share, comparable to a traditional OS in role.

As agentic systems matured the shared infrastructure pattern emerged: a runtime that handles agent loops + state + checkpoints; a tool registry where MCP servers and custom tools live; a model router that dispatches to the right LLM; a tracing + evals layer for observability; guardrails for safety; memory layers for persistence. Together this stack is sometimes called "agent OS" — by analogy to traditional OS providing scheduling, IO, security. Frameworks like LangGraph, Mastra, OpenAI Agents SDK, and Claude Agent SDK each provide a slice; full stacks compose them. The term is not standardised but appears in 2026 tech press and conference talks.

Common mistakes

• Treating agent OS as a single product — it's a stack of layers.

FAQ

Related terms

• AI agent — An AI agent is a system where a language model autonomously plans and executes a sequence of tool calls to accomplish a goal.
• Agent loop — An agent loop is the repeating cycle of an AI agent — observe state, decide on an action (usually a tool call), execute, observe the result, and repeat — until a goal is reached or a stop condition fires.
• MCP (Model Context Protocol) — MCP is an open protocol from Anthropic that standardises how language models connect to external tools, data sources, and prompts — the USB-C of LLM integrations.
• Model router — A model router picks which language model handles each request based on cost, latency, or task type — the standard production pattern in 2026.

Last updated: 2026-06-01. Raw markdown: https://promtable.com/glossary/agent-os.md.