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agentfield vs LangGraph

Open-source control plane that runs AI agents as microservices: write plain Python/Go/TS functions, get REST endpoints with routing, queues, retries, memory and tracing — one laptop to 10k agents. — versus — Build stateful, multi-actor LLM apps as graphs — durable execution, human-in-the-loop, streaming.

The curated verdict

Same job — production multi-agent systems — opposite shape. LangGraph is an in-process library: model your workflow as a stateful graph with durable execution. agentfield is an out-of-process control plane: plain functions become REST microservices and the platform handles fan-out, queues and retries, explicitly rejecting graph wiring. Library and embedded → LangGraph; platform and service-oriented → agentfield.

agentfieldLangGraph
Stars2.4k37k
Forks3746.3k
LanguageGoPython
LicenseApache-2.0MIT
Last activityyesterdayyesterday
Topicsagents, orchestrationagents, orchestration
Curated connections416

agentfield — the curator's take

The 'agents as a backend' play: write plain functions (no DSL, no graph wiring), and the Go control plane turns each into a REST endpoint any service can call — with fan-out to thousands of parallel agents, queues, retries, versioned deploys, observability and identity/audit built in. Reach for it when agents must be production infrastructure callable by frontends, cron jobs and other services — not a chat window. NOT for notebook experiments or a single local agent (a control plane + SDK is real operational commitment), and it won't give you reasoning-pattern libraries — you still design the agent logic it hosts. Its prompt-to-backend flow (/agentfield in Claude Code/Cursor) is a nice on-ramp, but evaluate the runtime, not the demo.

LangGraph — the curator's take

You reach for LangGraph the moment a simple agent loop stops being enough — when you need state that survives a crash, a human approving a step mid-run, or a flow that can loop back on itself. Most teams arrive here from plain LangChain and don't leave. If all you want is a quick tool-calling agent, this is more machinery than you need — start lighter and come back when you hit the wall.