Dev. Kelz

Everyone is building AI agents. Very few understand the agentic frameworks that actually power them. In 2025, two frameworks dominate agent development — not as competitors, but as complementary layers: n8n — Visual Workflow Automation What it does • Visually connects AI agents with business tools and APIs • Flow: Trigger → AI Agent → Tools → Action • Removes integration complexity and speeds up deployment Think of it as: The orchestrator that plugs AI into your entire tech stack — LangGraph — Graph-based Agent Orchestration (LangChain) What it does • Enables stateful, cyclical, multi-step agent workflows • Flow: State → Agents → Conditional Logic → State (loops) • Designed for complex reasoning and coordination Think of it as: The brain managing advanced agent decision-making — When to use n8n • AI + business tool integrations • Customer support and ops automation • No-code or low-code workflows for teams • Fast shipping with 700+ integrations When to use LangGraph • Multi-agent reasoning systems • Enterprise-grade AI applications • Cyclical or long-running workflows • Fine-grained state control and memory — Ecosystem strengths n8n • Visual builder for non-developers • Self-hosted, open-source option • Strong business automation community LangGraph • Deep LangChain integration • LangSmith for observability and debugging • Advanced state persistence and control — The real insight 👇 The best AI systems use both. n8n → Visual orchestration and tool integration LangGraph → Agent logic, reasoning, and state Think in layers: business automation and intelligent decision-making — Your turn 👋 What would you build first? A visually simple, tool-connected agent (n8n)? Or a deeply orchestrated, reasoning-heavy agent (LangGraph)?