How API Contract Testing Prevents Production Failures
API contract testing helps you catch breaking changes before they disrupt your workflows. See how n8n validates API responses while your automations run.
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When to Use an LLM Knowledge Graph or a Vector RAG
An LLM knowledge graph and vector RAG ground models differently. See when to use each, how to build a knowledge graph from text, and how to run both smoothly.
iPaaS vs. API Management: What Engineers Choose When Both Fall Short
Compare iPaaS versus API management tools. See why engineering teams that need execution control, self-hosting, and code-level extensibility reach for n8n.
You can now top up your n8n Assistant credits
On n8n Cloud, you can now buy extra Assistant credits when you run out - manually or with auto top-up. Here's how it works.
Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents
Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents
Introducing n8n Agents
n8n now has a new type of Agent. Describe what an agent should do, choose a model, the tools and workflows it can use, and it's ready to go!
Prompt Testing Frameworks for Production AI Workflows
Still guessing if your prompts work? Learn how to build a systematic prompt testing framework that catches regressions before they reach production.
How the Transactional Outbox Pattern Guarantees Event Delivery
Learn how the transactional outbox pattern prevents dual writes and enables reliable event publishing for scalable event-driven architectures.
Reducing AI Workflow Latency: Patterns That Actually Work
Learn how to reduce AI workflow latency with production patterns for latency optimization: model routing, caching, parallel execution, timeouts, and budgets.
API Rate Limiting for More Reliable Workflows
API rate limiting doesn't have to mean failed workflows. Learn how limits work and how to handle 429s with retries, batching, and smart pacing.
Try new models and services, skip the account setup
Starting with n8n v2.36, you can now use supported AI models and tool services on select n8n Cloud plans without creating a provider account or generating an API key. Choose Gateway credits instead of adding a credential. Six model providers and five tool services work right out
Reflection Pattern: AI Agents Self-Correct in Production
Reflection pattern for LLMs: a self-critique loop that improves correctness, clarity, and reliability with measurable quality gates, ROI, and safety controls
Process Orchestration: Execution Models, Observability, and Production Challenges
Compare deterministic, dynamic, and agentic process orchestration models to build reliable, scalable workflows with visibility across enterprise systems.
MCP vs. API: Key Differences and When To Use Each
MCP vs. API: Learn how the Model Context Protocol differs from traditional APIs, when to use each, and how to combine both in n8n.
Autonomous AI Agents: Architecture and Risk Mitigation
Discover what autonomous AI agents are and how they work. Learn different levels of autonomy, common use cases, and ways to mitigate risks.
Investing in multi-agent AI safety research
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
Adding MCP Tools to Reachy Mini
Adding MCP Tools to Reachy Mini
Co-Scientist: A multi-agent AI partner to accelerate research
Introducing Co-Scientist, a collaborative AI partner built with Gemini to help researchers accelerate scientific breakthroughs.
Le Chat. Custom MCP connectors. Memories.
Le Chat. Custom MCP connectors. Memories.
Empowering product development with an agentic workflow
Empowering product development with an agentic workflow