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
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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