Praxiserprobte Leitfäden für Teams, die KI in Produktion bringen
Verallgemeinerte Muster aus echten Projekten — ohne Kundennamen, mit allen Lehren. Geschrieben für CTOs, Tech Leads und Staff Engineers, die entscheiden, bezahlen und den Pager tragen.
Die Artikel sind auf Englisch verfasst — der Arbeitssprache unserer Engineering-Teams.
- Agentic AI·12 Min. Lesezeit
Implementing Model Context Protocol (MCP) in Production
Anthropic's Model Context Protocol turned a year of ad-hoc tool-calling hacks into a real interface. Here is what a production-grade MCP stack actually looks like once you leave the tutorial.
MCPLLM agentsLLMOpsAnthropic - Retrieval & Knowledge·11 Min. Lesezeit
GraphRAG vs Traditional RAG for Enterprise Knowledge
Vector RAG is easy to ship and hard to make excellent. GraphRAG is harder to ship and easier to make excellent — for the right question shapes. This guide is the checklist we run before recommending one over the other.
RAGGraphRAGNeo4jKnowledge graphs - LLMOps·10 Min. Lesezeit
Shipping LLM Features Safely: Evals, Guardrails and Rollout
The gap between an impressive demo and a feature you can leave running unattended is where most GenAI projects die. This is the playbook we run to close it.
LLMOpsEvalsGuardrailsRollout