27 AI Engineering Patterns in 60 Seconds Each
One production AI engineering pattern per week. 27 episodes and counting. Each Short covers a real pattern engineers hit in production — the problem, the fix, and the code.
RAG
Graph RAG in Practice: How I Wired Neo4j Into My AI Agent's Memory
·390 words·2 mins
Vector RAG retrieves documents. Graph RAG retrieves relationships. When your agent needs to reason across entities, timelines, and decisions, the graph wins. Open Interactive Version → The Problem I Was Trying to Solve # My AI agent PostSingular, running on OpenClaw, talks to me every day. It helps me build Luminar, manages my YouTube channel, and tracks infrastructure decisions across sessions.
Why Vector Memory Alone Isn't Enough: Knowledge Graph Memory for AI Agents
·744 words·4 mins
Vector databases are fast and convenient. But they can’t answer “what did I decide about the auth system 3 weeks ago and why?” For that, you need relationships — and that means a knowledge graph. The Problem with Pure Vector Memory # Most AI memory systems work like this: embed text, store in ChromaDB, retrieve by cosine similarity. It works well for “find things similar to this query.”
AI Engineer
KBC Bank & Insurance Leuven, Belgium 2023 - Present
Enterprise AI Agents
AWS Bedrock LangGraph Python AgentOps Production