const frederik = {
title: "AI Engineer & CEO",
location: "Denmark 🇩🇰",
currentFocus: "Multi-Agent Systems & Long-Running AI Agents",
companies: {
"Omika AI": "Building the future of AI solutions",
"Ace League": "Esports company"
},
expertise: [
"AI/ML Engineering",
"Multi-Agent Systems & Orchestration",
"Long-Running Agents & State Management",
"RAG & Contextual Retrieval",
"Production AI Infrastructure"
],
aiStack: {
frameworks: ["LangChain", "LangGraph", "LlamaIndex", "OpenAI SDK", "Anthropic SDK"],
mlOps: ["Weights & Biases", "TensorFlow", "PyTorch", "Hugging Face"],
vectorDBs: ["Pinecone", "Weaviate", "ChromaDB", "FAISS"],
graphDBs: ["Neo4j"],
validation: ["Pydantic"]
},
infrastructure: {
compute: ["AWS", "GCP", "Azure", "Hetzner", "Vercel", "Cloudflare"],
orchestration: ["Docker", "Kubernetes", "Celery"],
databases: ["PostgreSQL", "MongoDB", "Redis", "Supabase"]
},
askMeAbout: [
"Multi-Agent Orchestration",
"Long-Running Agents",
"LangGraph State Machines",
"Contextual Retrieval & RAG",
"Graph-Based Memory Systems"
],
lifePhilosophy: "Teaching machines to think, one model at a time 🤖✨"
};
| 🧠 Area | 🔧 Capabilities |
|---|---|
| Multi-Agent Systems | LangGraph state machines, agent orchestration, inter-agent communication, long-running autonomous agents |
| Context & Memory | Neo4j graph databases, stateful checkpointing, persistent memory, conversation threading |
| RAG & Retrieval | Contextual retrieval, LlamaIndex pipelines, semantic search, hybrid search, embeddings |
| LLM Integration | OpenAI, Anthropic, tool calling, structured outputs, streaming, Pydantic validation |
| MLOps | Weights & Biases tracking, model deployment, A/B testing, evaluation pipelines |
| Production Infrastructure | AWS / Azure, Kubernetes, Celery workers, async architectures, cost optimization |
