LLM Applications • Graph-Based AI • Enterprise Architecture • MLOps
🏗️ Architect production AI systems — from RAG pipelines to multi-agent orchestration, building intelligent applications that scale
🧠 Apply AI design patterns — modular architectures, pipeline orchestration, and evaluation frameworks that ensure reliability
🕸️ Graph-powered intelligence — knowledge graphs, semantic reasoning, and network-based ML for complex domains
- Modularity First: Composable AI systems with clear separation of concerns and independently testable components
- Evaluation-Driven: Rigorous testing frameworks, human-in-the-loop validation, continuous performance monitoring
- Practical Over Perfect: Ship iteratively, measure relentlessly, optimize where it matters
- Data-Centric Design: 90% engineering, 10% modeling — the data architecture makes or breaks the system
- LLM Applications: RAG systems, prompt engineering, context management, retrieval optimization
- AI Operations: MLOps pipelines, model serving patterns, A/B testing, deployment strategies
- Graph & NLP: Knowledge graphs, entity resolution, semantic search, graph algorithms
- Enterprise Integration: TOGAF-aligned architectures, governance frameworks, responsible AI practices
🔬 Multi-agent orchestration patterns — coordinating specialized AI systems for complex workflows
⚡ LLM evaluation frameworks — moving beyond vibes to measurable, reproducible quality
🚗 Weekend drives to National Trust spots — because good architecture needs perspective
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“Graphs are everywhere — and so are cool AI systems.”