I help teams turn AI ideas into agentic, data-driven systems that are understandable, scalable, and actually used in everyday work.

I believe the next wave of software won't just be apps and APIs, but systems of intelligent agents that understand context, remember decisions, and work alongside people.

My focus is on designing these agentic AI systems and the data foundations behind them, so businesses can move from one-off AI features to reliable, evolving intelligence in their everyday operations.

My expertise sits at the intersection of:

• 🧠 Agentic & Generative AI – shaping agent behaviours, goals, and workflows
• 🏗️ System Architecture – designing services, boundaries, and flows that can scale and evolve
• 📊 Data-Driven Design – building the context and foundations AI systems need to make better decisions

I work end-to-end: from defining how agents should think and act, to shaping the data and services that support them, to making sure the whole system can run reliably in production.

When I approach a problem or a system, I focus on:

• 🎯 Intent – what success looks like and who it serves
• 🧱 Structure – clear responsibilities for components, agents, and services
• 🧮 Context – the data and signals a system needs to make good decisions
• ⚙️ Operational reality – deployment, observability, failure modes, iteration loops
• 🤝 Alignment – making sure engineers, product, and decision-makers share the same mental model of the system

The goal is always the same:
Build solutions that teams can run, understand, and evolve with confidence.

This space is for:

• 🤖 Experiments around agentic workflows and orchestration – exploring how agents reason, decide, and collaborate
• 📊 Patterns for context-aware systems – using richer data representations (graphs, vectors) to inform agent decisions
• 🏗️ Architecture ideas and focused examples – showing how I approach AI-driven products from design to production