AI-Native Development and Consulting
We build products where AI isn't a feature — it's the architecture.
In Practice
Conversational platforms that replace traditional dashboards. Intent-driven interfaces where the agent determines voice, capability, and purpose. Products designed from the ground up for a world where agents mediate the experience.
We help teams navigate what's possible with modern AI tooling — not just integrating models into existing products, but rethinking the product itself. How should the interface work when conversation replaces navigation? How do you structure data when the first consumer is an agent?
This site is built on the same thinking we bring to client work. The agent woven into this experience isn't an add-on — it's the architecture.
What We Think About
The shift to AI-native products raises questions that most teams haven't had to answer yet. How do you structure data when the first consumer is an agent, not a human? What happens when you give up control of the LLM? How do you design interfaces where conversation and visual surfaces work together?
We write about what we're learning — not theory, but patterns tested through building real products.
Exploring what AI-native could mean for your product? Start a conversation — it's what we built this for.
Recent Thinking
View all →Trust, Autonomy, and Principles
Give agents principles, not scripts. Trust comes from authentic data, not prompt constraints. The evolution from explicit guardrails to principle-based prompting — and why the data layer is where trust actually lives.
Content Engineering for the Agent Era
How you structure data for AI consumption determines how agents present it. WAAG over RAG — reasoning at write time, not query time. Freeform content over rigid schemas. And it all starts with the human providing quality data, not the engineer or the agent. Content engineering sits alongside prompt engineering and context engineering as a distinct discipline.
Designing for Multiple AI Consumers
MCP lets any AI tool access your data — Bring Your Own LLM. The value: your product reaches every model and every client without rebuilding for each. The trade-off: when you give up control of the LLM, data quality and tool design become your only control surfaces. What MCP enables, what changes, and what compensates.
Selected Work
View all →
Mosaic
AI-native interactive persona platform. Instead of reading a document about someone, visitors have a conversation with their AI persona — in first person, in their voice. Same data serves four surfaces: conversation, visual display, external AI tools via MCP, and agent-first web discoverability.
Neo
Autonomous AI agent with a web interface for exploring and explaining any public GitHub codebase through natural language conversation. A hybrid architecture where Next.js handles the frontend while a Cloudflare Worker orchestrates agent execution in ephemeral Sandbox containers — solving the fundamental incompatibility between autonomous agents and serverless.
Revision3 — SBX Crypto iGaming Platform
Senior Software Engineer at Revision3, a software development agency specialising in blockchain gaming solutions. Full-stack engineering on SBX — a crypto iGaming casino and sportsbook startup. Multi-faceted role spanning admin dashboard development, consumer frontend, and backend microservices. Pioneered AI-assisted development workflows that codified repetitive patterns into documented, autonomous processes. Web3 technical advisor to the wider team. Full-time role, Jun 2024 – Dec 2025.