Agentic AI Architect • Engineering Leader • Scale by Subtraction Pioneer
I design production-ready AI agent systems that are reliable, governed, and truly autonomous—not just sophisticated chatbots. My work focuses on Control Planes, Deterministic Graphs, and the radical idea that systems scale better by removing complexity.
The next generation of AI scaling won't come from adding more tokens—it comes from removing complexity.
We don't ask microservices "nicely" to respect rate limits; we enforce it. Why treat AI agents differently? Build the Kernel for the AI OS.
Don't detect hallucinations after generation—prevent them structurally with multi-dimensional Knowledge Graphs that define what's possible.
Language is for humans. Code is for machines. The best agents are the ones that can't talk—they communicate through structured data.
Open source projects that make autonomous AI systems reliable, governed, and actually useful.
A Safety-First Kernel for Autonomous AI Agents. POSIX-inspired primitives with 0% policy violation guarantee. The operating system layer for agentic systems.
Comprehensive guide to building production AI systems. Documents the Inference Trap, Guardrail Router, and 90/10 Compute-to-Lookup ratio.
My methodology for building reliable AI systems. Focus on removing complexity rather than adding features. Via Negativa applied to software architecture.
Deep dives into agentic systems, architectural patterns, and the philosophy of building AI that works. Published on Medium and Dev.to.
Challenging conventional AI wisdom with practical, battle-tested approaches.
"Sustainable agent architecture does not require agents that remember more; it requires agents that know how to forget."
"Stop trying to prompt-engineer safety. Shift the burden of constraints from the probabilistic LLM to the deterministic Knowledge Graph."
"We don't ask microservices 'nicely' to respect rate limits; we enforce it. Why are we treating AI agents differently?"
Find me on these platforms for articles, code, and collaboration.