I work with CTOs, VPs of Engineering, and executive teams on architecture challenges that are too complex for a quick hire and too important to get wrong.
You've seen what AI agents can do. Maybe your team has built a few prototypes. But moving from demo to production - with proper tool orchestration, policy guardrails, observability, and governance - is a different problem entirely. You need someone who knows how these systems work from the inside.
I design agentic AI architectures that connect LLMs to your real-world systems safely and reliably. As a maintainer of the Model Context Protocol, I bring first-hand knowledge of the tooling layer that sits between AI models and enterprise infrastructure. I define the agent workflows, the policy boundaries, and the observability stack - then I help your team ship it.
A production-grade AI agent architecture with clear governance boundaries, integration patterns your team can extend, and measurable operational value - not a proof of concept that stalls.
The monolith served you well - until it didn't. Every change takes longer than it should. Teams step on each other. Deployments are risky. The board is asking why the technology can't keep pace with the business. You need a target-state architecture and a credible path to get there without stopping the engine mid-flight.
I define target-state architectures and technical roadmaps for commerce and customer platforms. That means domain modelling, service boundaries, eventing patterns, platform guardrails, and cost/performance trade-offs - all grounded in what your teams can realistically execute. I don't hand over a diagram and leave. I stay through the migration, aligning engineering, product, and leadership on sequencing and trade-offs. Past engagements have included enterprise programmes for Mizuno, La Prairie, and Active Brands.
A target-state architecture your teams understand and believe in, a phased migration plan with clear business milestones, and hands-on support through the hardest part - the cut-over.
Your engineering team is strong but stretched. You have a re-platform, a new product line, or an AI initiative that needs dedicated capacity - and you can't afford to spend six months hiring, onboarding, and aligning new engineers with your architecture. You need senior people who can ship from week one, not a bench of juniors who need hand-holding.
I assemble dedicated senior engineering teams built around the architecture we define together. These aren't borrowed engineers with no context - they're experienced professionals who understand the system they're building into, because the architecture and the team come from the same source. I handle the technical leadership, the architectural alignment, and the delivery governance. Your team stays focused on what they're already doing. Mine picks up the new workstream and delivers it at the standard your organisation expects.
Every engineer I place is senior. I don't do bench staffing, I don't backfill with juniors, and I don't hand you CVs and disappear. The teams I build operate as an extension of your engineering organisation - same standards, same rituals, same accountability. Most of my engineering teams have been with their clients for years - not because of contractual lock-in, but because they've become a genuine part of the delivery organisation. That's the benchmark I hold myself to.
A senior engineering team that's architecturally aligned from day one, integrated into your delivery rhythm, and focused on a defined programme of work - without the six-month hiring cycle or the risk of a context gap between the architecture and the people building it.
You're moving off a legacy commerce platform - or building a new one from scratch. The vendor landscape is overwhelming. Everyone's pitching “composable” and “headless” but nobody's telling you how to actually get there with 30–80 engineers, existing integrations, and a business that can't afford downtime.
I lead composable commerce re-platforms end-to-end - from discovery through vendor evaluation, architecture definition, and delivery governance. I've run these programmes on both sides: as the technical lead building the platform, and as the architect defining the target state. I know where these projects go wrong, and I design around those failure modes from day one. I've led programmes like these for brands including Pandora, Birkenstock, Le Creuset, and Daily Mail.
A composable platform architecture built for your specific business constraints, a delivery structure that keeps 30–80 engineers aligned, and an architecture that's designed to evolve - not one you'll need to replace again in three years.
I start by listening. Before I draw a single diagram, I need to understand the business context, the organisational dynamics, and the real constraints - not just the technical ones. The best architecture in the world fails if the team can't execute it or the business won't fund it.
Most of my engagements begin with a short discovery phase - typically a few focused sessions with your technical and business leadership. From there, the engagement takes one of three shapes: I embed with your team as a hands-on architect, I operate as an advisory architect, or I assemble a dedicated senior engineering team to deliver a defined programme of work alongside your existing organisation. Often it's a combination.
I work with your existing teams, not around them. The goal is always to leave your organisation stronger than I found it - with an architecture they understand, own, and can evolve without me.
Agentic AI architecture is the design of AI systems where autonomous agents use tools to interact with enterprise infrastructure. It involves defining agent workflows, policy boundaries, tool orchestration via protocols like MCP (Model Context Protocol), observability stacks, and governance models to move AI from prototype to production safely.
The Model Context Protocol (MCP) is an open protocol that standardises how AI models connect to external tools and data sources. It provides the tooling layer between AI agents and enterprise systems, enabling safe, reliable interactions. Konstantin Konstantinov is a maintainer of the MCP TypeScript SDK.
An enterprise should consider migration when: every change takes longer than it should, teams step on each other during development, deployments are risky, and the technology cannot keep pace with business growth. A migration requires a target-state architecture and a credible roadmap that does not halt business operations.
Composable commerce is an approach to building eCommerce platforms using best-of-breed, API-first components (MACH architecture: Microservices, API-first, Cloud-native, Headless) instead of monolithic suites. It enables businesses to swap or upgrade individual components without rebuilding the entire platform.
Engagements begin with a short discovery phase — focused sessions with technical and business leadership. From there, the engagement takes one of three shapes: an embedded hands-on architect role, an advisory architect role, or assembling a dedicated senior engineering team to deliver a defined programme of work. Often it is a combination. The goal is always to leave the organisation stronger than before.
Most conversations start with a problem, not a service line. Tell me what you're facing and we'll figure out the right approach together.
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