Building AI Systems That Hold Up in Production

Most AI systems fail in production not because the models are wrong, but because the architecture wasn't built for the real world. The gap between a working prototype and a system that holds up under real usage is where most teams stall.

I help CTOs close that gap.

How I Help

Three ways I work with CTOs:

Architecture Workshop
A focused engagement to evaluate your current AI stack, identify what breaks under real usage, and surface the challenges standing between your prototype and production. You walk away with clarity on what needs to be solved.

Execution Roadmap
Building on the workshop findings, I design a prioritised plan that sequences your AI work into shippable milestones. This includes the target architecture, dependencies, risk flags, and a clear technical blueprint your team can execute against.

Fractional AI Leadership
Ongoing embedded leadership for teams that need senior AI systems expertise, not more ML research.

How I Work

Every engagement starts with understanding where you are and where you need to get to. I assess your current architecture, team capabilities, and the real-world constraints your system needs to handle, then design a path to production that your team can execute.

The goal is to build clarity and capability inside your team, not create dependency.

Engagement Structure

Most engagements follow three phases:

1. Discovery and Assessment
Understand your stack, team, and product goals. Identify what is blocking production readiness.

2. Architecture and Roadmap
Design the target system and sequence the work into deliverable milestones.

3. Execution and Leadership
Hands-on support through implementation, whether as a workshop, a roadmap, or ongoing fractional leadership.

I work with a limited number of teams at a time to ensure each engagement receives the depth and precision it needs.