From AI pilots to production
I take on a small number of organizations across the Greater Toronto Area. I do the strategy, write the code, and sit with your team until it works.
The short version
I started as a software developer building websites in the early 1990s. From there I moved into infrastructure and architecture, then found my passion in delivery: leading projects and programs, running software engineering teams, and eventually leading a PMO where I owned governance, metrics, and financials.
That path is why this works. I can sit with your executives and talk about value and risk in the morning, pair with your engineers in the afternoon, and know what it takes to keep the thing running at night.
AI is the most interesting shift I have seen in three decades of this. I build with it every day and write about it every other week in Building with AI, my newsletter for engineering leaders and practitioners. The rest of my time goes to helping organizations get past the pilot stage.
How I can help
Most AI programs die somewhere between the deck and the shipped system. I work the whole distance: picking the problems worth solving, building the thing, and staying until people use it.
Forward-Deployed Engineering
I embed with your business, build the first version with your people, and stay until it runs in production.
AI Strategy
Find the few AI opportunities that matter, size them honestly, and sequence them into a plan leadership can fund and engineers can build.
Software Engineering
Move your team to AI-assisted workflows, agentic tooling, and the engineering practices that keep them fast and safe.
How I work
Understand the business before the technology
A short, structured look at your workflows, data, and constraints to find where AI will pay for itself.
Build a proof of concept against real work
A working prototype on your data, with your people. You decide whether to invest based on something real, not a demo.
Work inside your team
I join stand-ups, sit with operators, and build alongside your engineers so the solution fits how you actually work.
Make it dependable
Integrations, security, monitoring, and rollout so the prototype becomes a system the business can rely on.
Leave you self-sufficient
Documentation, training, and a clear operating model. The measure of a good engagement is that you do not need me afterwards.
Building with AI
Why I work this way
FDE job postings grew roughly 729% in a year and the labs committed some $9 billion to deployment ventures. That is not a sign enterprise AI is working — it is a sign 95% of pilots stall at the integration wall, and someone gets paid to close the gap.
Most teams trying to bring an AI system to life start by building the AI. That is the expensive half, the fastest-moving half, and the half where you have no advantage.
Anthropic started watermarking Claude's text this month, and a good part of my feed reacted like it had been caught. The reaction is more revealing than the announcement.
Begin with a conversation
Thirty minutes is enough to tell whether there is a fit. No deck, no pitch, just a frank conversation about your situation.
