About

Most organizations have gotten very good at executing what they already believe. They are much worse at noticing when those beliefs are wrong.

Execution has been getting cheaper for decades, and AI is the moment that trend reaches a tipping point. Organizations can now do more than they can coherently direct. The visible problem is always execution, but the real issue is almost always unclear or unscalable decision-making. That’s what I’m working to help solve, and it’s what I write about here.

I’ve been inside companies at every scale where these operating models get tested and refined, across Silicon Valley, London, and now Toronto. I was making the hard calls that produced the wins, while also owning the consequences of misses.

At Telenav, I joined as a fifty-person startup, grew with it through Series C and IPO, and stayed through post-IPO scaling, public-company scrutiny, and eventually activist investor pressure. That’s a full arc, from early-stage uncertainty through the specific disciplines that the transition to scaling demands. Along the way, I developed the particular envy that every leader at a scale-up feels when they look up at the hyperscalers and wonder why their own company can’t operate with that kind of precision.

That envy is what eventually took me inside two of the most sophisticated operating systems in the world. At Amazon, I learned how a company that treats itself as a machine actually runs the machine. At Meta, I saw how a company that runs on relationships builds coherence through social infrastructure instead of process. Both are best-in-class at what they do. Both have specific failure modes I saw up close. And both taught me something that most people who leave hyperscalers to join scale-ups discover too late: the mechanisms don’t transplant. What works at a hundred thousand people relies on scaffolding that a five-hundred-person company doesn’t have. Copy the artifact without the context and it fails, usually loudly and expensively.

At Workleap, I was brought in to help a 500-person scale-up navigate its own inflection point. The question was how to operate at the edge of what’s next when the old playbook stops holding. It has only sharpened since, and it’s where my writing now starts.

Fifty-person startup. Public-company scrutiny. Activist investor pressure. Hyperscaler process and hyperscaler social infrastructure. Scale-up navigating inflection. Each of these is a distinct operating context, and I’ve been inside all of them, making calls, in senior roles, spanning my nearly 30 years in Technology.

I work with founders at this inflection point, CTOs navigating AI acceleration, and PE-backed CEOs under performance pressure on the specific problem of decision architecture. I also work across VC portfolios, typically introduced through the partners who route these conversations. Redesigning how their organizations actually make calls in the new environment. If that sounds like something you’re wrestling with, get in touch.