FAQ
1
I don't run workshops or hand over slide decks. Every engagement starts with the Enterprise Platform Blueprint: a diagnostic that maps your actual technical liabilities, not a generic maturity model. I've scaled a platform to 12,000+ users across 700+ agencies, so I'm not theorizing about friction at scale. I've lived inside it.
2
My engagements begin with a technical diagnostic of your current stack, followed by a phased execution plan. I do not "manage" teams; I instrument them with the guardrails, workflows, and standards required to scale.
3
Yes. Most of my engagements report to a CEO, CIO, or PE operating partner, not just an engineering lead. I translate technical liabilities into what it costs, what it risks, and what it takes to fix, not an abstract severity score.
4
Yes. I provide rapid technical due diligence, post-acquisition platform rationalization, and fractional leadership - exactly the kind of work that protected margins and accelerated delivery in my prior roles.
5
As former EVP of DevOps Platforms at WPP, I led platform transformations across 700+ agencies and 12,000+ users, with positive outcomes in SaaS optimization, process automation, and cross-agency ecosystem rollouts.
6
Cognitive debt is the erosion of shared mental models... the accumulated gap between what a system actually is and what the team collectively understands it to be. I remediate it the same way across every engagement: a documented Remediation Roadmap that replaces guesswork with a quarter-by-quarter plan.
7
A process harness is the infrastructure that keeps you from getting boxed into a corner by a single AI vendor. It's a layer of abstract gateway middleware that decouples your core business logic from any specific model provider. This also lets you dynamically route requests to the most efficient model depending on complexity - routing routine tasks to faster, cheaper models while reserving heavyweight engines for deep reasoning. The result is optimized token management, zero vendor lock-in, and the freedom to swap underlying AI engines whenever a better option drops without rewriting your stack.
8
It can if scoped poorly. Strong engagements include explicit knowledge transfer, process harnesses, and hiring support so capabilities transfer internally.
9
Not necessarily. A mismatched full-time hire creates longer, costlier dependency. Fractional lets you validate needs with real execution data first.
10
The best fractional leaders execute alongside your team, rather than just delivering presentations. The difference is operational accountability for outcomes.
11
Fractional is usually lower total spend in the first year and more flexible. Full-time carries higher fixed cost but builds deeper continuity - if the fit is right.
12
Yes. Many engagements include role definition and candidate assessment to smooth the transition when the time is right.