Software companies hire me when the commercial model stops keeping up.
Pricing that no longer matches the value. Pipeline that looks healthy until the quarter closes. AI features shipping faster than anyone has decided how to sell them, govern them or charge for them.
Twenty years across fintech, capital markets and B2B software. Full P&L ownership. I do not hand over a deck and leave. I make the decisions clear, build the system and stay accountable to the number.
The commercial model usually breaks before the numbers show it.
Pricing was set when people did the work, and it has not moved. The pipeline looks healthy but conversion and forecasting are unreliable, and nobody can say why. AI features are shipping faster than the company can decide how to package them, what they cost to serve, or what the software is allowed to do on its own.
These read as three separate problems: a pricing problem, a sales problem, a product problem. They are one problem. The commercial system has not kept pace with the business.
Three ways I work with software companies.
The right starting point depends on the problem.
Agentic Margin Audit
A four-week commercial diagnostic for companies asking what AI does to their product, pricing, workflows and margin. It finds where the current model is exposed, what leadership has to decide, and what happens in the next 90 days.
Revenue Engine Programme
A 90-day programme to rebuild the machinery behind predictable revenue: sales stages and exit criteria, CRM architecture, pipeline governance, forecasting, management cadence, AI-enabled workflows. Your team inherits a working system, not a presentation.
Commercial Leadership
Embedded or board-level leadership for companies working through growth, underperformance, turnaround or a major commercial shift. Embedded means I am in the deals, in the CRM, in the operating cadence. At board level it means commercial oversight across revenue, cost, margin and risk.
Where my perspective is unusual
Traditional software gives people tools and charges by the seat. AI-enabled software increasingly does the work itself, which breaks the link between headcount and value. Three things move when that happens: what you can charge for, , and who ends up keeping the margin.
This is the third repricing of software I have worked through. Licences became subscriptions. Value was packaged into seats. Seats are now becoming work. I have run commercial systems on both sides of those shifts.
What the work looks like in practice
Your portfolio company's revenue plan is underperforming. Now what?
Pipeline coverage looks healthy but conversion is poor. The CRO hire hasn't delivered. Stage definitions mean different things to different reps. The board gets a different forecast every month. Sound familiar?
Most commercial due diligence focuses on the spreadsheet. The real risk is in the system underneath it: stages, qualification discipline, coaching cadence, and whether leadership can actually operate the revenue engine at scale.
And a new one is arriving: many portfolio companies are adding AI features. Fewer have answered what happens when agents change usage, pricing, implementation cost and support economics. Seat-based revenue lines can erode before the next valuation prices it in.
Commercial assessment. Evaluate the GTM system, team capability, forecast reliability, and AI readiness. Board-ready findings within 2 weeks.
AI pricing and margin review. A board-level look at where agents change usage, pricing power and support economics in a portfolio company, and what must be governed before they act.
Revenue engine rebuild. 90-day structured programme to install stages, CRM architecture, AI workflows, operating cadence, and coaching discipline. Milestone-based, board-reported.
Ongoing oversight. Board advisory, quarterly commercial reviews, and portfolio-level GTM pattern recognition across fintech, SaaS, and capital markets.
Acquisition support. Commercial due diligence, revenue risk assessment, and post-acquisition GTM integration for fintech and B2B SaaS targets.
Full P&L ownership across two companies. 70+ AEs at Salesforce. I think at company level, not function level.
Discuss a portfolio company →The Operating Margin
Public thinking on who gets paid, who controls the rules, and where the value ends up when technology changes the operating model. Written for operators, boards and investors, not for an algorithm.
Current questions: stablecoin economics and who keeps the float, AI-driven pricing and permission, revenue per employee and AI operating models, and what happens to systems of record when software becomes the operating surface.
Everyone is talking about AI.
Almost nobody has changed how they sell, price or go to market because of it.
If your board is asking what AI does to the commercial model, that is an operating question, not a research question.
Book a working session →30 minutes. One workflow, one pricing model or one live deal.
Three steps to clarity
Fill in the form or email me. Three things: your company, your agent or AI roadmap, and the commercial question on the table.
We pressure-test one workflow, one pricing model or one live deal, and see if there's a fit. No pitch, just signal.
If there's a fit, I send a proposal for the right engagement model within 48 hours.
- Based in
- Dublin, Ireland. Working globally
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