Every fintech I meet says they want to move at Revolut speed. Almost none of them are willing to accept what that actually requires.
When I was VP of Global Business, we were shipping new products at a cadence most financial services companies couldn't comprehend. Not because we had more people — we usually had fewer — but because we had built a machine for iteration. The cycle from idea to live product was compressed to the point that the strategic question changed: not can we build this, but which of these is worth building first.
What made that velocity possible
Ruthless prioritisation at the top, genuine autonomy at the team level, and a culture that treated a fast failure as strictly preferable to a slow one. We didn't launch perfect products. We launched products that were good enough to learn from, then iterated in public — quickly, based on real signal, with the willingness to walk things back if the data demanded it.
This is harder than it sounds. Most organisations slow down not because they lack talent but because they lack clarity. Every layer of approval, every cross-functional dependency that isn't explicitly managed, every strategy that isn't specific enough to generate a clean "no" — all of it accumulates into drag. At scale, drag becomes the defining constraint on what you can build.
How AI shifts the floor
AI is resetting the floor on velocity, but not the ceiling. Customer signal to working prototype in the same week — that's the new floor for teams using AI well. The teams using it badly are producing more output with the same drag still in place: more documents, more meetings, more half-built features that never reach a real customer. Speed isn't the variable that's changed. The variable is how quickly your organisation can decide.
The lesson
Product velocity isn't a function of effort. It's a function of organisational design. How decisions get made, how teams are structured around outcomes rather than functions, how you handle the tension between quality and speed — these are leadership choices, not engineering ones, and AI doesn't change which they are.
The companies that sustain real velocity as they scale are the ones that treat it as an explicit priority. Not an accident of a scrappy early team, but a system deliberately built and protected as the company grows. The ones that lose it almost always lose it the same way: by adding process to manage complexity instead of removing the complexity at the source.