Trusted to lead, not just to build

Track record

Three projects. Two as CTO, one my own. Described as the decisions they actually were rather than as outcomes — where there's no honest number to point at, there's no number.

Vision ESG

CTO

I came in as CTO with the platform still on a whiteboard. The brief was the whole system: data model, architecture, what gets built in-house and what gets bought.

The decision that mattered most wasn't a technical one in the usual sense. It was the scope call — working out which parts of the vision belonged in version one and which were going to quietly sink it if we tried. Saying no to features in a first build is unpopular in the room and obvious in hindsight.

What I take from it: the hardest part of being the technical authority is being the person willing to cut, and then owning that cut when someone asks six months later why a feature is missing.

Rising Collective

CTO

Same title, same shape of problem: design the system, then decide who builds it.

I built it myself. Not because delegating is wrong, but because at that size the design and the implementation kept correcting each other — decisions that looked clean in a diagram turned out wrong the moment they hit real code, and I wanted the feedback loop to be one person long.

What I take from it: an architect who never touches the build stops finding out which of their decisions were wrong.

Flushiest

Founder, built & launched

My own product. I built it, launched it, and got it covered by four news outlets and radio on a marketing budget that was effectively nothing.

The coverage is the part people ask about. The part that actually taught me something was everything before it — I assumed shipping was the hard bit, and found out that getting a working product in front of people is a completely separate discipline with its own rules, several of which are legal rules I didn't know existed. I ordered a print run of flyers before finding out how constrained handing them out in Amsterdam actually is.

What I take from it: the gap between "it works" and "people know about it" is where most good products die, and almost nobody is warned about it in advance. That gap is what I now advise on.

Want the thinking behind these?

The writing goes into more depth on the parts that generalise — launch constraints, AI-use policy, and what the Flushiest lesson actually cost.

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