Audience: Senior and lead PMs preparing for the system-design rounds that gate senior roles.
Pain: Those rounds screen PMs out, yet there's no realistic way to practise architecture or get scored on it.
The bet: PMs don't need to code — they need to reason about systems and get feedback fast. An AI grader closes that loop in seconds.
My move: Defined the 7-module, 23-challenge curriculum, built the canvas and the Claude scoring rubric, and shipped paywall, certificates and onboarding solo.
Outcome: Live and taking paying users, with AI-scored feedback in about 30 seconds.

FractnHR

B2B SAAS · SOLO BUILD · IN PRODUCTION

Solo · 4 wks

live demo ↗

Audience: A fractional HR consulting firm and the client companies it serves.
Pain: Client requests sprawled across email, Drive and Slack — nothing tracked, nothing auditable against retainers.
The bet: Position it as services-as-software — a workflow wedge and data moat — not another per-seat SaaS, to capture more of the consulting spend.
My move: Owned it end-to-end: data model, multi-tenant row-level security, audit-immutable trails, retainer gauges, client portal and a full test suite.
Outcome: Designed and shipped to production in about four weeks — solo, end-to-end.

BeinFit

CONSUMER PLATFORM · LIVE, MONETIZED

Live · paying

bein.fit ↗

Audience: UK fitness and wellness professionals, and the clients who book them.
Pain: Solo pros lose income to no-shows, manual scheduling and tax admin, running their business across disconnected tools.
The bet: Bundle bookings, subscriptions and HMRC tax into one place — and own distribution by working alongside GTM specialists instead of outsourcing it.
My move: Built the three-tier Stripe monetization funnel and HMRC integration, and cleared a seven-issue Apple App Store rejection to ship iOS.
Outcome: Live and monetized with paying customers; iOS app through review.

Rompo

0→1 · FOUNDER · VALIDATION

0→1 · live

rompo.travel ↗

Audience: Groups planning trips together, plus solo travellers organising the details.
Pain: Trip planning is scattered across chats, docs and spreadsheets, with no single source of truth.
The bet: Validate the wedge before building wide — run research and product on dual tracks, and kill it if the data says so.
My move: Built multi-party planning, expense tracking and sharing, run as parallel research and product tracks.
Outcome: Live and in validation with real users.

HOW I OPERATE

Three rules I actually follow.

Frame before you build.

My default under a fuzzy problem is to start building. The discipline I have trained is to first map who actually has the problem — then ship against that.

Kill it when the data says so.

I have shipped features to production and discontinued them when 30-day retention proved they were not working. Outcomes over attachment.

Work alongside the experts.

I bring in specialists — GTM, engineering — and stay in the room while they work, because that is how the product and I both get sharper.

ABOUT

DD.

I am a product operator who builds. Nine years across fintech, AI and consumer — AIB, Globant, Bank Hapoalim, Arrival, and two companies I helped start.

I am strongest at the seam between engineering, commercial and operations — and I do not stop at the strategy. I will sketch the data model, wire the payments and ship the thing. That is how I cut a lending platform's drop-off from 30% to 10%, and how I built PMLabs and FractnHR end-to-end, solo.

RICHMOND, WEST LONDON · INNOVATOR FOUNDER VISA · AVAILABLE FOR FRACTIONAL + ADVISORY

WRITING

ON SUBSTACK ↗

15 Jun 2026

READ ↗