I build products, and the systems that decide which products deserve to exist.
I am a Head of Product and AI product manager working across consumer platforms, fintech, intelligent interfaces, growth, and monetization.
My work spans the full product lifecycle: identifying the opportunity, challenging the premise, shaping the proposition, aligning teams, shipping the product, measuring its behavior, and deciding whether to scale, redesign, or stop.
I have helped grow products to more than a million subscribers, greenlit new standalone businesses, removed expensive features that did not justify their economics, rebuilt product operating models, and designed AI systems from first concept to working deployment.
The title is product. The advantage is that I can operate deeply inside the disciplines most product leaders have to delegate.
Dubai, 2026 Product management with sharper instruments.
Most product leaders depend on research, design, analytics, and technical teams to translate reality for them.
I work with those teams, but I can also interrogate each discipline at practitioner depth.
I can question the behavioral model behind a roadmap, the interaction logic behind an interface, the confidence behind an experiment, and the architecture behind an AI feature, without losing sight of the commercial decision they are supposed to serve.
That range matters most when the product is ambiguous, the market is culturally complex, or the technology does not yet have an established playbook.
- Product strategy
- →What deserves investment?
- Behavioral evidence
- →What is actually true?
- HCI and design
- →Why will the system work for humans?
- Analytics
- →Is the behavior commercially meaningful?
- AI and prototyping
- →How quickly can we make the idea real?
I reduce uncertainty before it becomes expensive.
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01 — Frame the bet
Before discussing features, I define the decision.
What behavior are we trying to change? What business outcome depends on it? What would have to be true for the product to deserve investment?
A roadmap without a product thesis is a backlog with better typography.
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02 — Search for evidence that can kill it
Good discovery does not exist to validate an idea.
I look for the evidence that would prove the premise wrong: weak demand, broken economics, cultural mismatch, low retention potential, operational complexity, or a user problem that is not important enough to solve.
The earlier a weak bet dies, the more capital the company keeps.
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03 — Make the smallest credible version real
I move from strategy into product definition, interaction logic, prototype, and technical feasibility.
For AI products, that includes model behavior, evaluation criteria, human control, failure states, confidence, and the moments where the system should stop pretending it knows.
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04 — Measure the shape, not just the number
Adoption alone is rarely enough.
I look at who adopted, where they hesitated, what they returned for, which cohort retained, how the behavior affected ARPU or LTV, and whether the product created durable value or temporary curiosity.
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05 — Scale, reshape, or shut it down
A shipped product is not a protected product.
When the evidence supports the thesis, I scale it. When the behavior is promising but the mechanism is wrong, I redesign it. When the economics do not hold, I stop it.
Product leadership includes knowing when persistence has become waste.
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Product and portfolio strategy
Zero-to-one products, product vision, roadmaps, prioritization, portfolio decisions, market expansion, proposition design, and product sunset.
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AI-native products
Agentic and multi-agent systems, conversational AI, voice AI, recommendation experiences, AI evaluation loops, human–AI interaction, and full-stack product prototyping.
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Growth and monetization
Acquisition, activation, onboarding, paywalls, pricing, subscriptions, ARPU, LTV, churn, retention, discovery, and experimentation.
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Complex product systems
Fintech, trading, transactional banking, entertainment ecosystems, government platforms, public infrastructure, smart devices, and multilingual products.
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Product organizations
Operating models, team design, research and design integration, vendor strategy, executive decision systems, and the workflows that turn evidence into action.
- 1.3M subscribers
- Yango Play growth from launch across ten markets
- +50% music discovery
- Navigation and recommendation model redesigned
- Up to $4M avoided annually
- Gaming investment sunset after LTV and retention analysis
- ~$5M saved annually
- Product operations restructured across four fintech platforms
- Regional product firsts
- Transactional banking chatbot · bilingual Alexa experience · public EV-charging UX
The common thread is not a particular industry or interface.
It is the ability to enter a difficult product system, understand what is really happening, and change the decision.
Architecture taught me systems. Psychology taught me doubt. Product taught me consequence.
I entered digital product through architectural design, where structure, movement, hierarchy, and human behavior are inseparable.
I later studied psychological sciences at Brunel University London, focusing on cognitive psychology, research methods, human factors, and HCI.
That combination still shapes how I work. I see products as behavioral systems: structures that guide attention, decisions, trust, and action over time.
I am also trained in product delivery and AI product management through PMP, IBM, and Duke programs. The qualifications matter less than how they connect: systems thinking, behavioral science, delivery discipline, and technical product judgment.
- >15+ years
- >20+ markets
- >Consumer · AI · Fintech · Telecom · Government
- >English · Arabic · French
- >Dubai, UAE · Golden Visa
Clear decisions. Strong teams. No theater.
I have built and led cross-functional product, research, and design teams, managed multimillion-dollar programs and product budgets, worked directly with CPOs and senior leadership, and partnered with engineering teams, regulators, consultancies, and technology vendors.
My leadership style is direct but not performative.
I expect teams to disagree with evidence in hand, expose risk early, write clearly, and separate personal attachment from product judgment.
The goal is not consensus.
The goal is a decision strong enough that the team understands why it is making it, and what evidence would cause it to change.