What I Do
- Zero-to-One Product Strategy: Define the right problem, align on ICP/JTBD, deliver a v1 people adopt and pay for.
- Validation & Early Traction: Run structured discovery, market narrative testing, and pilot programs to shorten time-to-first revenue.
- AI-Native Workflow Design: Embed AI where it compounds value: data capture, matching, decision support, measurable outcomes.
- Execution with Quality: Align strategy, architecture, and QA so speed doesn't compromise reliability.
Current Focus: Wicely
Building AI-native SaaS for R&D management in mid-market manufacturing. Helping product engineering and research teams save 20-30% of their weekly time through systematic data collection, team collaboration, and compounding knowledge.
Why purpose-built matters: R&D teams need data sovereignty, security from inception, and team-wide memory. Enterprise AI isn't consumer AI at scale, it's a fundamentally different product built for different requirements.
Core capabilities:
- Technology scouting and R&D pipeline management
- R&D project tracking with measurable outcomes
- Research team collaboration and knowledge capture
- Turning technical discoveries into competitive advantages
If that sounds familiar: book a 30-min intro call →
The Compounding Gap
Most R&D teams I work with face the same problem. They generate knowledge constantly: through experiments, supplier evaluations, customer conversations, competitive research. But the organisation doesn't hold onto it.
Projects end and the learnings stay in someone's notes. Engineers leave and take six months of context with them. Decisions get made in Slack threads and become irretrievable three weeks later.
The result: the team starts from scratch, repeatedly. The same mistakes resurface. The same ground gets covered. The compounding that should happen, doesn't.
This is the problem Wicely solves. It's also the lens through which I approach every advisory engagement: not "how do we add more process?" but "where is knowledge leaking, and how do we make it stick?"
How I Work
- Problem-first: Clarify the real problem before designing the solution.
- Outcome-focused discovery: Instead of "What do you need?", I ask "Walk me through your last frustrating day." Specificity reveals real problems, not feature wishlists.
- Small, testable bets: Weekly learning loops with explicit hypotheses and go/no-go rules.
- Opinionated & measurable: Codified playbooks that make outcomes repeatable.
Background
- Product leadership: Building & shipping SaaS, leading cross-functional teams, owning discovery → delivery → adoption.
- Entrepreneurship: Co-founding and scaling early-stage ventures.
- Industries: Manufacturing, Marine, Climate Tech, MedTech, EdTech, IT Infrastructure. Cross-industry pattern recognition drives better solutions.
- Quantitative edge: MSc Mathematics, plus degrees in Business Intelligence, MBA, IT Project Management.
- Craft: Mathematics-informed product thinking, engineering-grade standards, and business model clarity.
Track Record
- 15+ years in product leadership and entrepreneurship
- 4 companies co-founded, including scaling to €2M+ revenue
- 10+ digital products delivered across MedTech, B2B SaaS, eCommerce
- 100+ customer interviews driving product roadmap decisions
- Scaled teams from 25 to 200 employees across growth phases
Working Together
Currently focused full-time on building Wicely. Limited availability for part-time advisory engagements in product strategy, customer discovery, and AI-native workflow design. Subject to capacity and strategic fit.
How engagements typically work:
- Intro call (30 min, free): A short conversation to understand your situation, the problem you're solving, and whether there's a genuine fit.
- Scoping session: If there's a fit, we define the specific problem, agree on measurable outcomes, and set a realistic timeline. Typically 4-8 weeks.
- Focused engagement: Structured, time-boxed work with clear deliverables and a weekly check-in to stay aligned and adjust course.
Who This Is For
Good fit
- Mid-market manufacturer (50-500 employees) with an active R&D or product engineering team
- R&D workflows that feel fragmented: scattered tools, unclear ownership, or knowledge that lives in someone's head
- A leader who can champion change internally and has budget for a focused engagement
- Teams that want measurable process improvements, not just more software
Not a fit
- Early-stage startups looking for a full-time product manager or hands-on delivery lead
- Enterprise organisations with multi-month RFP procurement processes
- Teams looking for someone to manage a pre-defined roadmap or run sprints
- Engagements requiring full-time on-site presence
If that describes your situation: let's talk →
Principles
- Simplicity scales: Fewer steps, clear state, named nouns.
- Data with purpose: Capture only what drives decisions.
- UX is process: Remove ambiguity and accelerate progress.
- Trust through transparency: Clear metrics, trade-offs, and ownership.
📍 Based in Barcelona, Working Globally | 🌐 English, Spanish, Catalan, Russian