Capture the vision precisely
Lead stakeholder discovery, align goals and constraints, and define the intended experience across user flows, interface states and micro-interactions.
- Vision capture
- Decision rationale
I lead AI-native products from strategy to delivery.
I originate product vision and strategy, validate market opportunities, and personally define product features, roadmaps, backlogs and sprint priorities. I lead cross-functional teams through AI-native prototyping, technical definition, testing and delivery, with deep expertise in UX, conversion strategy and product execution.
Client Advisory Boards, interviews, heatmaps and user analytics
Product vision, self-directed backlogs, MVP scope, epics and roadmaps
AI-assisted prototypes, React/Next.js and technical product requirements
Customer retention, monetization and cross-functional product leadership
My decisions are informed by deep competitive, market and behavioral research, with validation down to individual interactions before concepts reach user testing. Each feature starts with a defined customer problem, a reason to build it now and the evidence that would change the plan.
Across product leadership, consulting and startup work, I have led strategy sessions focused on defining stakeholder vision, validating markets, identifying competitive opportunities and improving conversion. I coach teams to support each feature, flow and interaction with research, customer psychology and evidence rather than visual preference.
I help founders and stakeholders define what the product should become, who it serves and where it should compete, then translate that direction into the priorities teams build against.
I use competitor benchmarking, cross-category audits and market analysis to uncover where a product can win and establish its differentiated value.
My design teams document the rationale behind micro-features, behavior, navigation, messaging and interaction patterns, so every detail can be defended in review before it reaches development.
I apply customer motivations, persuasive messaging, onboarding friction and retention principles to product decisions. I also served as the sales subject-matter expert for an IT consulting firm’s instructional design team.
I develop product vision in close collaboration with stakeholders, often as the primary product stakeholder. I define the decisions behind each feature, record the rationale, and carry that vision through backlog, design, implementation and review. I expect the design rationale to hold up beyond the wireframe.
Lead stakeholder discovery, align goals and constraints, and define the intended experience across user flows, interface states and micro-interactions.
Use UX and conversion psychology to anticipate customer questions, motivations, hesitation and trust signals before they become barriers to action.
Combine familiar interaction patterns with competitive research and cross-category inspiration to create meaningful product differentiation.
Train teams in market research, competitive analysis and conversion strategy, drawing on curricula I authored for startup launch and growth programs.
I carry the same product intent from customer research through strategy, technical definition, delivery and outcome measurement. Product, design, engineering and QA work from one shared definition of the problem, the scope and the expected result.
Client Advisory Boards, interviews and usability studies reveal customer needs. Heatmaps, click and scroll analytics, surveys and feedback show where experiences need to improve.
Define product vision and positioning from market evidence and adjacent-market research. Connect pricing, packaging and monetization to investment decisions and the product’s long-term commercial strategy.
Own epics, MVP scope and sprint priorities across cross-functional squads. Keep each squad’s backlog tied to the roadmap so sprint work traces back to a customer outcome and a business goal.
Build AI-native prototypes with React and Next.js. Define API and service requirements, data models, engineering constraints, edge cases and acceptance criteria with delivery teams.
Apply advanced UX, sales and conversion psychology to onboarding, activation and retention. Remove hesitation at decision points so customers understand the value, trust the product and take the next step.
Carry products through release readiness by specifying expected behavior, verifying critical journeys and confirming release criteria. After launch, measure outcomes against the success metrics set before the build.
I align teams around measurable product goals and balance speed, cost, quality and technical possibilities as decisions move toward delivery. Every step produces evidence or a testable artifact that the next step builds on.
Talk to users, clients and stakeholders to collect evidence.
Audit competitors, market leaders and adjacent categories.
Define MVP scope and future roadmap around value and effort.
Prototype and optimize interfaces and decision flows.
Define technical requirements, acceptance criteria, edge cases and development test cases before coding.
Coordinate test-driven implementation, verify expected behavior with QA, then measure and iterate.
I translate validated strategy into working prototypes and testable requirements, then stay involved as teams move from definition to delivery.
feature: onboarding-flow condition: first-time-user require: clear-next-action expected: successful-activation
Product requirements, user journeys, interface states, user stories, acceptance criteria and edge cases.
AI-assisted working prototypes, API contracts, service boundaries, integration dependencies and engineering specifications.
Resolve implementation questions before coding so product, design, engineering and QA share the same intended experience. Agree on release criteria up front.
I use market and competitive evidence to answer three questions before a feature earns engineering time. Is there a market, is this a real client problem, and does the proposed experience work?
I study direct competitors, best-in-class products and out-of-category experiences. I compare customer expectations, underserved needs, positioning, buying motivations and commercial potential to identify a credible point of differentiation.
I work from client conversations, support patterns, feedback and behavior data. I separate recurring problems from isolated feature requests and challenge assumptions before they become roadmap commitments.
Before user testing, I challenge each proposed micro-feature, interaction, flow and message against market research, product patterns and conversion principles. I then use working prototypes and usability studies to test the experience and refine it with engineering and QA.
I evaluate the target customer, their current alternatives and the competitive landscape before deciding what the product should offer and which bets deserve engineering capacity.
Segment the audience, review customer feedback and current workarounds, and identify the segment with the strongest reason to act now.
Compare existing customer expectations, barriers to adoption and switching costs to shape a value proposition customers will act on.
Size the commercial potential against build cost, engineering dependencies and technical feasibility to decide which bets earn a place on the roadmap.
I connect product goals to customer and business measures such as activation, retention, task success, adoption and conversion. Research, behavioral analytics and usability testing help me diagnose friction, choose the next investment and evaluate whether a product decision is working.
Customer churn reduction · B2B SaaSResearch into onboarding and retention friction set the priorities for the experience improvements behind this result.
Checkout usability task completionFive participants completed eight test tasks. Hesitation by three participants at the primary action informed a review-first checkout redesign.
Scope and positioning decisionsValidation findings set which marketplace journeys and prospecting capabilities were prioritized for the first release and which were deferred.
I also design Client Advisory Board research programs, including recruitment criteria, interview protocols, usability tasks, feedback synthesis and decision-making frameworks.
I validate the product concept and its individual decisions from several research angles before putting a prototype in front of users. Testing then challenges what the earlier research suggested, instead of being the first time the idea is evaluated.
Define the stakeholder vision and hypotheses, then test the concept against competing approaches, customer behavior and the rationale behind positioning and conversion decisions. Challenge the proposed flows and messages before committing to a design direction.
Use moderated tests, interviews, heatmaps, funnels and analytics to see where users hesitate, misread or drop off. Use the findings to refine the product, recheck assumptions and prioritize changes.
Competitive evidence provides an informed starting point. Observed behavior can confirm or overturn it. I draw on more than one source of evidence for a product decision.
I build the product backlogs and roadmaps, define features and epics, and set sprint priorities. Research and client input inform the work, and cross-functional reviews surface insight and risk before I decide sequencing, scope and staffing.
Bring together customer and client research, market gaps, product analytics, stakeholder requests and strategic goals. Frame each candidate epic around the problem, expected value and evidence.
Bring my proposed epics and sprint priorities to product, design, engineering and QA for review. Use structured voting and discussion to challenge assumptions, uncover risks and surface dependencies before work is committed.
Evaluate customer impact, market opportunity, commercial potential, effort, technical dependencies, delivery risk and team capacity. Advance, simplify, defer or remove work accordingly.
Break the approved scope into build-ready stories and acceptance criteria, assign the relevant cross-functional squad and align its sprint commitments, QA requirements and success measures.
I prioritized the client and talent journeys first, then planned related features around technical readiness so squads could focus on the work that unlocked the next product milestone.
I framed each initiative around a customer problem and expected value. That gave the team a consistent basis for comparing priorities across the product.
I scoped a two-sided talent marketplace, designed how an AI-native prospecting platform’s agents work together, and led retention improvements at a B2B SaaS company.
Defined marketplace workflows, policies, APIs and integrations across NestJS services. Led AI-assisted development of the Next.js interface, with 70 core UI components and 104 Storybook stories.
Product vision · Technical requirements · AI-native executionSequenced epics by dependency. Time tracking preceded payouts, and billing enabled transactions. Defined acceptance criteria and QA handoffs so squads stayed on the work that unlocked the next milestone.
MVP strategy · Product prioritization · Technical feasibilityLed product, customer-experience and retention improvements across onboarding, dashboards and lifecycle journeys. Aligned research, redesign and roadmap decisions with activation and long-term customer value.
Customer retention · Product strategy · Business impactDefined specialized AI agents and conversational orchestration so customers could describe goals in natural language. Scoped prospect insights, audience recommendations and coordinated campaign workflows.
Agentic product strategy · Data interpretation · Conversational orchestrationConnected product flows to service responsibilities, API behaviors, integration requirements and QA scenarios across both platforms, giving product, engineering and QA a shared delivery blueprint and a single reference for every service.
Technical product strategy · Service requirements · Cross-team executionDefined feature boundaries and dependencies before engineering estimation so each initiative could be evaluated on its own. Turned product scope into actionable initiatives with build-ready requirements and a clear delivery plan.
Epic definition · Product planning · Delivery readinessI choose what matters now, what can wait and what has to change so a team can build something useful without unnecessary complexity.
My decision: Focus the initial marketplace on profiles, listings, search and onboarding. Defer work that does not unlock the core client and talent experience, and protect that scope as new requests arrive.
Customer value / Scope / Time to marketMy decision: Simplify project editing during checkout rather than delay the MVP for a full planning experience. Use usability-test hesitation to guide a review-first flow.
Usability / Feasibility / Delivery speedMy decision: Prioritize audience definition, AI agents and goal-driven orchestration ahead of the landing page. In the proposed experience, customers can explain campaign objectives in plain language and still use the traditional interface when they need it.
AI-native product vision / User experience / Roadmap prioritizationMy decision: Require product specifications, acceptance criteria and QA cases before an epic reaches development, with clear product, engineering and QA ownership in each staffed squad.
Delivery readiness / Quality / AccountabilityI interview, recruit, select and train people across product, UX, engineering and QA. I organize teams around owned epics, develop team leads and guide delivery with clear responsibilities.
Interviewed and selected product and UX professionals, then trained designers in market research, innovation and conversion strategy. Coached product managers, business analysts and Scrum Masters.
Recruited frontend, backend, full-stack and AI engineers. Formed a separate data science team, aligned contributors around product requirements, and made technical decisions and documentation part of delivery.
Established QA, DevOps and delivery standards across squads, including escalation paths and handoff practices, so product, engineering and quality teams shared ownership from definition through release.
Coached engineers to understand the customer problem behind each ticket and designers to think strategically. New team members learned from specifications, acceptance criteria and QA cases.
My career spans startup advisory, SaaS product leadership, enterprise financial services, marketplaces and AI-native platforms. Across these roles, I have owned roadmaps and MVP scope and turned customer insight into products teams could deliver.
Owned product vision and priorities for a talent marketplaceand an AI-native B2B prospecting platform. Led AI-native prototypes,technical scope and a separate data science team. Establisheddocumentation-first delivery so engineers understood each decision.
Led SaaS product strategy, roadmaps, UX and growth.Aligned onboarding and retention initiatives with product goals,turning customer friction into experience improvements thatcontributed to a 43% reduction in customer churn.
Advised on discovery and product positioning for an AI-focusedworkforce intelligence platform. Helped frame the marketopportunity and identify MVP priorities, connecting customerneeds to a focused direction for product planning.
Led product vision and market differentiation for a consumerplatform. Connected customer research to MVP decisions andfeature scope, then guided cross-functional backlog planningaround the consumer experience.
Led product research, enterprise UX and strategy consultingacross digital businesses and client engagements. Facilitatedstrategy reviews to shape positioning, requirements andinteraction decisions around a shared product direction.
Advised startup founders on customer discovery and priorities,connecting competitive differentiation with growth strategy.Created more than 200 training videos to share the methodand support informed product decisions throughout planning.
Jira, Linear, ProductBoard, Asana, Trello and Confluence for product vision, roadmaps, epic ownership, backlog prioritization, MVP scope and cross-functional Scrum delivery.
Figma, FigJam, Miro, Sketch, Adobe Creative Suite and Axure for interactive prototypes, usability studies, heatmaps, behavior analytics and reusable design systems.
React, Next.js, Tailwind CSS, TypeScript familiarity and GitHub for AI-assisted prototypes, service specifications, API contracts and test-driven delivery.
Excel, conversion funnels, retention cohorts, KPIs and Net Promoter Score (NPS) to assess behavior, interpret experiments and guide product decisions.
Architecture decisions, user stories, QA plans and cross-team handoffs, written so product, design, engineering and QA work from the same source of truth.
Claude Code, Claude Desktop, ChatGPT, Codex and Figma MCP for working prototypes, AI-native MVPs, research synthesis and code review.
Open to Senior AI-Native Product Manager, Senior Technical Product Manager and Lead Product Manager roles where market insight, product judgment, AI-native execution and cross-functional leadership create meaningful customer and business value.
Discuss an opportunity