Product Manager, Lab

📋 Description

• • Are you a visionary Product Manager with a passion for exploring uncharted territories and a knack for de-risking bold, high-uncertainty product opportunities? Fundraise Up is seeking an exceptional individual to lead our innovative 'Lab' initiative, a dedicated space for exploring the future of digital fundraising.
• • At Fundraise Up, we're not just scaling our core platform; we're strategically investing in high-risk, high-upside product bets that have the potential to redefine the entire fundraising landscape. The Lab is at the forefront of this mission, tasked with systematically exploring what's next – new capabilities, emerging categories, and novel ways technology can reshape how nonprofits connect with their supporters.
• • As the Product Manager for the Lab, your primary objective is to reduce uncertainty and drive learning, rather than simply shipping features. You will own promising ideas from their nascent stages through to critical investment decisions. This involves deep exploration, rigorous hypothesis framing, rapid experimentation, and ultimately, making clear 'scale, pivot, or kill' decisions. The expectation is that most ideas will be terminated early, with only a select few graduating to our Core or New Markets teams, backed by robust evidence.
• • Success in this role is measured by the speed of learning and the quality of decisions made, not by the volume of output or traditional adoption metrics. You will be instrumental in identifying opportunities that emerge from new technologies, advancements in AI, shifts in data utilization, evolving platform capabilities, or fundamental infrastructure changes.
• • Your responsibilities will include translating nascent signals and technical possibilities into clear, testable product hypotheses. You will explore ideas even before a clear buyer, established category, or definitive demand signal exists. To manage this exploration, you will maintain a dynamic backlog, meticulously documenting risks, assumptions, and learning objectives for each initiative.
• • A crucial aspect of your role will be designing experiments and defining explicit 'kill criteria' before any development begins. You will frame experiments around the single riskiest assumption, ensuring that each test is designed for maximum learning efficiency. You will select the appropriate fidelity for each experiment, ranging from low-fidelity prototypes and technical spikes to 'wizard-of-oz' tests and live pilots, always building 'just enough' to learn and avoiding premature optimization.
• • You will execute scrappy prototypes, Minimum Viable Products (MVPs), and pilots with minimal scope, working in close collaboration with Engineering, Design, Data, and Go-to-Market teams. Ruthless prioritization of learning speed will be paramount, ensuring that experiments deliver actionable insights quickly.
• • Based on the outcomes of these experiments, you will synthesize findings into opinionated recommendations: Scale, Iterate, or Kill. Clear communication of what was tested, what was learned, and what remains unknown will be essential. You will be empowered to avoid 'zombie initiatives,' ensuring every experiment concludes with a decisive outcome and the courage to terminate your own ideas swiftly when evidence suggests they are not viable.
• • When an opportunity demonstrates strong potential, you will prepare it for a seamless handoff to the appropriate team. This includes providing validated value and problem hypotheses, comprehensive evidence from experiments or pilots, clearly defined risks, assumptions, and success metrics, and a proposed ownership and scaling model. Importantly, the Lab does not run scaled products; ownership transfer will be complete.
• • Operating with transparency is key. You will maintain a visible Lab portfolio, showcasing what is being explored, the rationale behind it, and the current signals. You will publish decision memos and learning summaries, and share insights from failed experiments openly when clear lessons have been learned.
• • You will leverage AI to accelerate learning, utilizing modern AI tools to expedite research, synthesis, prototyping, and experimentation. You will explore AI-enabled product ideas with a realistic perspective, considering factors like cost, latency, data requirements, and accuracy, and critically distinguishing genuine capability shifts from mere hype. You will help the wider organization understand when AI truly accelerates learning and when it does not.
• • Finally, you will selectively launch bold initiatives, even when short-term adoption is uncertain. These launches will be treated as genuine product bets, not mere demonstrations, designed to test future categories, shape market perception, and signal technical leadership. You will be explicit about the intent behind each launch: whether it's for learning, creating optionality, or external signaling.