Product ownership for how 7 million monthly active users discover, understand and act on weather data, spanning product vision, discovery, roadmap decisions, delivery and post-launch learning.
The core weather-information experience, including management of the rain radar, is shaped through customer evidence, behavioural insights and the decisions people need to make as conditions change. Those inputs become a clear vision and prioritised roadmap, aligned with engineering, design and data before delivery.
The AI weather experience progressed from opportunity discovery and value validation to launch, production and iteration. Product responsibility covered LLM evaluation, guardrails and observability: defining response-quality criteria, testing failure cases, setting behavioural boundaries and monitoring real usage to guide improvements after release.
An agent-enabled product system connects research synthesis, product decisions and the preparation of review-ready PRDs, tickets and design inputs. Structured checkpoints keep people accountable for judgement while reducing a workflow that previously took weeks to roughly a day.
A cross-product growth strategy uses WebView experiences to connect distribution with user journeys across platforms. The approach evaluates both where an experience is surfaced and how users reach it, making acquisition, activation and adoption part of one journey rather than isolated feature targets.
The push-notification strategy combines segmentation, context and relevance around different weather needs. Engagement is evaluated alongside retention and downstream product use, so notification value is measured by the useful action it enables instead of delivery or click volume alone.
