For decades, product roadmapping was straightforward. It used to be just a list of features to be built and deployed sequentially. But with artificial intelligence, that system of working is no longer sufficient. AI is capable of transforming a product from a static tool into a dynamically adaptive entity. As a result of this modification, product roadmapping requires a new approach. Product roadmaps need to go beyond simple feature delivery, they should incorporate continuous data acquisition, model optimization, and ethical implications of a system that learns.
This implies product leaders should be equipped to foresee the development of intelligent products, and Henry Oribe is great at that. Many product managers still plan functionality and timelines, but Henry plans a roadmap that makes provision for the unique complexities of AI development. He understands that the most critical factor in a world increasingly shaped by AI isn’t solely about which features to develop, but rather how to enable a product to learn and optimize its performance over time.
A significant component of his planning is how to get data. Regular features can be built and deployed, but AI is useless if there’s no data to train its models. So, Henry’s roadmaps include clear plans for how the product will obtain the necessary data. This may require focusing on new user inputs, integrating external data sources, or developing internal tools for data labeling. He ensures the team understands that data is the most important element for product improvement.
He also understands that AI solutions need roadmaps that focus on improving the models. A regular feature is done once it’s deployed, but an AI model is never really done. It needs to be continuously monitored, retrained, and refined as fresh datasets are incorporated and user behavior changes. Henry’s roadmaps account for this ongoing work, scheduling time to evaluate model performance, A/B testing different models, and deploying improvements to ensure the product intelligence remains suitable and accurate.
Henry also integrates ethical AI principles into his roadmaps. He understands that developing more intelligent products should not negatively impact fairness, transparency, or privacy. So, his roadmaps include provisions for detecting bias in algorithms, interpreting AI decisions to users, and ensuring data protection. By accounting for these considerations, he ensures the team builds an ethical product from the outset, instead of rectifying errors later.
Finally, he’s good at balancing new, experimental features with product stability. AI development is often experimental, A/B tests could reveal a hypothesis is wrong, or a new model might not work as expected. Henry’s roadmaps are designed to handle this uncertainty while maintaining the product’s foundational reliability.
Henry Oribe’s leadership turns a product roadmap from a static list of features into a blueprint for a product that learns and grows. He is a visionary who ensures his teams build products not just for today but are orchestrating the intelligent systems of the future.
