AI
AI development, unlike traditional software engineering, isn’t a straight line. Models need to adapt to new data, user behaviors, and shifting business conditions. In fast-paced environments, agility becomes more than just a buzzword—it’s a necessity. The key to success in AI is to build systems that can
Product Lifecycle & Roadmaps
When it comes to product roadmaps, most of us are used to thinking in linear terms. We develop features, launch them, and then move on to the next big thing. But with AI, the roadmap looks a little different. Unlike traditional software features, AI systems don’t just get built
AI
Building AI-powered products isn’t just about understanding the technology—it’s about bridging the gap between product goals and technical execution. To get AI right, product leaders need to collaborate effectively with data scientists. It sounds simple, but in practice, these two groups often speak different languages, and misalignment
AI
In the world of product development, it’s tempting to chase the latest trends, and AI is no exception. Every day, we hear about how AI is transforming industries, creating new possibilities for automation, personalization, and insight. But as product leaders, it’s our job to separate the hype from
AI
In 1997, chess champion Garry Kasparov took on IBM’s supercomputer, Deep Blue. It was a match that symbolized the rising potential of artificial intelligence (AI). After Kasparov won the first round, many assumed humans still held the upper hand. But then Deep Blue came back to win, marking a